ISSN 1210-2512 (Print)

ISSN 1805-9600 (Online)

Radioengineering

Radioeng

Proceedings of Czech and Slovak Technical Universities

About the Journal Editorial Board Publishing Department Sponsors and Supporters Opened special issues Společnost pro radioelektronické inženýrství [CZ]
About the Journal
Feature Articles
Editorial Board
Publishing Department
Society [CZ]
Log out
Your Profile
Administration

September 2012, Volume 21, Number 3

Show all Hide all
RIS File
BibTeX

J.Z. Zhang, F.Q. Yao, H.S. Zhao [references] [full-text] [Download Citations]
Distributed Clustering in Cognitive Radio Ad Hoc Networks Using Soft-Constraint Affinity Propagation

Absence of network infrastructure and heterogeneous spectrum availability in cognitive radio ad hoc networks (CRAHNs) necessitate the self-organization of cognitive radio users (CRs) for efficient spectrum coordination. The cluster-based structure is known to be effective in both guaranteeing system performance and reducing communication overhead in variable network environment. In this paper, we propose a distributed clustering algorithm based on soft-constraint affinity propagation message passing model (DCSCAP). Without dependence on predefined common control channel (CCC), DCSCAP relies on the distributed message passing among CRs through their available channels, making the algorithm applicable for large scale networks. Different from original soft-constraint affinity propagation algorithm, the maximal iterations of message passing is controlled to a relatively small number to accommodate to the dynamic environment of CRAHNs. Based on the accumulated evidence for clustering from the message passing process, clusters are formed with the objective of grouping the CRs with similar spectrum availability into smaller number of clusters while guaranteeing at least one CCC in each cluster. Extensive simulation results demonstrate the preference of DCSCAP compared with existing algorithms in both efficiency and robustness of the clusters.

  1. MITOLA, III, J., MAGUIRE JR, G. Cognitive radio: making software radios more personal. IEEE Personal Communications, 1999, vol. 6, no. 4, p. 13–18.
  2. CHITTABRATA GHOSH, SUMIT, R., CAVALCANTI, D. Coexistence challenges for heterogeneous cognitive wireless networks in TC white spaces. IEEE Wireless Communications, 2011, vol. 18, no. 4, p. 22-31.
  3. AKYILDIZ, I. F., LEE, W.-Y., CHOWDHURY, K. R. CRAHNs: Cognitive radio ad hoc networks. Ad Hoc Networks, 2009, vol. 7, no. 5, p. 810–836.
  4. STEENKISTE, P., SLIKER, D., MINDEN, G. J., DIPANKAR RAYCHAUDHURI, Future directions in cognitive radio network research. NSF Workshop Report, March, 2009.
  5. HAO NAN, SANG-JO YOO, TAE-IN HYON Distributed coordinated spectrum sharing MAC protocol for cognitive radio. In Proc. of IEEE International Symposium DySPAN2007. Dublin (Ireland), April 2007, p. 240–249.
  6. QUANSHENG GUAN, YU, F. R., SHENGMING JIANG, GANG WEI Prediction-based topology control and routing in cognitive radio mobile ad hoc networks. IEEE Transactions on Vehicular Technology, Nov. 2010, vol. 59, no. 9, p.4443-4452.
  7. TSENG, Y.-C., NI, S.-Y., CHEN, Y.-S., SHEU, J.-P. The broadcast storm problem in a mobile ad hoc network. Wireless Networks, 2002, vol. 8, no. 2/3, p. 153–167.
  8. KOMALI, R. S, THOMAS, R. W, DASILVA, L. A, MACKENZIE, A. B. The price of ignorance-distributed topology control in cognitive networks. IEEE Transactions on Wireless Communications, April 2010, vol. 9, no. 4, p. 1434-1445.
  9. HAYKIN, S. M. Fundamental issues in cognitive radio. In B. Bhargava, E. Hussain (ed.) Cognitive Radio Networks. Springer- Verlag, 2007.
  10. YU, J. Y., CHONG, P. H. J. A survey of clustering scheme for mobile ad hoc networks. IEEE Communications Surveys & Tutorials. First quarter 2005, vol. 7, no. 1, p. 32-48.
  11. LAZOS, L., LIU, S., KRUNZ, M. Spectrum opportunity-based control channel assignment in cognitive radio networks. In Proc. of the 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks SECON2009. Rome (Italy), June, 2009, p.1-9.
  12. CESANA, M., CUOMO, F., EKICI, E. Routing in cognitive radio networks: Challenges and solutions. Ad Hoc Networks, 2011, vol. 9, no. 3, p. 228-248.
  13. KOK-LIM ALVIN YAU, KOMISARCZUK, P., TEAL, P. D. Context-awareness and intelligence in distributed cognitive radio networks: a reinforcement learning approach. In Proc. of 11th IEEE Australian Communications Theory Workshop (AusCTW'10). Canberra (Australia), February 2010, p. 1-5.
  14. MUECK, M., HAYAR, A. A local cognitive pilot channel (LCPC) for neighborhood discovery, relaying and cluster based local cognitive information management. In Proc. of the 5th International Conference on Cognitive Radio Oriented Wireless Networks & Communications (CROWNCOM), June 2010, p. 1-5.
  15. CHOWDHURY, K. R., AKYILDIZ, I. F. OFDM based common control channel design for cognitive radio ad hoc networks. IEEE Transactions on Mobile Computing, Feb. 2011, vol. 10, no. 2, p. 228-238.
  16. XIUKUI LI, ZEKAVAT, S. A. Automatic construction of cognitive radio networks. In Proc. of IEEE Wireless Communications and Networking Conference 2008. March/April, 2008, p. 870-875.
  17. KONDAREDDY, Y. R., AGRAWAL, P., SIVALINGAM, K. Cognitive radio network setup without a common control channel. In Proc. of IEEE Milcom2008, p. 1-6, November, 2008.
  18. HAITAO ZHENG, GUANG-HUA YANG Distributed coordination in dynamic spectrum allocation networks. In Proc. of IEEE International Symposium DySPAN2005. Baltimore (MD, USA), 8~11, November, 2005, p. 259-268.
  19. YU, J. Y., CHONG, P. H. J. 3hBAC (3-hop between adjacent cluster heads): a novel non-overlapping clustering algorithm for mobile ad hoc networks. In Proc. of the IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (Pacrim’03). Victoria (B.C., Canada), Aug. 2003, vol. 1, p. 318–21.
  20. FREY, B., DUECK, D. Clustering by passing messages between data points. Science, February 2007, vol. 315, p. 972-976.
  21. LEONE, M., SUMEDHA, M. WEIGT, M. Clustering by softconstraint affinity propagation: Applications to gene-expression data. Bioinformatics, 2007, vol. 23, no. 20, p. 2708-2715.
  22. CHEN, T., ZHANG, H., MAGGIO, G. M., CHLAMTAC, I. CogMesh: a cluster-based cognitive radio network. In Proc. of IEEE International Symposium DySPAN2007. Dublin (Ireland), April 2007, p. 168-178.
  23. CHEN, T., ZHANG, H., MAGGIO, G. M., CHLAMTAC, I. Topology management in CogMesh: a cluster-based cognitive radio mesh network. In Proc. of the 2007 IEEE International Conference on Communications. Glasgow (Scotland, UK), June 2007, p. 6516-6521.
  24. LEI GONG, JIE CHEN, WANBIN TANG, SHAOQIAN LI Application of clustering structure in the hierarchical spectrum sharing network based on cognitive radio. In Proc. of the 3rd Internat. Conf. on Cognitive Radio Oriented Wireless Networks & Communications (CROWNCOM). Singapore, May 2008, p. 1-5.
  25. ASTERJADHI, A., BALDO, N., ZORZI, M. A cluster formation protocol for cognitive radio ad hoc networks. In Proc. of the European Wireless Conference (EW 2010). Lucca (Italy), April 2010, p. 955 – 961.
  26. JIANZHAO ZHANG, FUQIANG YAO, HANGSHENG ZHAO, FAN WANG Cluster-based dynamic topology management in cognitive radio ad hoc networks. Frequenz, May, 2011, vol. 65, no. 3/4, p. 109-119.
  27. SHEA, C., HASSANABADI, B., VALAEE, S. Mobility-based clustering in VANETs using affinity propagation. In Proc. of IEEE Global Telecommunications Conference 2009. Honolulu (Hawaii), Nov.30-Dec.4, 2009, p.1-6.
  28. BADDOUR, K. E., URETEN, O., WILLINK, T. J. Efficient clustering of cognitive radio networks using affinity propagation. In Proc. of the 4th International Conference on Cognitive Radio Oriented Wireless Networks & Communications (CROWNCOM). Hannover (Germany), Aug 2009, p. 1-6.
  29. KARIV, O., HAKIMI, S. L. An algorithmic approach to network location problems. II: The p-medians. SIAM Journal on Applied Mathematics, Dec. 1979, vol. 37, no. 3, p. 539–560.

Keywords: Cognitive radio ad hoc networks, clustering, soft-constraint affinity propagation, robustness

Z. Fan, D. Guo, B. Zhang [references] [full-text] [Download Citations]
Outage Probability and Power Allocation for Two-Way DF Relay Networks with Relay Selection

In this paper, we investigate the outage probability and power allocation for the two-way decode-and-forward (DF) relay networks with relay selection.~Specially, we consider independent but not necessarily identical distributed Rayleigh fading channels. Firstly, we derive an exact closed form outage probability expression. To shed light on the relation between the outage probability and the power allocation factor, an upper bound for the outage probability is derived, too. We then propose a power allocation scheme in the sense of minimizing this upper bound. Monte Carlo simulations are conducted to show that the derived outage probability expression excellently matches simulation results, and our proposed power allocation scheme performs effectively.

  1. SENDONARIS, A., ERKIP E., AAZHANG B. User cooperation diversity-part I: system description. IEEE Transactions on Communications, 2003, vol. 51, no. 11, p. 1927 - 1938.
  2. LANEMAN, J. N., TSE, D. N. C., WORNELL, G. W. Cooperative diversity in wireless networks: efficient protocols and outage behavior. IEEE Transactions on Information Theory, 2004, vol. 50, no. 12, p. 3062 - 3080.
  3. LUO, J., BLUM, R. S., CIMINI, L. J., GREENSTEIN, L. J., HAIMOVICH, A. M. Decode-and-forward cooperative diversity with power allocation in wireless networks. IEEE Transactions on Wireless Communications, 2007, vol. 6, no. 3, p. 793 - 799.
  4. BLETSAS, A., KHISTI, A., WIN, M. Z. Opportunistic cooperative diversity with feedback and cheap radios. IEEE Transactions on Wireless Communications, 2008, vol. 7, no. 5, p. 1823 - 1827.
  5. XU, K., GAO, Y., YI, X., PAN, Y., ZHANG, Y., SU, S. Opportunistic relaying in time division broadcast protocol with incremental relaying. Radioengineering, 2012, vol. 21, no. 1, p. 115 - 125.
  6. RANKOV, B., WITTNEBEN, A. Spectral efficient protocols for half-duplex fading relay channels. IEEE Journal on Selected Areas in Communications, 2007, vol. 25, no. 2, p. 379 - 389.
  7. KIM, S. J., DEVROYE, N., MITRAN, P., TAROKH V. Achievable rate regions and performance comparison of half duplex bidirectional relaying protocols. IEEE Transactions on Information Theory, 2011, vol. 57, no. 10, p. 6405 - 6418.
  8. LI, Q., TING, S. H., PANDHARIPANDE, A., HAN, Y. Adaptive two-way relaying and outage analysis. IEEE Transactions on Wireless Communications, 2009, vol. 8, no. 6, p. 3288 - 3299.
  9. JU, M., KIM, I. M. Error performance analysis of BPSK modulation in physical-layer network-coded bidirectional relay networks. IEEE Transactions on Communications, 2010, vol. 58, no. 10, p. 2770 - 2775.
  10. CUI, T., GAO, F., HO, T., NALLANATHAN, A. Distributed spacetime coding for two-way wireless relay networks. IEEE Transactions on Signal Processing, 2009, vol. 57, no. 2, p. 658 - 671.
  11. ZHOU, Q. F., LI, Y., LAU F. C. M., VUCETIC, B. Decode-andforward two-way relaying with network coding and opportunistic relay selection. IEEE Transactions on Communications, 2010, vol. 58, no. 11, p. 3070 - 3076.
  12. KRIKIDIS, I. Relay selection for two-way relay channels with MABC DF: a diversity perspective. IEEE Transactions on Vehicular Technology, 2010, vol. 59, no. 9, p. 4620 - 4628.
  13. SONG, L. Relay selection for two-way relaying with amplify-andforward protocols. IEEE Transactions on Vehicular Technology, 2011, vol. 60, no. 4, p. 1954 - 1959.
  14. ZHANG, Y., TAFAZOLLI, R. Power allocation for bidirectional AF relaying over Rayleigh fading channels. IEEE Communications Letters, 2010, vol. 14, no. 2, p. 145 - 147.
  15. PISCHELLA, M., RUYET, D. L. Optimal power allocation for twoway relay channel with data rate fairness. IEEE Communications Letters, 2011, vol. 15, no. 9, p. 959 - 961.
  16. DAVID, H. A. Order Statistics. Hoboken (NJ, USA): Wiley, 1970.

Keywords: Two-way relay networks, relay selection, decode-and-forward, outage probability, power allocation

Y. B. Li, R. Yang, Y. Lin, F. Ye [references] [full-text] [Download Citations]
The Spectrum Sharing in Cognitive Radio Networks Based on Competitive Price Game

The competitive price game model is used to analyze the spectrum sharing problem in the cognitive radio networks, and the spectrum sharing problem with the constraints of available spectrum resource from primary users is further discussed in this paper. The Rockafeller multiplier method is applied to deal with the constraints of available licensed spectrum resource, and the improved profits function is achieved, which can be used to measure the impact of shared spectrum price strategies on the system profit. However, in the competitive spectrum sharing problem of practical cognitive radio network, primary users have to determine price of the shared spectrum without the acknowledgement of the other primary user’s price strategies. Thus a fast gradient iterative calculation method of equilibrium price is proposed, only with acknowledgement of the price strategies of shared spectrum during last cycle. Through the adaptive iteration at the direction with largest gradient of improved profit function, the equilibrium price strategies can be achieved rapidly. It can also avoid the predefinition of adjustment factor according to the parameters of communication system in conventional linear iteration method. Simulation results show that the proposed competitive price spectrum sharing model can be applied in the cognitive radio networks with constraints of available licensed spectrum, and it has better convergence performance.

  1. HAYKIN, S. Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 2005, vol. 23, no. 2, p. 201 - 220.
  2. AKYILDIZ, I. F., LEE, W. Y., VURAN, M. C., MOHANTY, S. A survey on spectrum management in cognitive radio networks. IEEE Communications Magazine, 2008, vol. 46, no. 4, p. 40 - 48.
  3. FETTE, B. A. Cognitive Radio Technology. Newnes, USA, 2006.
  4. JI, Z., LIU, K.J. R. Cognitive radios for dynamic spectrum access - Dynamic spectrum sharing: A game theoretical overview. IEEE Communications Magazine, 2007, vol. 45, no. 5, p. 88 - 94.
  5. NIYATO, D., HOSSAIN, E. Competitive pricing for spectrum sharing in cognitive radio networks: Dynamic game, inefficiency of Nash equilibrium, and collusion. IEEE Journal on Selected Areas in Communications, 2008, vol. 6, no. 1, p. 192-202.
  6. NIYATO, D., HOSSAIN, E. Optimal price competition for spectrum sharing in cognitive radio: A dynamic game-theoretic approach. In Proc. of the 50th IEEE Global Telecommunications Conference. Washington (USA), 2007, p. 4625-4629.
  7. HONG, H., NIU, K., HE, Z. A game theoretic analysis of pricing for spectrum sharing in cognitive radio networks. In Proceedings of the 1st IEEE International Conference on Communications Technology and Applications. Beijing (China), 2009, p. 467-471.
  8. TAN, X., LIU, Y., WEI, S. Game-based spectrum allocation in cognitive radio networks. Journal of South China University of Technology (Natural Science), 2010, vol. 38, no. 5, p. 22-26. (in Chinese)
  9. LI, Y., YANG, R., YE, F. Price game based spectrum sharing in cognitive radio networks. Advanced Materials Research, 2011, vol. 225-226, p. 632-636.
  10. CHUA, S., GOLDSMITH, A. Variable-rate variable-power MQAM for fading channels. In Proc. of the 46th IEEE Vehicular Technology Conference. Atlanta (USA), 1996, p. 815-819.

Keywords: Cognitive radio, spectrum sharing, game theory, competitive price model

Z. Zhang, Q. Wu, J. Wang [references] [full-text] [Download Citations]
Energy-efficient Power Allocation Strategy in Cognitive Relay Networks

Cognitive radio and cooperative technique are two essential techniques for the future generation green communication paradigm owing to its inherent advantages of adaptability and cognition. Typically, previous studies on power allocation in the cognitive relay networks often concentrate on two goals independently: the first goal is to minimize the transmit power to reduce energy consumption, as depicted in strategy 1; the second goal is to maximize the transmit rate, as depicted in strategy 2. In this paper, we shift our focus to energy-efficient-oriented design, that is, green power allocation between source and relay. Therefore, we present a novel power allocation strategy considering the two goals jointly, as depicted in strategy 3, and compare the proposed strategy with two previous strategies. Specifically, because the strategy 3 is nonlinear, we use the Lagrange dual method to solve it effectively. Finally, the numerical results are presented to validate our theoretical results through theory simulation and Monte Carlo simulation. Numerical performance results show that the proposed strategy works better than that of the two previous strategies from the viewpoints of energy-efficient.

  1. Federal Communication Commission (FCC). ET Docket No 03-322: Notice of Proposed Rule Making and Order in the Matter of Facilitating Opportunities for Flexible, Efficient, and Reliable Spectrum Use Employing Cognitive Radio Technologies. Washington DC (USA), 2003.
  2. MITOLA, J. III, MAGUIRE, G. Q. Jr. Cognitive radio: making software radios more personal. IEEE Personal Communication Magazine, 1999, vol. 6, no. 4, p. 13 - 18.
  3. MITOLA, J. Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio. Ph.D. dissertation. Stockholm (Sweden): Royal Institute Of Technology (KTH), 2000.
  4. AKBULUT, A., ADIGUZEL, T., YILMAZ, A. E. Estimation of time-varying channel state transition probabilities for cognitive radio systems by means of particle swarm optimization. Radioengineering, 2012, vol. 21, no. 1, p. 104 - 109.
  5. QIHUI WU, HAN HAN, JINLONG WANG, ZHITAO ZHAO, ZE ZHANG Sensing task allocation for heterogeneous channels in cooperative spectrum sensing. Radioengineering, 2010, vol. 19, no. 4, p. 544 - 551.
  6. FERDOUS, N., AHMED, M., MATIN, M. A., HABIBA, U. Efficient algorithm for power allocation in relay-based cognitive radio network. Radioengineering, 2011, vol. 20, no. 4, p. 946 - 951.
  7. ZHANG, H., WANG, X., KUO, G. S., BOHNERT, T. M. Optimum detection location-based cooperative spectrum sensing in cognitive radio. Radioengineering, 2010, vol. 19, no. 4, p. 552 - 560.
  8. HAYKIN, S. Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications, 2005, vol. 23, no. 2, p. 201 - 220.
  9. ZHAO, Q., SADLER, B. M. A survey of dynamic spectrum access. IEEE Signal Processing Magazine, 2007, vol. 24, no. 3, p. 79 - 89.
  10. HAYKIN, S., REED, J. H., LI, G. Y., SHAFI, M. Scanning the issue. Proceedings of IEEE, 2009, vol. 97, no.4, p. 608 - 611.
  11. AKYILDIZ, I. A., LEE, W. Y., VURAN, M. C., MOHANTY, S. NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey. Computer Networks, 2006, vol. 50, no. 13, p. 2127 - 2159.
  12. ZHANG, Q., JIA, J., ZHANG, J, Cooperative relay to improve diversity in cognitive radio networks. IEEE Communications Magazine, 2009, vol. 47, no. 2, p. 111 - 117.
  13. JIA, J., ZHANG, J., ZHANG, Q. Cooperative relay for cognitive radio networks. In The 28th Conference on Computer Communications, IEEE INFOCOM 2009. Rio de Janeiro (Brazil), 2009, p. 2304 - 2312.
  14. ZONGSHENG, ZHANG., JINLONG, WANG., QIHUI, WU. A novel channel selection strategy based on outage probability in cognitive relay network. Under review.
  15. HOU, Y. T., SHI, Y., EPHREMIDES, A. Spectrum sharing for multihop networking with cognitive radios. IEEE Journal on Selected Areas in Communications, 2008, vol. 26, no. 1, p. 146 - 155.
  16. SADEK, A. K., LIU, K. J. R., EPHREMIDES, A. Cognitive multiple access via cooperation: protocol design and performance analysis. IEEE Transactions on Information Theory, 2007, vol. 53, no. 10, p. 3677 - 3696.
  17. YULONG, ZOU, JIA ZHU, BAOYU ZHENG, YU-DONG YAO. An adaptive cooperation diversity scheme with best-relay selection in cognitive networks. IEEE Transactions on Signal Processing, 2010, vol. 58, no. 10, p. 5438 - 5445.
  18. MUSAVIAN, L., AISSA. S. Cross-layer analysis of cognitive radio relay networks under quality of service constrains. In IEEE 69th Vehicular Technology Conference, VTC Spring 2009. Barcelona (Spain), 2009.
  19. MIN XIE, WEI ZHANG, KAI-KIT WONG. A geometric approach to improve spectrum efficiency for cognitive relay networks. IEEE Transactions onWireless Communications, 2010, vol. 9, no. 1, p. 268 - 281.
  20. DONG LI, XIANUA DAI Power control in cooperative cognitive radio networks by geometric programming. In 15th Asia-Pacific Conference on Communications, APCC 2009. Shanghai (China), 2009, p. 118 - 121.

Keywords: Cognitive relay networks (CRN); energy-efficient (EE); secondary user (SU); primary user (PU)

H. Xiao, H. Shao, K. Yang, F. Yang, W. Wang [references] [full-text] [Download Citations]
Multiple Timescale Energy Scheduling for Wireless Communication with Energy Harvesting Devices

The primary challenge in wireless communication with energy harvesting devices is to efficiently utilize the harvesting energy such that the data packet transmission could be supported. This challenge stems from not only QoS requirement imposed by the wireless communication application, but also the energy harvesting dynamics and the limited battery capacity. Traditional solar predictable energy harvesting models are perturbed by prediction errors, which could deteriorate the energy management algorithms based on this models. To cope with these issues, we first propose in this paper a non-homogenous Markov chain model based on experimental data, which can accurately describe the solar energy harvesting process in contrast to traditional predictable energy models. Due to different timescale between the energy harvesting process and the wireless data transmission process, we propose a general framework of multiple timescale Markov decision process (MMDP) model to formulate the joint energy scheduling and transmission control problem under different timescales. We then derive the optimal control policies via a joint dynamic programming and value iteration approach. Extensive simulations are carried out to study the performances of the proposed schemes.

  1. SURIYACHAI, U., SCOTT, A. A survey of mac protocols for mission-critical applications in wireless sensor networks. IEEE Commun. Surveys and Tutorials, 2011, vol. PP, no. 99, p. 1-25.
  2. SZYMANSKI, T., GILBERT, D. Provisioning mission-critical telerobotic control systems over internet backbone networks with essentially-perfect QoS. IEEE J. Select. Areas Commun., 2010, vol. 28, no. 5, p. 630-643.
  3. SHIANG, H., VAN-DER-SCHAAR, M. Online learning in autonomic multi-hop wireless networks for transmitting missioncritical applications. IEEE J. Select. Areas Commun., 2010, vol. 28, no. 5, p. 728-741.
  4. DHAINI, A., HO, P. Mc-fiwiban: an emergency-aware missioncritical fiber-wireless broadband access network. IEEE Commun. Magazine, 2011, vol. 49, no. 1, p. 134-142.
  5. OKORAFOR, U., KUNDUR, D. Security-aware routing and localization for a directional mission critical network. IEEE J. Select. Areas Commun., 2010, vol. 28, no. 5, p. 664-676.
  6. NIYATO, M., HOSSAIN, E., BHARGAVA, V. Wireless sensor networks with energy harvesting technologies: a game-theoretic approach to optimal energy management. IEEE Tran. Wireless Commun., 2007, vol. 14, no. 4, p. 90-96.
  7. SHARMA, V., MUKHERJI, U., JOSEPH, V., GUPTA, S. Optimal energy management policies for energy harvesting sensor nodes. IEEE Trans. Wireless Comm., 2010, vol. 6, no. 4, p. 1326-1336.
  8. TUTUNCUOGLU, K., YENER, A. Optimal power control for energy harvesting transmitters in an interference channel. In Proc. of ASILOMAR. CA(USA), 2011, p.378-382.
  9. TUTUNCUOGLU, K., YENER, A. Optimum transmission policies for battery limited energy harvesting nodes. IEEE Trans. Wireless Comm., 2012, vol. 11, no. 3, p. 1180-1189.
  10. YANG, J., ULUKUS, S. Optimal packet scheduling in an energy harvesting communication system. IEEE Trans. Comm., 2012, vol. 60, no. 1, p. 220-230.
  11. OZEL, O, YANG, J., ULUKUS, S. Optimal broadcast scheduling for an energy harvesting rechargeable transmitter with a finite capacity battery. IEEE Trans. Wireless Comm., to be appeared.
  12. OZEL, O., TUTUNCUOGLU, K., YANG, J., ULUKUS, S., YENER, A. Resource management for fading wireless channels with energy harvesting nodes In Proc. IEEE INFOCOM' 11. Shanghai (China), 2011.
  13. GORLATOVA, A., ZUSSMAN, G. Networking ultra low power energy harvesting devices: Measurements and algorithms. In Proc. IEEE INFOCOM' 11. Shanghai (China), 2011.
  14. KANSAL, A., HSU, J., ZAHEDI, S., SRIVASTAVA, M. Power management in energy harvesting sensor networks. ACM Trans. Embed. Comput. Syst., 2007, vol. 6.
  15. REDDY, S., MURTHY, C. Profile-based load scheduling in wireless energy harvesting sensors for data rate maximization. In Proc. of IEEE ICC 2010. Cape Town (South Africa), 2010, p. 1-5.
  16. SHENOY, V., MURTHY, C. Throughput maximization of delayconstrained traffic in wireless energy harvesting sensors. In Proc. of IEEE ICC 2010. Cape Town (South Africa), 2010, p. 1-5.
  17. CHANG, S., FARD, P. Multitime scale Markov decision processes. IEEE Trans. Automatic Control, 2003, vol. 48, no. 6, p. 976-987.
  18. HUGHES, J., GUTTORP, P., CHARLES, S. A non-homogeneous hidden Markov model for precipitation occurrence. Journal of the Royal Statistical Society: Series C, 1999, vol. 48, no. 1, p. 15-30.
  19. LAMBERT, M., WHITING, J., METCALFE, A. A non-parametric hidden Markov model for climate state identification. Hydrology and Earth System Sciences, 2003, vol. 7, no. 5, p. 652-667.
  20. BELLONE, E., HUGHES, J., GUTTORP, P. A hidden Markov model for downscaling synoptic atmospheric patterns to precipitation amounts. Climate Research, 2000, vol. 15, no. 1, p. 1-12.
  21. ZHANG, Q., KASSAM, S. Finite-state Markov model for Rayleigh fading channels. IEEE Trans. Commun., 1999, vol. 47, no. 11, p. 1688-1692.
  22. PUTERMAN, M. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, 1994.
  23. BERTSEKAS, D. Dynamic Programming and Optimal Control. Athena Scientific, 2007.

Keywords: Energy scheduling, energy harvesting, multiple timescale Markov decision process, transmission control, wireless communication

Y. Liu, Z. Tan [references] [full-text] [Download Citations]
Carrier Frequency Offset Estimation for OFDM Systems using Repetitive Patterns

This paper deals with Carrier Frequency Offset (CFO) estimation for OFDM systems using repetitive patterns in the training symbol. A theoretical comparison based on Cramer Rao Bounds (CRB) for two kinds of CFO estimation methods has been presented in this paper. Through the comparison, it is shown that the performance of CFO estimation can be improved by exploiting the repetition property and the exact training symbol rather than exploiting the repetition property only. The selection of Q (number of repetition patterns) is discussed for both situations as well. Moreover, for exploiting the repetition and the exact training symbol, a new numerical procedure for the Maximum-Likelihood (ML) estimation is designed in this paper to save computational complexity. Analysis and numerical result are also given, demonstrating the conclusions in this paper.

  1. BINGHAM, J. A. C. Multicarrier modulation for data transmission: An idea whose time has come. IEEE Communications Magazine, 1990, vol. 28, no. 5, p. 5-14.
  2. MAY, T., ROHLING, H., ENGELS, V. Performance analysis of Viterbi decoding for 64-DAPSK and 64-QAM modulated signal. IEEE Transactions on Communication, 1998, vol. 46, no. 2, p. 182 - 190.
  3. REIMERS, U. Digital video broadcasting. IEEE Communications Magazine, 1998, vol. 36, no. 6, p. 104 - 110.
  4. Local and Metropolitan Area Networks-Part 16, Air Interface for Fixed Broadband Wireless Access Systems. IEEE Standard IEEE 802.16e.
  5. SCHMIDL, T. M., COX, D. C. Robust frequency and timing synchronization for OFDM. IEEE Transactions on Communications, 1997, vol. 45, no. 12, p. 1613 - 1621.
  6. MORELLI, M., MENGALI, U. An improved frequency oset estimator for OFDM applications. IEEE Communications Letters, 1999, vol. 3, no. 3, p. 75 - 77.
  7. MINN, H., BHARGAVA, V. K., LETAIEF, K. B. A robust timing and frequency synchronization for OFDM systems. IEEE Transactions on Wireless Communications, 2003, vol. 2, no. 4, p. 822 - 839.
  8. CHOI, J. W., LEE, J. Joint ML estimation of frame timing and carrier frequency oset for OFDM systems employing time-domain repeated preamble. IEEE Transactions on Wireless Communications, 2010, vol. 9, no. 1, p. 311 - 317.
  9. CHENG, M., CHOU, C. Maximum-likelihood estimation of frequency and time osets in OFDM systems with multiple sets of identical data. IEEE Transactions on Signal Processing, 2006, vol. 54, no. 7, p. 2848 - 2852.
  10. MINN, H., FU, X., BHARGAVA, V. K. Optimal periodic training signal for frequency oset estimation in frequency-selective fading channels. IEEE Transactions on Communications, 2006, vol. 54, no. 6, p. 1081 - 1096.
  11. MORELLI, M., MENGALI, U. Carrier-frequency estimation for transmissions over selective channels. IEEE Transactions on Communications, 2000, vol. 48, no. 9, p. 1580 - 1589.
  12. KAY, S. M. Fundamentals of Statistical Signal Processing: Estimation Theory. Englewood Clis (NJ, USA): Prentice Hall, 1993.
  13. TELLAMBURA, C., PARKER, M. G., GUO, Y. J., SHEPHERD, S. J., BARTON, S. K. Optimal sequencws for channel estimation using discrete Fourier transform techniques. IEEE Transactions on Communications, 1999, vol. 47, no. 2, p. 230 - 238.
  14. MOW, W. H., LI, S. Y. R. Aperiodic autocorrelation properties of perfect polyphase sequences. In Singapore ICCS/ISlTA ’92. Singapore, 1992, p. 1232 - 1234.
  15. MEYRS, M. H., FRANKS, L. E. Joint carrier phase and symbol timing recovery for PAM systems. IEEE Transactions on Communications, 1980, vol. 28, no. 8, p.1121 - 1129.
  16. HAYKIN, S. Adaptive Filter Theory. Fourth Edition. Upper Saddle River (NJ, USA): Prentice Hall, 2001.

Keywords: OFDM, CFO, repetitive patterns

B. Nikolic, B. Dimitrijevic, N. Milosevic, G.T. Djordjevic [references] [full-text] [Download Citations]
Performance Improvement of QPSK Signal Predetection EGC Diversity Receiver

This paper proposes a modification of quadrature phase-shift-keying (QPSK) signal diversity reception with predetection equal gain combiner (EGC). The EGC combining is realized by using the constant modulus algorithm (CMA). Carrier synchronization is performed by the phase locked loop (PLL). Comparative analysis of the modified and ordinary diversity receiver in the presence of carrier frequency offset in the additive white Gaussian noise (AWGN) channel, as well as in Rician fading channel is shown. The proposed diversity receiver allows significant frequency offset compared to the diversity receiver that uses only PLL, and the error probability of the proposed receiver is very close to the error probability of the receiver with only PLL and zero frequency offset. The functionality of the proposed diversity receiver, as well as its properties is experimentally verified on a system based on universal software radio peripheral (USRP) hardware. The performed comparison confirms the expected behavior of the system.

  1. SIMON, M. K., ALOUINI, M. S. Digital Communication over Fading Channels: A Unified Approach to Performance Analysis. New York: Wiley, 2000.
  2. PROAKIS, J. G. Digital Communications. New York: McGraw- Hill, 2000.
  3. KWOK, Y. K. R., LAU, V. K. N. Diversity techniques. Wireless Internet and Mobile Computing: Interoperability and Performance, 2007, DOI: 10.1002/9780470167960.ch4
  4. PATTERH, M. S., KAMAL, T. S., SOHI, B. S. BER performance of MQAM with L-branch MRC diversity reception over correlated Nakagami-m fading channels. Wireless Communications and Mobile Computing, 2003, vol. 3, no. 3, p. 397–406.
  5. ANNAMALAI, A., TELLAMBURA, C., BHARGAVA, V. K. Equal-gain diversity receiver performance in wireless channels. IEEE Transactions on Communications, 2000, vol. 48, no. 10, p. 1732–1745.
  6. NAJIB, M. A., PRABHU, V. K. Analysis of equal-gain diversity with partially coherent fading signals. IEEE Transactions on Vehicular Technology, 2000, vol. 49, no. 3, p. 783–791.
  7. SAGIAS, N. C., KARAGIANNIDIS, G. K., Effects of carrier phase error on EGC receivers in correlated Nakagami-m fading. IEEE Communications Letters, 2005, vol. 9, no. 7, p. 580–582.
  8. NIKOLIC, B. Z., DJORDJEVIC, G. T., KARAGIANNIDIS, G. K. On the effect of imperfect cophasing in MRC and EGC receivers over correlated Weibull fading. Wireless Personal Communications, 2012, vol. 62, no. 1, p. 31–39.
  9. GODARD, D. Self-recovering equalization and carrier tracking in two-dimensional data communication systems. IEEE Transactions on Communications, 1980, vol. 28, no. 11, p. 1867–1875.
  10. GOOCH, R., LUNDELL, J. The CM array: an adaptive beamformer for constant modulus signals. In Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing. Tokyo (Japan), 1986, p. 2523–2526.
  11. DJIGAN, V. I. Joint use of constant modulus and least squares criteria in linearly-constrained communication arrays. Radioengineering, 2007, vol. 16, no. 4, p. 88–95.
  12. GODARA, L. C. Application of antenna arrays to mobile communications. Part II: Beam-forming and direction-of-arrival considerations. Proceedings of the IEEE, 1997, vol. 85, no. 8, p. 1195–1245.
  13. JOHNSON, C. R., SCHNITER, P., ENDRES, T. J., BEHM, J. D., BROWN, D. R., CASAS, R. A. Blind equalization using the constant modulus criterion: A review. Proceedings of the IEEE, 1998, vol. 86, no. 10, p. 1927–1950.
  14. CHEN, S., WOLFGANG A, HANZO L, Constant modulus algorithm aided soft decision directed scheme for blind space-time equalization of SIMO channels. In Proc. IEEE 60th Vehicular Technology Conference. Los Angeles (CA, USA), 2004, p. 1718 to 1722.
  15. AGEE, B. G. The least-squares CMA: A new technique for rapid correction of constant modulus signals. In Proc. IEEE International Conference on ICASSP '86 Acoustics, Speech, and Signal Processing. Tokyo (Japan), 1986, p. 953–956.
  16. BIEDKA, T. E., TRANTER, W. H., REED, J. H. Convergence analysis of the least squares constant modulus algorithm in interference cancellation applications. IEEE Transactions on Communications, 2000, vol. 48, no. 3, p. 491–501.
  17. CHEN, Y., LE-NGOC, T., CHAMPAGNE, B., CHANGJIANG, X. Recursive least squares constant modulus algorithm for blind adaptive array. IEEE Transactions on Signal Processing, 2004, vol. 52, no. 5, p. 1452–1456.
  18. DE LAMARE, R. C., SAMPAIO-NETO, R. Blind adaptive codeconstrained constant modulus algorithms for CDMA interference suppression in multipath channels. IEEE Communications Letters, 2005, vol. 9, no. 4, p. 334–336.
  19. DE LAMARE, R. C., HAARDT, M., SAMPAIO-NETO, R. Blind adaptive constrained reduced-rank parameter estimation based on constant modulus design for CDMA interference suppression. IEEE Transactions on Signal Processing, 2008, vol. 52, no. 6, p. 2470–2482.
  20. DE LAMARE, R. C., SAMPAIO-NETO, R. Low-complexity variable step-size mechanisms for stochastic gradient algorithms in minimum variance CDMA receivers. IEEE Transactions on Signal Processing, 2006, vol. 54, no. 6, p. 2302–2317.
  21. WANG, L., CAI, Y., DE LAMARE, R. C. Low-complexity adaptive step size constrained constant modulus SG-based algorithms for blind adaptive beamforming. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing. Las Vegas (NV, USA), 2008, p. 2593–2596.
  22. CAI, Y., DE LAMARE, R. C. Low-complexity variable step-size mechanism for code-constrained constant modulus stochastic gradient algorithms applied to CDMA interference suppression. IEEE Transactions on Signal Processing, 2009, vol. 57, no. 1, p. 313–323.
  23. DEMIR, M. A., OZEN, A. A novel variable step size adjustment method based on autocorrelation of error signal for the constant modulus blind equalization algorithm. Radioengineering, 2012, vol. 21, no. 1, p. 37–45.
  24. SETHARES, W., LAWRENCE, D., JOHNSON, C. JR., BITMEAD, R. Parameter drift in LMS adaptive filters. IEEE Transactions on Acoustics, Speech and Signal Processing, 1986, vol. 34, no. 4, p. 868–879.
  25. GARDNER, F. M. Phase Lock Techniques. New York: Wiley, 1979.

Keywords: Equal gain combiner, constant modulus algorithm, phase locked loop, adaptive filtering

M. Modarresi, S. M.-S. Sadough [references] [full-text] [Download Citations]
Improved Design and Implementation of Variational Bayesian Iterative Receivers

It was recently shown that detection performance can be significantly improved if the statistics of channel estimation errors are available and properly used at the receiver. Although deriving the statistics of channel estimation errors is rather straightforward for pilot-only channel estimation methods, it is not the case for semi-blind receivers such as variational Bayesian (VB) receivers. We have shown in a recent contribution that by a modified formulation of the VB formalism, one can reduce the impact of channel uncertainty on the decoder performance. In this paper, we propose different practical VB receiver implementation techniques that lead to further performance improvement. The adequacy of the proposed receiver design compared to classically-used VB receivers is demonstrated by simulations for orthogonal frequency-division multiplexing (OFDM) systems.

  1. CAVERS, J. K. An analysis of pilot symbol assisted modulation for Rayleigh fading channels. IEEE Transactions on Vehicular Technology, 1991, vol. 40, no. 4, p. 686 – 693.
  2. CIRPAN, H. A., PANAYIRCI, E., DOGAN, H. Non-data-aided channel estimation for OFDM systems with space-frequency transmit diversity. IEEE Transactions on Vehicular Technology, 2006, vol. 55, no. 2, p. 449 – 457.
  3. CHRISTENSEN, L. P. B., LARSEN, J. On data and parameter estimation using the variational Bayesian EM-algorithm for blockfading frequency-selective MIMO channels. In Proceedings of IEEE international conference on Acoustics, Speech and Signal Processing, ICASSP 2006. Toulouse (France), 2006.
  4. LI, F., ZHU, S., RONG, M. Detection of OFDM systems with channel estimation errors using variational inference. IEEE Signal Processing Letters, 2009, vol. 16, no. 5, p. 434 - 437.
  5. STEFANATOS, S., KATSAGGELOS, A. K. Joint data detection and channel tracking for OFDM systems with phase noise. IEEE Transactions on Signal Processing, 2008, vol. 56, no. 9, p. 4230 - 4243.
  6. LIN, D. D., LIM, T. J. The variational inference approach to joint data detection and phase noise estimation in OFDM. IEEE Transactions on Signal Processing, 2007, vol. 55, no. 5, p. 1862 - 1874.
  7. SADOUGH, S. M. S., DUHAMEL, P. Improved iterative detection and achieved throughputs of OFDM systems under imperfect channel estimation. IEEE Transactions on Wireless Communications, 2008, vol. 7, no. 12, p. 5039 - 5050.
  8. SADOUGH, S. M. S., KHALIGHI, M. A., DUHAMEL, P. Improved iterative MIMO signal detection accounting for channel-estimation errors. IEEE Transactions on Vehicular Technology, 2009, vol. 58, no. 7, p. 3154 - 3167.
  9. SADOUGH, S. M. S., KHALIGHI, M. A. Optimal turbo-BLAST detection of MIMO-OFDM systems with imperfect channel estimation. 2007, in IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2007. Athens (Greece), 2007, p. 1 - 6.
  10. SADOUGH, S. M. S., MODARRESI, M. New method for increasing the accuracy of EM-based channel estimation. Radioengineering, 2011, vol. 20, no. 4, p. 968 - 975.
  11. SADOUGH, S. M. S., MODARRESI, M. Improved iterative Joint detection and estimation through variational bayesian inference. International Journal of Electronics and Communications - AE¨U, 2012, vol. 66, no. 5, p. 380 - 383.
  12. BEAL, M. J. Variational Algorithms for Approximate Bayesian Inference. PhD thesis. London (UK): University College London, 2003.
  13. MAGNIEZ, P., MUQUET, B., DUHAMEL, P., BUZENAC, V., DECOURVILLE, M. Optimal decoding of bit-Interleaved modulations: Theoritical aspects and practical algorithms. In Proceedings of International Symposium on Turbo Codes and Related Topics. Brest (France), 2003, p. 169 - 172.
  14. BAHL, L., COCKE, J., JELINEK, F., RAVIV, J. Optimal decoding of linear codes for minimizing symbol error rate. IEEE Transactions on Information Theory, 1974, vol. 20, no. 2, p. 284 – 287.
  15. ZHUANG, X., VOOK, F.W. Iterative channel estimation and decoding for a turbo-coded OFDM system via the EM algorithm. In Proceedings of IEEE Internarional Conference on Acoustics, Speech and Signal Processing, ICASSP 2002. Orlando (FL, USA), 2002, p. III- 2337 - III-2340.

Keywords: VBEM algorithm, joint iterative data detection and channel estimation, channel estimation errors, OFDM

Y. Wang, A. Liu, D. Guo, X. Liu [references] [full-text] [Download Citations]
Reduced-complexity Non-data-aided Timing Recovery for PAM-based M-ary CPM Receivers

Continuous phase modulation (CPM) is a widely used modulation scheme in communication systems. However, difficulties arise with the design of CPM receivers, due to the nonlinear nature of CPM. One popular solution is to linearize CPM with pulse amplitude modulation (PAM) representation. In this paper, a reduced-complexity non-data-aided (NDA) timing recovery method for PAM-based M-ary CPM receivers is proposed. The proposed method is based on the PAM representation and maximum likelihood principle. The merits of the proposed method are twofold. On one hand, the proposed method is reduced-complexity in nature for PAM-based CPM receivers, i.e., it shares the match filter bank with PAM-based detectors. On the other hand, it is shown that the performance of the proposed method is better than the existing method with some modulation schemes. Therefore, the proposed method provides an important synchronization component for PAM-based M-ary CPM receivers.

  1. LAURENT, P. A. Exact and approximate construction of digital phase modulations by superposition of amplitude modulated pulses (AMP). IEEE Transactions on Communications, 1986, vol. 34, no. 2, p. 150 - 160.
  2. MENGALI, U., MORELLI, M. Decomposition of M-ary CPM signals into PAM waveforms. IEEE Transactions on Information Theory, 1995, vol. 41, no. 5, p. 1265 - 1275.
  3. PERRINS, E., RICE, M. PAM decomposition of M-ary multi-h CPM. IEEE Transactions on Communications, 2005, vol. 53, no. 12, p. 2065 - 2075.
  4. PERRINS, E., RICE, M. PAM representation of ternary CPM. IEEE Transactions on Communications, 2008, vol. 56, no. 12, p. 2020 - 2024.
  5. CARIOLARO, G., A system-theory approach to decompose CPM signals into PAM waveforms. IEEE Transactions on Communications, 2010, vol. 58, no. 1, p. 200 - 210.
  6. KALEH, G. K. Simple coherent receivers for partial response continuous phase modulation. IEEE Transactions on Communications, 1989, vol. 7, no. 12, p. 1427 - 1436.
  7. PERRINS, E., RICE, M. A new performance bound for PAMbased CPM detectors. IEEE Transactions on Communications, 2005, vol. 53, no. 10, p. 1688 - 1696.
  8. PERRINS, E., KUMARASWAMY, B. Decision feedback detectors for SOQPSK. IEEE Transactions on Communications, 2009, vol. 57, no. 8, p. 2359 - 2368.
  9. PERRINS, E., RICE, M. Reduced-complexity approach to iterative detection of coded SOQPSK. IEEE Transactions on Communications, 2007, vol. 55, no, 7, p. 1354 - 1362.
  10. WARDLE, M., RICE, M. PAM approach to weak CPM and its application to flight termination receivers. IEEE Transactions on Aerospace and Electronic Systems, 2008, vol. 44, no. 2, p. 468 - 480.
  11. COLAVOLPE, G., RAHELI, R. Reduced-complexity detection and phase synchronization of CPM signals. IEEE Transactions on Communications, 1997, vol. 45, no. 9, p. 1070 - 1079.
  12. MORELLI, M., VITETTA, G. M. Joint phase and timing recovery for MSK-type signals. IEEE Transactions on Communications, 2000, vol. 48, no. 12, p. 1997 - 1999.
  13. PERRINS, E., BOSE, S., WYLIEGREEN, M. P. Timing recovery based on PAM representation of CPM. In IEEE Military Communications Conference, MILCOM 2008. San Diego (CA, USA), 2008, p. 1 - 8.
  14. CHANDRAN, P., PERRINS, E. Decision-directed symbol timing recovery for SOQPSK. IEEE Transactions on Aerospace and Electronic Systems, 2009, vol. 45, no. 2, p. 781 - 789.
  15. D’ANDREA, A. N., GINESI, A., MENGALI, U. Frequency detectors for CPM signals. IEEE Transactions on Communications, 1995, vol. 43, no. 2,3,4, p. 1828 - 1837.
  16. LAMBRETTE, U., MEYR, H. Two timing recovery algorithms for MSK. In IEEE International Conference on Communications, ICC’94. New Orleans (USA), 1994, p. 1155 - 1159.
  17. MELHAN, R., CHEN, Y. E., MEYR, H. A fully digital feedforward MSK demodulator with joint frequency offset and symbol timing estimation for burst mode mobile radio. IEEE Transactions on Vehicular Technology, 1993, vol. 42, no. 4, p. 434 - 443.
  18. D’ANDREA, A. N., MENGALI, U., REGGIANNINI, R. A digital approach to clock recovery in generalized minimum shift keying. IEEE Transactions on Vehicular Technology, 1990, vol. 39, no. 3, p. 227 - 234.
  19. CHANDRAN, P., PERRINS, E. Symbol timing recovery for CPM with correlated data symbols. IEEE Transactions on Communications, 2009, vol. 57, no. 5, p. 1265 - 1270.
  20. FUSCO, T., IZZO, L., PETRELL, A., TANDA, M. Blind symbol timing estimation for OFDM/OQAM systems. IEEE Transactions on Signal Processing, 2009, vol. 57, no. 12, p. 4952 - 4958.
  21. D’ANDREA, A. N., MENGALI, U., MORELLI, M. Symbol timing estimation with CPM modulation. IEEE Transactions on Communications, 1996, vol. 44, no. 10, p. 1362 - 1372.
  22. MORELLI, M., MENGALI, U., VITETTA, G. M. Joint phase and timing recovery with CPM signals. IEEE Transactions on Communications, 1997, vol. 45, no. 7, p. 867 - 876.

Keywords: Continuous phase modulation, pulse amplitude modulation representation, timing recovery, non-data-aided, reduced-complexity

M. Blaha, J. Machac [references] [full-text] [Download Citations]
Planar Resonators for Metamaterials

This paper presents the results of an investigation into a combination of electric and magnetic planar resonators in order to design the building element of a volumetric metamaterial showing simultaneously negative electric and magnetic polarizabilities under irradiation by an electromagnetic wave. Two combinations of particular planar resonators are taken into consideration. These planar resonators are an electric dipole, a split ring resonator and a double H-shaped resonator. The response of the single resonant particle composed of a resonator with an electric response and a resonator with a magnetic response is strongly anisotropic. Proper spatial arrangement of these particles can make the response isotropic. This is obtained by proper placement of six planar resonators on the surface of a cube that now represents a metamaterial unit cell. The cells are distributed in space with 3D periodicity.

  1. BAENA, J. D., JELINEK, L., MARQUES, R., ZEHENTNER, J. Electrically small isotropic three-dimensional magnetic resonators for metamaterial design. Applied Physics Letters, 2006, vol. 88, p. 134108-1 to 134108-3.
  2. SILVEIRINHA, M. G., FERNANDES, C. A. Homogenization of 3-D-connected and nonconnected wire metamaterials. IEEE Trans. on Microwave Theory and Techniques, 2005, vol. 53, p. 1418 to 1430.
  3. KOSCHNY, T., ZHANG, L., SOUKOULIS, C. Isotropic threedimensional left-handed metamaterials. Physical Review B, 2005, vol. 71, no. 12, 121103(R), 4 pages.
  4. RUDOLPH, S., GRBIC, A. The design and performance of an isotropic negative-refractive-index metamaterial lens. In 2011 XXXth URSI General Assembly and Scientific Symposium, p. 1-4, 2011.
  5. HOLLOWAY, C. L., KUESTER, E. F., BAKER-JARVIS, J., KABOS, P. A double negative (DNG) composite medium composed of magnetodielectric spherical particles embedded in a matrix. IEEE Trans. Antennas Propag., 2003, vol. 51, no. 10, p. 2596-2603.
  6. VENDIK, I., VENDIK, O., ODIT, M. Isotropic artificial media with simultaneously negative permittivity and permeability. Microwave and Opt. Tech. Lett., 2006, vol. 48, p. 2553-2556.
  7. ZEDLER, M., CALOZ, C., RUSSER, P. A 3-D isotropic lefthanded metamaterial based on the rotated transmission-line matrix (TLM) scheme. IEEE Transaction on Microwave Theory and Techniques, 2007, vol. 55, p. 2930-2941
  8. IYER, A., ELEFTHERIADES, G. A three-dimensional isotropic transmission-line metamaterial topology for free-space excitation. Applied Physics Letters, 2008, vol. 92, no. 26, 261106, 3 pages.
  9. HUDLICKA, M., MACHAC, J. Triple wire medium for use in isotropic metamaterials. In Proceedings of the 37th European Microwave Conference. Munich (Germany), October 2007, CDROM, p. 628-631.
  10. BLAHA, M., MACHAC, J., RYTIR, M. A double H-shaped resonator and its use as an isotropic ENG metamaterial. International Journal on Microwave and Wireless Technologies, Aug. 2009, vol. 1, no. 4, p. 315-321.
  11. HRABAR, S., BENIC, L., BARTOLIC, J. Simple experimental determination of complex permittivity or complex permeability of SNG metamaterials. In Proceedings of the 36th European Microwave Conference. Manchester (UK), 2006, p. 1395-1398.
  12. NICHOLSON, K. J., GHORBANI, K. Design, manufacture and measurement of a metamaterial with tunable negative-refractive index region. In APMC 2009. Asia Pacific Microwave Conference. Singapore, 2009, p. 1231-1233.
  13. BECVAR, V., BLAHA, M., MACHAC, J. Planar resonator with negative electric and magnetic polarizabilities. In Proceedings of the 21st International Conference Radioelektronika. Brno (Czech Rep.), April 2011, p.147-150.
  14. KRUPKA, J., GWAREK, W., KWIETNIEWSKI, N., HARTNETT, J. G. Measurements of planar metal–dielectric structures using split-post dielectric resonators. IEEE Transactions on Microwave Theory and Techniques, 2010, vol. 58, no. 12, p. 3511-3518.
  15. JELINEK, L., BAENA, J. D., MARQUES, R., ZEHENTNER, J. Direct polarizability extraction method. In Proceedings of the 36th European Microwave Conference. Manchester (UK), 2006, CDROM, p. 983-986.
  16. TRETYAKOV, S. Analytical Modelling in Applied Electromagnetics. Boston, London: Artech House, 2003.
  17. MACHAC J., PROTIVA P., ZEHENTNER J. Isotropic epsilonnegative particles. In Proceedings of the 2007 IEEE MTT-S International Microwave Symposium. Honolulu (Hi., USA), June 2007, TH4D-03, CD ROM.
  18. SCHURING, D., MOCK, J. J., SMITH, D. R. Electric-fieldcoupled resonators for negative permittivity metamaterials. Applied Phys. Letters, 2006, vol. 88, p. 041109-1 to 041109-3.
  19. PADILLA, W. J., ARONSSON, M. T., HIGSTRETE, C., LEE, M., TAYLOR, A. J., AVERITT, R. D. Electrically resonant terahertz metamaterials: Theoretical and experimental investigations. Physical Review B, 2007, vol. 75, p. 04102-1 to 04102-4.
  20. http://www.t-ceram.com/ceramic-materials.htm

Keywords: Metamaterial, negative electric polarizability, negative magnetic polarizability, isotropic response, planar resonator.

M. Gokten [references] [full-text] [Download Citations]
Efficient Analysis of Ferrite Loaded Waveguides Using the MRFD Method

A full wave two-dimensional Multiresolution Frequency Domain formulation for efficient analysis of the dispersion characteristics of ferrite loaded waveguide structures is developed and presented. It has been concluded that the proposed formulation, which takes advantage of the compactly supported wavelet bases to expand electric and magnetic fields, allows coarser discretization compared to conventional Finite Difference Frequency Domain (FDFD) scheme. The efficiency and accuracy of the newly developed formulation, in comparison to FDFD method, is demonstrated by solving the dispersion characteristics of fully and partially ferrite loaded waveguide structures.

  1. OKONIEWSKI, M., OKONIEWSKA, E. FDTD analysis of magnetized ferrites: A more efficient algorithm. IEEE Microwave and Guided Wave Letters, 1994, vol. 4, no. 6, p. 169 - 171.
  2. PEREDA, J. A., VIELVA, L. A., SOLANO, M. A., VEGAS, A., PRIETO, A. FDTD analysis of magnetized ferrites. Application to the calculation of dispersion characteristics of ferrite-loaded waveguides. IEEE Transactions on Microwave Theory and Techniques, 1995, vol. 43, no. 2, p. 350.
  3. AL-BARQAWI, H., DIB, N., KHODIER M. A two-dimensional full-wave finite-difference frequency-domain analysis of ferrite loaded structures. International Journal of Infrared and Millimeter Waves, 2008, vol. 29, no. 5, p. 443 - 456.
  4. ROBERTSON, R., TENTZERIS, M., KRUMPHOLZ, M., KATEHI, L. P. B. Modelling of dielectric cavity structures using multiresolution time-domain analysis. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 1998, vol. 11, p. 55 -68
  5. FUJII M., HOEFER, W. J. R. A wavelet formulation of the finitedifference method: Full-vector analysis of optical waveguide junctions. IEEE Journal of Quantum Electronics, 2001, vol. 37, no. 8, p. 1015-1029.
  6. DOGARU, T., CARIN, L. Multiresolution time-domain using CDF biorthogonal wavelets. IEEE Transactions on Microwave Theory and Techniques, 2001, vol. 49, no. 5, p. 902-912.
  7. GOKTEN, M., ELSHERBENI, A. Z., ARVAS, E. Electromagnetic scattering analysis using the two-dimensional MRFD formulation. Progress in Electromagnetics Research, 2008, vol. 79, p. 404 - 416.
  8. GOKTEN, M., ELSHERBENI, A. Z., ARVAS, E. A multiresolution frequency domain method using biorthogonal wavelets. In 22nd Annual Review of Progress in Applied Computational Electromagnetics. Miami, (U.S.A.), 2006, p. 16-21.
  9. YAGLI, A. F. MRFD method for scattering from three dimensional dielectric bodies. Radio Engineering, Sept. 2001, vol. 20, no. 3, p. 581-586.
  10. DAUBECHIES, I. Ten Lectures on Wavelets. Philadelphia, PA: Society for Industrial and Applied Mathematics, 1992.
  11. GOKTEN, M., ELSHERBENI, A. Z., ARVAS, E. The multiresolution frequency domain method for general guided wave structures. Progress in Electromagnetics Research, 2007, vol. 69, p. 55- 66.
  12. POZAR, D. M. Microwave Engineering. 3rd ed. John Wiley, 2005.
  13. LEHOUCQ, R. B., SORENSEN, D. C., YANG, C. ARPACK Users' Guide: Solution of Large-Scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods, SIAM, 1998
  14. KRUMPHOLZ, M., KATEHI, L. P. B. MRTD: new time-domain schemes based on multiresolution analysis. IEEE Trans. on Microwave Theory and Techniques, 1996, vol. 44, no. 4, p. 555 -571.

Keywords: Multiresolution analysis, Finite Difference Method, MRFD, ferrite loaded waveguide, frequency domain

K. N. Abdul Rani, M. F. Abdul Malek, N. Siew-Chin [references] [full-text] [Download Citations]
Nature-inspired Cuckoo Search Algorithm for Side Lobe Suppression in a Symmetric Linear Antenna Array

In this paper, we proposed a newly modified cuckoo search (MCS) algorithm integrated with the Roulette wheel selection operator and the inertia weight controlling the search ability towards synthesizing symmetric linear array geometry with minimum side lobe level (SLL) and/or nulls control. The basic cuckoo search (CS) algorithm is primarily based on the natural obligate brood parasitic behavior of some cuckoo species in combination with the Levy flight behavior of some birds and fruit flies. The CS metaheuristic approach is straightforward and capable of solving effectively general N-dimensional, linear and nonlinear optimization problems. The array geometry synthesis is first formulated as an optimization problem with the goal of SLL suppression and/or null prescribed placement in certain directions, and then solved by the newly MCS algorithm for the optimum element or isotropic radiator locations in the azimuth-plane or xy-plane. The study also focuses on the four internal parameters of MCS algorithm specifically on their implicit effects in the array synthesis. The optimal inter-element spacing solutions obtained by the MCS-optimizer are validated through comparisons with the standard CS-optimizer and the conventional array within the uniform and the Dolph-Chebyshev envelope patterns using MATLABTM. Finally, we also compared the fine-tuned MCS algorithm with two popular evolutionary algorithm (EA) techniques include particle swarm optimization (PSO) and genetic algorithms (GA).

  1. WAGIH, M. M. M., ELKAMCHOUCHI, H. M. Application of particle swarm optimization algorithm in smart antenna array systems. Progress in Electromagnetics Research, 2009, p. 461 to 476.
  2. HO, M.-H., LIAO, S.-H., CHIU, C.-C. A novel smart UWB antenna array design by PSO. Progress in Electromagnetics Research C, Aug 2010, vol. 15, p. 103-115.
  3. GROSS, F. Smart Antennas for Wireless Communications with MATLAB. New York: McGraw-Hill, 2005.
  4. PAL, S., BASAK, A., DAS, S., ABRAHAM, A. Linear antenna array synthesis with invasive weed optimization algorithm. In International Conference of Soft Computing and Pattern Recognition, 2009, p. 161-166.
  5. ZAHARIS, Z., KAMPITAKI, D., PAPASTERGIOU, A., HATZIGAIDAS, A., LAZARIDIS, P., SPASOS, M. Optimal design of a linear antenna array using particle swarm optimization. In 5th WSEAS Int. Conf. on Data Networks, Communications and Computers. Bucharest (Romania), 2006.
  6. NIK ABD MALIK, N. N., ESA, M., SYED YUSOF, S. K., MARIMUTHU, J. Suppression of antenna's radiation side lobes using particle swarm optimization. In Progress in Electromagnetics Research Symposium. Moscow (Russia), 2009.
  7. KHODIER, M. M., CHRISTODOULOU, C. G. Linear array geometry synthesis with minimum side lobe level and null control using particle swarm optimization. IEEE Trans. Antennas Propag., Aug. 2005, vol. 53, p. 2674-2679.
  8. GAVIRIA, N., MELDE, K. L., MCNEILL, K. M., RODRIGUEZ, J. J. Development of array distributions for smart antennas with low side lobes, interference-nulling, and effective radiated voltage constraints. In IEEE Antennas and Propagation Society International Symposium. Albuquerque (NM, USA), 2006, p. 3323-3326.
  9. CENGIZ, Y., TOKAT, H. Linear antenna array design with use of genetic, memetic and tabu search optimization algorithms. Progress in Electromagnetics Research C, 2008, vol. 1, p. 63-72.
  10. LEE, K. C. Frequency-domain analyses of nonlinearly loaded antenna arrays using simulated annealing algorithms. Progress in Electromagnetics Research, 2005, vol. 53, p. 271-281.
  11. KHODIER, M. M., AL-AQEEL, M. Linear and circular array optimization: A study using particle swarm intelligence. Progress in Electromagnetics Research B, 2009, vol. 15, p. 347-373.
  12. DOLPH, C. A current distribution for broadside arrays which optimizes the relationship between beam width and side lobe level. Institute of Radio Engineers, 1946, p. 335-348.
  13. GREENBERG, M. Advanced Engineering Mathematics. New Jersey: Prentice-Hall, 1998.
  14. BALANIS, C. A. Antenna Theory Analysis and Design. 3rd ed. San Francisco: John Wiley, 2005.
  15. BATAINEH, M. H. On Chebyshev array design using particle swarm optimization. Journal of Electromagnetic Analysis and Applications, 2011, vol. 3, p. 213-219.
  16. MERAD, L., BENDIMERAD, F., SIDI, M. Design of linear antenna arrays for side lobe reduction using the tabu search method. The International Arab Journal of Information Technology, 2008, vol. 5, p. 219-222.
  17. Cuckoo search. vol. 2011: Wikipedia, 2010.
  18. YANG, X.-S., DEB, S. Cuckoo Search via Levy flights. In Proc. World Congr. on Nature & Biologically Inspired Computing (NaBIC 2009). India, 2009, p. 210-214.
  19. YANG, X.-S., DEB, S. Engineering optimization by cuckoo search. Int. J. Mathematical Modelling and Numerical Optimization, Dec 2010, vol. 1, no. 4, p. 330-343.
  20. BLUM, C., ROLI, A. Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Comput. Surv., 2003, vol. 35, p. 268-308.
  21. BROWN, C., LIEBOVITCH, L. S., GLENDON, R. Levy flights in Dobe Ju/'hoansi foraging patterns. Human Ecol., 2007, vol. 35, p. 129-138.
  22. REYNOLDS, A. M., FRYE, M. A. Free-flight odor tracking in Drosophila is consistent with an optimal intermittent scale-free search. PLoS One, 2007, vol. 2, p. e354.
  23. PAVLYUKEVICH, I. Levy flights, non-local search and simulated annealing. J. Comput. Physics, 2007, vol. 226, p. 1830-1844.
  24. Levy flight. Vol. 2011: Wikipedia, 2011.
  25. SHLESINGER, M. F. Search research. Nature, 2006, vol. 443, p. 281-282.
  26. MANTEGNA, R. N. Fast, accurate algorithm for numerical simulation of Levy stable stochastic processes. Physical Review E, 1994, vol. 49, p. 4677-4683.
  27. Financial applications of stable distribution. In Handbook of Stats. vol. 14, 1996.
  28. CHAMBERS, J. M., MALLOWS, C. L., STUCK, B. W. A method for simulating stable random variables. Journal of the American Stats. Assoc., 1976, vol. 71, p. 340-344.

Keywords: Modified cuckoo search, side lobe suppression, null control, linear array, isotropic radiator, Dolph-Chebyshev.

N. Zakaria, S. K. A. Rahim, T. S. Ooi, K. G. Tan, A. W. Reza, M. S. A. Rani [references] [full-text] [Download Citations]
Design of Stacked Microstrip Dual-band Circular Polarized Antenna

This study introduces a new design of dual-band circular polarized (CP) microstrip antenna for ISM band applications (2.45 GHz and 5.8 GHz). The proposed dual-band CP microstrip antenna with compact design has achieved design intention of having return loss of < −10 dB and axial ratio of < 3 dB for both frequencies of 2.45 GHz and 5.8 GHz. The antenna has been successfully designed, fabricated, simulated, and measured and it shows the advantages of good dual-band and CP performances. Thus, the obtained results confirm satisfactory performance and good agreement.

  1. YANG, K. P., WONG, K. L. Dual-band circularly-polarized square microstrip antenna. IEEE Transactions on Antennas and Propagation, 2001, vol. 49, p. 377-382.
  2. OH, J.-H., HONG, Y.-P., YOOK, J.-G. Dual circularly polarized stacked patch antenna for GPS/SDMB. In IEEE International Symposium on Antennas and Propagation Society. San Diego (USA), July 2008, p. 1-4.
  3. KIM, H. J., KIM, S. M., SON, J. M., YANG, W. G. Design and implementation of dual band circular polarization square patch antenna. In Proc. Asia-Pacific Microwave Conf. (APMC 2005). Suzhou (China), Dec. 2005, p. 1-4.
  4. LIAO, W., CHU, Q.-X. Dual-band circularly polarized microstrip antenna with small frequency ratio. Progress in Electromagnetics Research Letters, 2010, vol. 15, p. 145-152.
  5. BAO, X. L., AMMANN, M. J. Dual frequency circularly polarized patch antenna with compact size and small frequency ratio. IEEE Transactions on Antennas and Propagation, 2007, vol. 50, p. 2104-2107.
  6. MALEKABADI, S. A., ATTARI, A. R., MIRASALEHI, M. M. Compact and broadband circular polarized microstrip antenna with wide band axial ratio bandwidth. In International Symposium on Telecommunication. Tehran (Iran), 2008, p. 106 - 109.
  7. LAI, D.-Q., CHU, Q.-X. A stacked dual-band equilateral-triangular circularly polarized microstrip antenna. In Proc. Asia-Pacific Microwave Conference (APMC 2008). Macau, 2008, p. 1 – 4.
  8. FUJIMOTO, T., TANANKA, K. Stacked square microstrip antenna with a shorting post for dual band operation in WLAN applications. In Proc. of Asia-Pacific Microwave Conference(APMC 2006). Yokohama (Japan), Dec. 2006, p. 1979-1982.
  9. OOI, T. S., RAHIM, S. K. A., KOH, B. P. 2.45 GHz and 5.8 GHz compact dual-band circularly polarized patch antenna. Journal of Electromagnetic Waves and Applications, 2010, vol. 24, no. 11-12, p. 1473-1482.
  10. LU, J.-H., TANG, C.-L., WONG, K.-L. Single-feed slotted equilateral-triangular microstrip antenna for circular polarization. IEEE Transactions on Antennas and Propagation, 1999, vol. 47, p. 1174-1178.
  11. FUJIMOTO, K., JAMES, J. R. Mobile Antenna Systems Handbook. Boston: Artech House Inc., 1994.
  12. KE, S.-Y. A dual-band microstrip antenna for precise GPS applications. WHAMPOA – An Interdisciplinary Journal (Department of Electrical Engineering, R.O.C. Military Academy, Taiwan), 2007.
  13. CHANG, T.-N., NI, G.-Y. Dual-band circular polarized antenna with a quad-EMC structure. Microwave and Optical Technology Letters, 2007, vol. 49, no. 3, p. 645-647.
  14. YANG, S., FENG, Q. Y., DONG, B. Broadband stacked annular ring patch antenna for CP operation. In International Conference on E-Business and Information System Security. Wuhan (China), May 2009, p. 1-3.
  15. THIAGARAJAH, S., BORHANUDDIN, M. A., HABAEBI, M. H. Circular polarized active microstrip antenna for commercial GPS application. In Proceedings of TENCON. Kuala Lumpur (Malaysia), 2000, vol. 1, p. 109 – 114.
  16. GARG, R., BHARTIA, P., BAHL, I., ITTIPIBOON, A. Microstrip Antenna Design Handbook. Artech House, 2001.
  17. SEKRA, P., BHATNAGAR, D., SAXENA, V. K., SAINI, J. S. Single feed circularly polarized edge truncated elliptical microstrip antenna. In 2009 International Conference on Emerging Trends in Electronic and Photonic Devices & Systems (ELECTRO-2009). Varanasi (India), 2009, p. 353-356.

Keywords: Microstrip antenna, patch antenna, circular polarized

R. K. Maharjan, B. Shrestha, N. Y. Kim [references] [full-text] [Download Citations]
Microstrip Cross-coupled Interdigital SIR Based Bandpass Filter

A simple and compact 4.9 GHz bandpass filter for C-band applications is proposed. This paper presents a novel microstrip cross-coupled interdigital half-wavelength stepped impedance resonator (SIR) based bandpass filter (BPF).The designed structure is similar to that of a combination of two parallel interdigital capacitors. The scattering parameters of the structure are measured using vector network analyzer (VNA). The self generated capacitive and inductive reactances within the interdigital resonators exhibited in a resonance frequency of 4.9 GHz. The resonant frequency and bandwidth of the capacitive cross-coupled resonator is directly optimized from the physical arrangement of the resonators. The measured insertion loss (S21) and return loss (S11) were 0.3 dB and 28 dB, respectively, at resonance frequency which were almost close to the simulation results.

  1. POZAR, D. M. Microwave Engineering. 3rd edition. New York, 2004.
  2. MANDAL, M. K., SANYAL, S. Compact wideband bandpass filter using microstrip to slotline broadside-coupling. IEEE Microwave and Wireless Components Letters, 2007, vol. 17, p. 640-642.
  3. CHEN, F., TU, Z., CHU, Q., YANG, J. A novel microstrip openloop resonator filter for high selectivity application. In Proceedings of Asia-Pacific Microwave Conference 2007. 11-14 December 2007.
  4. TU, W. H., CHANG, K. Compact microstip filter using open stub and spurline. IEEE Microwave and Wireless Components Letters, 2005, vol. 15, p. 268-270.
  5. VAGNER, P., KASAL, M. A novel bandpass filter using a combination of open-loop defected ground structure and half-wavelength microstrip resonators. Radioengineering, 2010, vol. 19, no. 3, p. 392-396.
  6. JUNG, D. J., LEE, J. K., CHANG, K. Wideband bandpass filter using microstrip ring. Microwave and Optical Technology Letters, 2011, vol. 53, p. 154-155.
  7. LEE, G. A. MEGAHED, M. A., FLAVIIS, F. D. Low-cost compact spiral inductor resonator filters for system-in-a-package. IEEE Transactions on Advanced Packaging, 2005, vol. 28, p. 761-771.
  8. BAO, Z. H., CHEN, J. X., TANG, H., ZHOU, L. H. Compact dual-band bandpass filter using slot-line resonator. Microwave and Optical Technology Letters, 2010, vol. 52, p. 2299-2300.
  9. SAGAWA, M., TAKAHASHI, K., MAKIMOTO, M. Miniaturized hairpin resonator filters and their application to receiver frontend MIC’s. IEEE Trans. Microwave Theory Tech., 1989, vol. 37, p. 1991-1997.
  10. MATTHAEI, G. L., FENZI, N. O., FORSE, R. J., ROHLFING, S. M. Hairpin-comb filters for HTS and other narrow-band applications. IEEE Trans. Microwave Theory Tech., 1997, vol. 45, p. 1226-1231.
  11. YABUKI, H., SAGAWA, M., MAKIMOTO, M. Voltage controlled push-push oscillators using miniaturized hairpin resonators. IEEE MTT-S Int Microwave Symp Dig., 1991, vol. 3, p. 1175-1178.
  12. LEE, S. Y., TSAI, C. M. New cross-coupled filter design using improved hairpin resonators. IEEE Trans. Microwave Theory Tech., 2000, vol. 48, p. 2482-2490.
  13. SHRESTHA, B., MAHARJAN, R. K., CHO, S., YOON, K. C., KIM, N. Y. A low-phase noise oscillator using spurline resonator for I-band application. In Asia-Pacific Microwave Conference, APMC-2010. Yokohama (Japan), 2010, p. 469-472.
  14. HONG, J. S., LANCASTER, M. J. Microstrip Filters for RF/Microwave Applications. A Wiley-Interscience Publication, John Wiley & Sons, Inc. 2001.
  15. MAKIMOTO, M., YAMASHITA, S. Microwave Resonators and Filters for Wireless Communications, Theory, Design and Application. Berlin Heidelberg New York: Springer-Verlag, 2001.
  16. WADELL, B. C. Transmission Line Design Handbook. USA: Artech House, 1991.

Keywords: Bandpass filter, interdigital resonator, stepped impedance resonator (SIR), half wavelength SIR resonator

W. Jaikla, S. Siripongdee, P. Suwanjan [references] [full-text] [Download Citations]
MISO Current-mode Biquad Filter with Independent Control of Pole Frequency and Quality Factor

This article presents a three-inputs single-output biquadratic filter performing completely standard functions: low-pass, high-pass, band-pass, band-reject and all-pass functions, based on current controlled current conveyor transconductance amplifier (CCCCTA). The quality factor and pole frequency can be electronically/independently tuned via the input bias current. The proposed circuit uses 2 CCCCTAs and 2 grounded capacitors without external any resistors which is very suitable to further develop into an integrated circuit. The filter does not require double input current signal. Each function response can be selected by suitably selecting input signals with digital method. Moreover, the circuit possesses high output impedance which would be an ideal choice for current-mode cascading. The PSPICE simulation results are included to verify the workability of the proposed filter. The given results agree well with the theoretical anticipation.

  1. TOUMAZOU, C. LIDGEY, F. J. HAIGH, D. G. Analogue IC Design: The Current-Mode Approach. Stevenage (UK): Peter Peregrinus, 1990.
  2. BAJER, J., LAHIRI, A., BIOLEK, D. Current-mode CCII+ based oscillator circuits using a conventional and a modified Wienbridge with all capacitors grounded. Radioengineering, 2011, vol. 20, no. 1, p. 245 - 250.
  3. LI, Y. Current-mode sixth-order elliptic band-pass filter using MCDTAs. Radioengineering, 2011, vol. 20, no. 3, p. 645 - 649.
  4. JAIKLA, W., NOPPAKARN, A., LAWANWISUT, S. New gain controllable resistor-less current-mode first order allpass filter and its application. Radioengineering, 2012, vol. 21, no. 1, p. 312 to 316.
  5. SEDRA, A. S., SMITH, K. C. Microelectronic Circuits. 3rd ed. Florida (USA): Holt, Rinehart and Winston, 1991.
  6. IBRAHIM, M. A., MINAEI, S., KUNTMAN, H. A. A 22.5 MHz current-mode KHN-biquad using differential voltage current conveyor and grounded passive elements. International Journal of Electronics and Communication (AEU), 2005, vol. 59, no. 5, p. 311 - 318.
  7. SOLIMAN, A. M. New current mode filters using current conveyors. International Journal of Electronics and Communication (AEU), 1997, vol. 51, no. 3, p. 275 - 278.
  8. TANGSRIRAT, W., SURAKAMPONTORN, W. Systematic realization of cascadable current-mode filters using CDTAs. Frequenz, 2006, vol. 60, p. 241-245.
  9. SIRIPRUCHYANUN, M., JAIKLA, W. Electronically controllable current-mode universal biquad filter using single DOCCCDTA. Circuits, Systems & Signal Processing, 2008, vol. 27, no. 1, p. 113 - 122.
  10. HORNG, J-W. Current-mode universal biquadratic filter with five inputs and one output using tree ICCIIs. Indian Journal of Pure & Applied Physics, 2011, vol. 49, p. 214 - 217.
  11. SINGH, S. V., MAHESHWARI, S., CHAUHAN D. S. Single MO-CCCCTA-based electronically tunable current/transimpedance- mode biquad universal filter. Circuits and Systems, 2011, vol. 2, no. 1, p. 1 - 6.
  12. LEE, C.-N. Multiple-mode OTA-C universal biquad filters. Circuits, Systems & Signal Processing, 2010, vol. 29, no. 2, p. 263 to 274.
  13. ARSLAN, E., METIN, B., CIEKOGLU, O. Multi-input singleoutput cascadable current-mode universal filter topology with a single current conveyor. In Proceedings of the Third IASTED International Conference Circuits, Signals, and Systems. Marina del Rey (CA, USA), 2005, p. 62 - 66.
  14. SENANI, R., ABDALLA, K. K., BHASKAR, D. R. A state variable method for the realization of universal current-mode biquads. Circuits and Systems, 2011, vol. 2, no. 4, p. 286 - 292.
  15. PANDEY, N., PAUL, S. K. VM and CM universal filters based on single DVCCTA. Active and Passive Electronic Components, 2011, Article ID 929507.
  16. SINGH, S. V. MAHESHWARI, S., CHAUHAN, D. S. Electronical-ly tunable current-mode SIMO/MISO universal biquad filter using MO-CCCCTAs. International Journal of Recent Trends in Engineering and Technology, 2010, vol. 3, no. 3, p. 65 - 70.
  17. CHUNHUA, W., HAIGUANG, L., YAN, Z. Universal currentmode filter with multiple inputs and one output using MOCCII and MO-CCCA. International Journal of Electronics and Communication (AEU), 2009, vol. 63, no. 6, p. 448 - 453.
  18. OZCAN, S., KUNTMAN, H., ÇIÇEKOGLU, O. A novel multiinput single-output filter with reduced number of passive elements using single current conveyor. In Proceedings of the 43rd IEEE Midwest Symposium on Circuits and Systems. Lansing (MI, USA), 2000, p. 1030 - 1032.
  19. SAWANGAROM, V., DUMAWIPATA, T., TANGSRIRAT, W., SURAKAMPONTORN, W. Cascadable three-input single-output current-mode universal filter using CDBAs. In The 2007 ECTI International Conference, 2007, p. 53 - 56.
  20. CHANNUMSIN, O., PUKKALANUN, T., TANGSRIRAT, W. Universal current-mode biquad with minimum components. In Proceedings of the 2011 International MultiConference of Engineering and Computer Scientists, IMECS 20011. Hong Kong (China), 2011, p. 1012 - 1015.
  21. TANGSRIRAT, W., SURAKAMPONTORN W. Electronically tunable current-mode universal filter employing only plus-type current-controlled conveyors and grounded capacitors. Circuits, Systems & Signal and Processing, 2006, vol. 27, no. 6, p. 701 - 713.
  22. TANGSRIRAT, W. Cascadable current-controlled current-mode universal filters using CDTAs and grounded capacitors. Journal of Active and Passive Electronic Devices, 2009, vol. 4, p. 135 - 145.
  23. TANGSRIRAT, W., DUMAWIPATA, T. SURAKAMPONTORN, W. Multiple-input single-output current-mode multifunction filter using current differencing transconductance amplifiers. International Journal of Electronics and Communication (AEU), 2007, vol. 61, no. 4, p. 209 - 214.
  24. TANGSRIRAT, W., PUKKALANUN, T. Structural generation of two integrator loop filters using CDTAs and grounded capacitors. International Journal of Circuit Theory and Applications, 2011, vol. 39, no. 1, p. 31 - 45.
  25. HORNG, J.-W. High output impedance current-mode universal biquadratic filters with five inputs using multi-output CCIIs. Microelectronics Journal, 2011, doi:10.1016/j.mejo.2011.02.007.
  26. PANDEY, N., PAUL, S. K. Multi-input single-output universal current mode biquad. Journal of Active and Passive Electronic Devices, 2006. vol. 1, no. 3 - 4, p. 229 - 240.
  27. KUMNGERN, M. Multiple-input single-output current-mode universal filter using translinear current conveyors. Journal of Electrical and Electronics Engineering Research, 2011, vol. 3, no. 9, p. 162 - 170.
  28. PROMMEE, P. ANGKEAW, K. SOMDUNYAKANOK, M. DEJHAN, K. CMOS-based near zero-offset multiple inputs max– min circuits and its applications. Analog Integrated Circuits and Signal Processing, 2009, vol. 61, no. 1, p. 93 - 105.

Keywords: Analog filter, CCCCTA, Current-mode, Multiple input-Single output

N. Schwerg [references] [full-text] [Download Citations]
Symbolical Analysis of RF-Network Problems using Mason’s Rule

We briefly review Mason’s rule for the computation of RF-network problems and show its implementation into the software package freeMASON. This tool solves symbolically Mason’s rule for any wave quantity and allows to derive analytical expressions as well as their functional evaluation. We demonstrate our approach studying the effect of an unbalanced magictee on the RF power distribution to two accelerating cavities.

  1. VALUCH, D. High CW Power, Phase and Amplitude Modulator Realized with Fast Ferrite Phase-Shifters. PhD thesis. Bratislava (Slovakia): Slovak University of Technology, 2004.
  2. FRISCHHOLZ H. Generation and distribution of radio-frequency power in LEP. IEEE Transactions on Nuclear Science, 1985, vol. 32, no. 5, p. 2791 - 2793.
  3. HADI, M. F., PIKET-MAY, M. A modified FDTD (2, 4) scheme for modeling electrically large structures with high-phase accuracy. IEEE Transactions on Antennas and Propagation, 1997, vol. 45, no. 2, p. 254 - 263.
  4. KUROKAWA, K. Power waves and the scattering matrix. IEEE Transactions on Microwave Theory and Techniques, 1965, vol. 13, no. 2, p. 194 - 202.
  5. Hewlett Packard. S-parameter design, Application Note 154. 1990.
  6. MASON, S. J. Feedback theory - some properties of signal flow graphs. Proceedings of the IRE, 1953, vol. 41, no. 9, p. 1144 - 1156.
  7. MASON, S. J. Feedback theory - further properties of signal flow graphs. Proceedings of the IRE, 1956, vol. 44, no. 7, p. 920 - 926.
  8. BRUNNER, O., SCHWERG, N., CIAPALA, E. RF power generation in Linac4. In Proceedings of 25th Linear Accelerator Conference. Tsukuba (Japan), 2010.
  9. SCHWERG, N. freeMASON 1.0: Software Package for Mathematica 7.0. 2012. (contact author for free download).
  10. GLOCK, H.-W., ROTHEMUND, K., VAN RIENEN, U. CSC - a procedure for coupled S-Parameter calculations. IEEE Transactions on Magnetics, 2002, vol. 38, no. 2, p. 1173 - 1176.

Keywords: Mason’s rule, symbolical network analysis, RF power distribution, S-parameters, flow graph

P. Struhovsky, O. Subrt, J. Hospodka, P. Martinek [references] [full-text] [Download Citations]
Developing Model-Based Design Evaluation for Pipelined A/D Converters

This paper deals with a prospective approach of modeling, design evaluation and error determination applied to pipelined A/D converter architecture. In contrast with conventional ADC modeling algorithms targeted to extract the maximum ADC non-linearity error, the innovative approach presented allows to decompose magnitudes of individual error sources from a measured or simulated response of an ADC device. Design Evaluation methodology was successfully applied to Nyquist rate cyclic converters in our works [13]. Now, we extend its principles to pipelined architecture. This qualitative decomposition can significantly contribute to the ADC calibration procedure performed on the production line in term of integral and differential nonlinearity. This is backgrounded by the fact that the knowledge of ADC performance contributors provided by the proposed method helps to adjust the values of on-chip converter components so as to equalize (and possibly minimize) the total non-linearity error. In this paper, the design evaluation procedure is demonstrated on a system design example of pipelined A/D converter. Significant simulation results of each stage of the design evaluation process are given, starting from the INL performance extraction proceeded in a powerful Virtual Testing Environment implemented in Maple™ software and finishing by an error source simulation, modeling of pipelined ADC structure and determination of error source contribution, suitable for a generic process flow.

  1. PARENTI, M., VECCHI, G., BONI, A., CHIORBOLI, G., Systematic design and modeling of high-resolution, high-speed pipeline ADCs. Measurement, 2005, vol. 37, no. 4, p. 344 - 351.
  2. HUNG-CHIH, L., ZWEI-MEI, L., JIEH-TSORNG, W. A 15b 20MS/s CMOS pipelined ADC with digital background calibration. Digest Proc. ISSCC, 2004, article No. 25.2, on-line version.
  3. YUN, R., QIN, Y., SIGNELL, S. LMS-based calibration of pipelined ADCs including linear and nonlinear errors. In Proc. IEEE Conf. ECCTD. Seville (Spain), 2007, p. 348-351.
  4. CHIORBOLI, G., MORANDI, C. Functional simulation of a technique for background calibration of capacitor mismatch errors in pipelined A/D converters. Measurement, 2006, vol. 39, no. 3, p. 204-212.
  5. WRIXON, A., KENNEDY, M. P. A rigorous exposition of the LEMMA method for analog and mixed-signal testing. IEEE Trans. Instrum. Meas., October 1999, vol. 48, no. 5, p. 978-985.
  6. MALOBERTI, F. Data Converters. Springer, 2007. ISBN 978-0- 387-32485-2, pp. 184-199.
  7. SUBRT, O., MARTINEK, P., WEGENER, C. A contribution to advanced extraction methods for static ADC non-linearity. In Proc. IEEE Instrumentation and Measurement Technology Conference Proceedings IMTC. Warsaw (Poland), May 2007, CD.
  8. The Institute of Electrical and Electronics Engineers, Inc.: IEEE Standard for Terminology and Test Methods for Analog-to-Digital Converters, IEEE Std. 1241-2000, New York, December 2000.
  9. SUBRT, O. Application of SI technique in A/D Conversion and its LEMMA-aided design evaluation. Ph.D. Thesis. CTU Prague, Faculty of Electrical Engineering, December 2005.
  10. WEGENER, C., KENNEDY, M. P. Linear model-based error identification and calibration for data converters. In Proc. of Conf. on Design Automation and Test in Europe DATE. Munich (Germany), March 2003, p. 630-635.
  11. MICHAELI, L. Modeling of the Analog-Digital Interfaces. TU Kosice, 2001. ISBN 80-968550-1-8(in Slovak).
  12. STRUHOVSKY, P., SUBRT, O., HOSPODKA, J., MARTINEK, P. Advanced modeling and design evaluation procedure applied to pipelined A/D converter. In Proc. of the 13th Workshop on ADC Modelling and Testing IWADC. Florence (Italy), September 2008.
  13. STRUHOVSKY, P., SUBRT, O., HOSPODKA, J., MARTINEK, P. Developing virtual ADC testing environment in MAPLE. In Proc. of the 10th Workshop on Design and Diagnostics of Electronic Circuits and Systems DDECS. Krakow (Poland), April 2007.

Keywords: Pipelined A/D converter, ADC modeling, design evaluation, integral and differential non-linearity, error determination.

D. K. Upadhyay [references] [full-text] [Download Citations]
Class of Recursive Wideband Digital Differentiators and Integrators

New designs of recursive digital differentiators are obtained by optimizing a general fourth-order recursive digital filter over different Nyquist bands. In addition, another design of recursive digital differentiator is also obtained by optimizing the specified pole-zero locations of existing recursive digital differentiator of second-order system. Further, new designs of recursive digital integrators are obtained by inverting the transfer functions of designed recursive digital differentiators with suitable modifications. Thereafter, the zero-reflection approach is discussed and then applied to improve the phase responses of designed recursive digital differentiators and integrators. The beauty of finally obtained recursive digital differentiators and integrators is that they have nearly linear phase responses over wideband and also provide the choice of suitable recursive digital differentiator and integrator according to the importance of accuracy, bandwidth and the system simplicity.

  1. SKOLNIK, M. I. Introduction to Radar Systems. New York: McGraw-Hill, 1980.
  2. HSUE, C.-W., TSAI, L.-C., CHEN, K. –L. Implementation of firstorder and second-order microwave differentiators. IEEE Transactions on Microwave Theory and Techniques, 2004, vol. 52, no. 5, p. 1443-1447.
  3. SEDRA, A. S., SMITH, K. C. Microelectronic Circuits, USA: Oxford Univ. Press, 2004.
  4. AL-ALAOUI, M. A. A novel differential differentiator. IEEE Trans. Instrumentation Measurements, 1991, vol. 40, p. 826-830.
  5. AL-ALAOUI, M. A. A differential integrator with a built in highfrequency compensation. IEEE Trans. Circuits Syst. I, 1998, vol. 45, no. 5, p. 517-522.
  6. AL-ALAOUI, M. A. Low frequency differentiators and integrators for biomedical and seismic signals. IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., 2001, vol. 48, no. 8, p. 1006-1011.
  7. AL-ALAOUI, M. A. Novel approach to designing digital differentiators. Electron. Lett., 1992, vol. 28, no. 15, p. 1376 to 1378.
  8. AL-ALAOUI, M. A. Novel digital integrator and differentiator. Electron. Lett., 1993, vol. 29, no. 4, p. 376–378.
  9. AL-ALAOUI, M. A. Errata. Electron. Lett., 1993, vol. 29, no. 10, p. 934.
  10. BIHAN, J. L. Novel class of digital integrators and differentiators. Electron. Lett., 1993, vol. 29, no. 11, p. 971-973.
  11. AL-ALAOUI, M. A. Novel IIR differentiator from the Simpson integration rule. IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., 1994, vol. 41, no. 2, p. 186–187.
  12. AL-ALAOUI, M. A. A class of second-order integrators and lowpass differentiators. IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., 1995, vol. 42, no. 4, p. 220–223.
  13. PAPAMARKOS, N., CHAMZAS, C. A new approach for the design of digital integrators. IEEE Trans. Circuits Syst. I, Fundam. Theory Appl., 1996, vol. 43, no. 9, p. 785–791.
  14. AL-ALAOUI, M. A. Novel stable higher order s-to-z transforms. IEEE Trans. Circuits Syst. I, Fundam. Theory and Appl., 2001, vol. 48, no. 11, p. 1326-1329.
  15. AL-ALAOUI, M. A. Al-Alaoui operator and the α-approximation for discretization of analogue systems. Facta Univ. Electr. Eng., 2006, vol. 19, no. 1, p. 143-146.
  16. AL-ALAOUI, M. A. Linear phase low pass IIR digital differentiators. IEEE Trans. Signal Processing, 2007, vol. 55, no. 2, p. 697-706.
  17. AL-ALAOUI, M. A. Al-Alaoui operator and the new transformation polynomials for discretization of analogue systems. Electrical Engineering, 2008, vol. 90, no. 4, p. 455-567.
  18. TSENG, C. C. Closed form design of digital IIR integrators using numerical integration rules and fractional sample delay. IEEE Trans. Circuits Syst. I, Fundam. Theory and Appl., 2007, vol. 54, no. 3, p. 643-655.
  19. TSENG, C. C., LEE, S. L. Digital integrator design using Richardson extrapolation and fractional delay. IEEE Trans. Circuits Syst. I, 2008, vol. 55, no. 8, p. 2300-2309.
  20. NGO, N. Q. A New approach for the design of wideband digital integrator and differentiator. IEEE Transactions on Circuits and Systems—II, 2006, vol. 53, no. 9, p. 936-940.
  21. GUPTA, M., JAIN, M., KUMAR, B. Recursive wideband digital integrator and differentiator. Wiley Int. J. Circ. Theory Appl., 2010, DOI:10.1002/cta.658.
  22. GUPTA, M., JAIN, M., KUMAR, B. Novel class of stable wideband recursive digital integrators and differentiators. IET Signal Process., 2010, vol. 4, no. 5, p. 560-566.
  23. UPADHYAY, D. K. Recursive wideband digital differentiators. Electron. Lett., 2010, vol. 46, no. 25, p. 1661-1662.
  24. AL-ALAOUI, M. A. Class of digital integrators and differentiators. IET Signal Process., 2011, vol. 5, no. 2, p. 251- 260.
  25. UPADHYAY, D. K., SINGH, R. K. Recursive wideband digital differentiator and integrator. Electron. Lett., 2011, vol. 47, no. 11, p. 647-648.
  26. MOLLOVA, G. Compact formulas for least-squares design of digital differentiators. Electron. Lett., 1999, vol. 35, no. 20, p. 1695-1697.
  27. PROAKIS, J. G. Digital Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, 1996.
  28. MITRA, S. K. Digital Signal Processing. 3rd ed. New York: McGraw-Hill, 2006.
  29. KUMAR, B., DUTTA ROY, S. C. Design of efficient FIR digital differentiators and Hilbert transformers for midband frequency ranges. Wiley Int. J. Circ. Theory Appl., 1989, vol. 17, no. 4, p. 483-488.
  30. KUMAR, B., DUTTA ROY, S. C. Maximally linear FIR digital differentiators for high frequencies. IEEE Trans. Circuits and Systems, 1989, vol. 36, no. 4, p. 890-893.
  31. CARLSSON, B. Maximum flat digital differentiator. Electron. Lett., 1991, vol. 27, no. 8, p. 675-677.
  32. SUNDER, S., RAMACHANDRAN, V. Design of equiripple non recursive digital differentiators and Hilbert transformers using a weighted least squares technique. IEEE Trans. Signal Process., 1994, vol. 42, no. 9, p. 2504-2509.
  33. TSENG, C. C. Digital differentiator design using fractional delay filter and limit computation. IEEE Trans. Signal Process., 2005, vol. 52, no. 10, p. 2248-2259.
  34. PEI, S. C., SHYU, J. J. Analytic closed-form matrix for designing higher order digital differentiators using eigen-approach. IEEE Trans. Signal Process., 1996, vol. 44, p. 698-701.
  35. HSUE, C.-W., CHENG, T.-R., CHENG, H.-M., CHAEN, H. -M. A second-order microwave differentiators. IEEE Microwave Wireless Comp. Lett., 2003, vol. 13, no. 3, p. 137-139.
  36. HSUE, C.-W., TSAI, L. -C., TSAI, Y. -H. Time-constant control of microwave integrators using transmission lines. IEEE Trans. Microw. Theory Tech. 2006, vol. 54, no. 3, p. 1043-1047.
  37. HSUE, C.-W., TSAI, L. -C., KAN, S. T. Implementation of a trapezoidal-rule microwave integrator. Microw. and Opt. Tech. Lett., 2006, vol. 48, no. 4, p. 822-825.

Keywords: Digital differentiator, digital integrator, linear phase, recursive, wideband

M. S. Khan, M. Grabner, S. S. Muhammad, M. S. Awan, E. Leitgeb, V. Kvicera, R. Nebuloni [references] [full-text] [Download Citations]
Empirical Relations for Optical Attenuation Prediction from Liquid Water Content of Fog

Simultaneous measurements of the liquid water content (LWC) and optical attenuation have been analyzed to predict optical attenuation caused by fog particles. Attenuation has been measured at two different wavelengths, 830 nm and 1550 nm, across co-located links. Five months measured data have been processed to assess power-law empirical models, which estimate optical attenuation from the LWC. The proposed models are compared with other published models and are demonstrated to perform sufficiently well to predict optical attenuation if the LWC values are available.

  1. AHARONOVICH, M., ARNON, S. Performance improvement of optical wireless communication through fog with a decision feedback equalizer. Journal of Optical Society of America, 2005, vol. 22, no. 8, p. 1646 - 1654.
  2. MUHAMMAD, S. S., FLECKER, B., LEITGEB, E., GEBHART, M. Characterization of fog attenuation in terrestrial free space links. Journal of Optical Engineering, 2007, vol. 46, no. 6, p. 066001.
  3. GRABNER, M., KVICERA, V. The wavelength dependent model of extinction in fog and haze for free space optical communication. Optics Express, 2011, vol. 19, no. 4, p. 3379 - 3386.
  4. WEI, Z. Z., ZHEN-SEN, W. Millimeter-wave attenuation due to fog and clouds. International Journal of Infrared and Millimeter Waves, 2000, vol. 21, no. 10, p. 1607 - 1615.
  5. TONNA, G., VALENTI, C. Optical attenuation coefficients and liquid water content relationship in fog, at seventy four wavelengths from 0.35 to 90 m. Atmospheric Environment, 1983, vol. 17. no. 10, p. 2075 - 2080.
  6. MUHAMMAD, S. S., AWAN, M. S., REHMAN, A. PDF estimation and liquid water content based attenuation modeling for fog in terrestrial FSO links. Radioengineering, 2010, vol. 19, no. 2, p. 228 - 236.
  7. KONTOGEORGAKIS, C. Millimeter through Visible Frequency Waves through Aerosols Particle Modeling, Reflectivity and Attenuation. Master’s thesis. Virginia Polytechnic Institute and State University, 1997.
  8. KIM, I. I., McARTHUR, B., KOREVAAR, E. Comparison of laser beam propagation at 785 and 1550 nm in fog and haze for optical wireless communications. Proc. SPIE, 2001, vol. 4214, p. 26 - 37.
  9. KRUSE, P. W., McGLAUCHLIN, L. D., McQUISTAN, R. B. Elements of infrared technology: Generation, Transmission and Detection. New York: John Wiley and Sons, 1962.
  10. AL NABOULSI, M., SIZUN, H., DE FORNEL, F. Fog attenuation prediction for optical and infrared waves. Optical Engineering, 2004, vol 43, no. 2, p. 319 - 329.
  11. ROBERTS, R. E., SEEKAMP, L. N. Infrared attenuation by aerosols in limited atmospheric visibility: relationship to liquid water content. IDA PAPER P-1394. Institute for Defence Analyses, 1979, p. 1-11.
  12. TONNA, G. Backscattering, extinction, and liquid water content in fog: a detailed study of their relations for use in lidar systems. Applied Optics, 1991, vol. 30, no. 9, p. 1132-1140.
  13. CSURGAI-HORVATH, L., FRIGYES, I. Characterization of Fog by Liquid Water Content for Use in Free Space Optics. In Proceedings of ConTEL. Graz (Austria), 2011, p. 189 - 194.
  14. VASSEUR H., OESTGES, C., VORST, A. V. Influence de la troposph`ere sur les liaisons sans fil aux ondes millim´etriques et optiques. In Propagation E´lectromagne´tique du De´came´trique `a L’angstr¨om, Rennes, 1997 (in French).
  15. AWAN, M. S. Statistical-Dynamical Channel Modeling of Outdoor Optical Wireless Links. PhD thesis. Graz (Austria): TU Graz, 2010.
  16. SHETTLE, E. P. Models of aerosols, clouds, and precipitation for atmospheric propagation studies. In AGARD conference Proceedings. 1989.
  17. TOMASI, C., TAMPIERI, F. Features of the proportionality coefficient in the relationship between visibility and liquid water content in haze and fog. Journal of Atmosphere, 1976, vol. 1, no. 2, p. 61 - 76.
  18. KHAN, M. S., MUHAMMAD, S. S., AWAN, M. S., LEITGEB, E., GRABNER, M., KVICERA, V. Validating relationship between aerosol’s liquid water content and optical attenuation for terrestrial FSO links. In Proceedings of ConTEL. Graz (Austria), 2011, p. 195 - 198.
  19. KHAN, M. S., MUHAMMAD, S. S., AWAN, M. S., KVICERA, V., GRABNER, M., LEITGEB, E. Further results on fog modeling for terrestrial free-space optical links. Optical Engineering, 2012, vol. 51, no. 3. p. 031207
  20. GULTEPE, I., TARDIF, R., MICHAELIDES, S. C., CERMAK, J., BOTT, A., BENDIX, J., MULLER, M. D., PAGOWSKI, M., HANSEN, B., ELLROD, G., JACOBS, W., TOTH, G., COBER, S. G. Fog research: A review of past achievements and future perspectives. Pure and Applied Geophysics, 2007, vol. 164, p. 1121 - 1159.
  21. CHYLEK , P. Extinction and liquid water content of fogs and clouds. Journal of Atmospheric Sciences, 1978, vol. 35, no. 2, p. 296 - 300.

Keywords: Free-Space optical links, Liquid water content, Optical attenuation, Drop size distribution, Aerosols.

J. Dedkova, K. Ostanina [references] [full-text] [Download Citations]
Two-dimensional Tissue Image Reconstruction Based on Magnetic Field Data

This paper introduces new possibilities within two-dimensional reconstruction of internal conductivity distribution. In addition to the electric field inside the given object, the injected current causes a magnetic field which can be measured either outside the object by means of a Hall probe or inside the object through magnetic resonance imaging. The Magnetic Resonance method, together with Electrical impedance tomography (MREIT), is well known as a bio-imaging modality providing cross-sectional conductivity images with a good spatial resolution from the measurements of internal magnetic flux density produced by externally injected currents. A new algorithm for the conductivity reconstruction, which utilizes the internal current information with respect to corresponding boundary conditions and the external magnetic field, was developed. A series of computer simulations has been conducted to assess the performance of the proposed algorithm within the process of estimating electrical conductivity changes in the lungs, heart, and brain tissues captured in two-dimensional piecewise homogeneous chest and head models. The reconstructed conductivity distribution using the proposed method is compared with that using a conventional method based on Electrical Impedance Tomography (EIT). The acquired experience is discussed and the direction of further research is proposed.

  1. HOLDER, D. S. Electrical Impedance Tomography. Philadelphia: IOP Publishing, 2005.
  2. SIKORA, J., WOJTOWICZ, S. Industrial and Biological Tomography. Theoretical Basis and Applications. Warsaw: Electrotechnical Institute, 2010.
  3. SANKOWSKI, D., SIKORA, J. Electrical Capacitance Tomography. Theoretical Basis and Applications. Warsaw: Electrotechnical Institute, 2010.
  4. CRILE, G. W., HOSMER, H. R., ROWLAND, A. F. The electrical conductivity of animal tissue under normal and pathological conditions. American Journal of Physiology, 1922, vol. 60, no. 1, p. 59 - 106.
  5. MEYER, A. W. Method for detecting brain tumors in the trepanation by electrical resistance measurement (Methode zum Auffinden von Hirntumoren bei der Trepanation durch elektrische Widerstandsmessung). Zentralblatt fur Chirurgie, 1921, no. 48, p. 1824 – 1826 (in German).
  6. FOSTER, K. R., SCHWAN, H. P. Dielectric properties of tissues and biological materials: a critical review. Critical Reviews in Biomedical Engineering, 1989, vol. 17, no. 1, p. 25 - 104.
  7. GEDDES, L. A., BAKER, L. E. The specific resistance of biological materials - a compendium of data for the biomedical engineer and physiologist. Medical and Biological Engineering and Computing, 1967, vol. 5, no. 3, p. 271 - 293.
  8. LAW, S. K. Thickness and resistivity variations over the upper surface of the human skull. Brain Topography, 1993, vol. 6, no. 2, p. 99 - 109.
  9. SEO, J. K., KWON, O., WOO, E. J. Magnetic resonance electrical impedance measurement tomography (MREIT): conductivity and current density imaging. Journal of Physics: Conference Series, 2005, vol. 12, p. 140 - 155.
  10. JEON, K., LEE, C.-O., WOO, E. J., KIM, H. J., SEO, J. K. MREIT conductivity imaging based on the local harmonic Bz algorithm: animal experiments. Journal of Physics: Conference Series, 2010, vol. 224, no. 1, p. 1 - 4.
  11. LEE, T. H., NAM, H. S., LEE, M. G., KIM, Y. J., WOO, E. J., KWON, O. I. Reconstruction of conductivity using the dual-loop method with one injection current in MREIT. Physics in Medicine and Biology, 2010, vol. 55, no. 24, p. 7523 - 7539.
  12. KWON, O., LEE, J. Y., YOON, J. R. Equipotential line method for magnetic resonance electrical impedance tomography. Inverse Problems, 2002, vol. 18, p. 1-12.
  13. ZHANG, X., YAN, D., ZHU, S., HE, B. Noninvasive imaging of head-brain conductivity profiles. IEEE Engineering in Medicine and Biology Magazine, 2008, vol. 27, no. 5, p. 78 - 83.
  14. MIKLAVCIC, D., PAVSELI, N., HART, F. X. Electric Properties of Tissues. Wiley Encyclopedia of Biomedical Engineering. John Wiley & Sons, 2006.
  15. DEDKOVA, J., OSTANINA, K. Implementation of fuzzy filters in EIT image reconstructions. Acta Technica CSAV, 2011, vol. 56, no. 2, p. 207 - 216.
  16. GHANNAM, M. M., EL-GEBALY, R. H., GABER, M. H., ALI, F. F. Inhibition of Ehrlich tumor growth in mice by electric interference therapy (in vivo studies). Electromagnetic Biology and Medicine, 2002, vol. 21, no. 3, p. 255 - 268.

Keywords: Impedance tomography, magnetic resonance, image reconstruction, inverse problem, finite element method

A. J. Sporka, O. Polacek, J. Havlik [references] [full-text] [Download Citations]
Segmentation of Speech and Humming in Vocal Input

Non-verbal vocal interaction (NVVI) is an interaction method in which sounds other than speech produced by a human are used, such as humming. NVVI complements traditional speech recognition systems with continuous control. In order to combine the two approaches (e.g. "volume up, mmm") it is necessary to perform a speech/NVVI segmentation of the input sound signal. This paper presents two novel methods of speech and humming segmentation. The first method is based on classification of MFCC and RMS parameters using a neural network (MFCC method), while the other method computes volume changes in the signal (IAC method). The two methods are compared using a corpus collected from 13 speakers. The results indicate that the MFCC method outperforms IAC in terms of accuracy, precision, and recall.

  1. SPORKA, A. J., KURNIAWAN, S. H., SLAV´IK, P. Whistling user interface (U3I). In 8th ERCIM International Workshop “User Interfaces For All”. Vienna (Austria), 2004, p. 472 - 478.
  2. IGARASHI, T., HUGHES, J. F. Voice as sound: using non-verbal voice input for interactive control. In Proceedings of the 14th Annual ACM Symposium on User Interface Software and Technology. New York (USA), 2001, p. 155 - 156.
  3. MARTIN, A., CHARLET, D., MAUUARY, L. Robust speech/nonspeech detection using LDA applied to MFCC. In Proceedings of the 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Salt Lake City (USA), 2001, p. 237 - 240.
  4. SHAFRAN, I., ROSE, R. Robust speech detection and segmentation for real-time ASR applications. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing. Hong Kong, 2003, 432 - 435.
  5. ZIBERT, J., PAVESIC´ , N., MIHELICˇ , F. Speech/non-speech segmentation based on phoneme recognition features. EURASIP Journal on Applied Signal Processing, 2006, vol. 2006, p. 47 - 47.
  6. SCHEIRER, E., SLANEY, M. Construction and evaluation of a robust multifeature speech/music discriminator. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing. Munich (Germany), 1997, p. 1331 - 1334.
  7. KIM, B.-W., CHOI, D.-L., LEE, Y.-J. Speech/music discrimination using Mel-Cepstrum modulation energy. Lecture Notes in Computer Science, 2007, vol. 4629, p. 406 - 414.
  8. SPORKA, A. J., Zˇ IKOVSKY´ , P., SLAVI´K, P. Explicative document reading controlled by non-speech audio gestures. Lecture Notes in Computer Science, 2006, vol. 4188, p. 695 - 702.
  9. SPORKA, A. J., KURNIAWAN, S. H., SLAV´IK, P. Non-speech operated emulation of keyboard. In Cambridge Workshop on Universal Access and Assistive Technology, CWUAAT 2006: Designing Accessible Technology. Cambridge (UK), 2006, 145 - 154.
  10. SPORKA, A. J., KURNIAWAN, S. H., MAHMUD, M., SLAV´IK, P. Non-speech input and speech recognition for real-time control of computer games. In Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility. New York (USA), 2006, p. 213 - 220.
  11. PRUTHI, T., CHHATPAR, S., NGIA, L., BROWN, J., HARRIS, J. Method for Non-Speech Vocalization to Control UGVs using Humming. Technical manual. [Online] Available at: http://www.think-amove. com/pdfs/AUVSIJune2008.pdf.
  12. HACIHABIBOGLU, H., CANAGARAJAH, C. Musical instrument recognition with wavelet envelopes. In Proceedings of Forum Acusticum. Sevilla (Spain), 2002.
  13. TINDALE, A., KAPUR, A., FUJINAGA, I. Towards timbre recognition of percussive sounds. In Proceedings of International Computer Music Conference. Miami (USA), 2004.
  14. FRAGOULIS, D., AVARITSIOTIS, J., PAPAODYSSEUS, C. Timbre recognition of single notes using an ARTMAP neural network. In Proceedings of the 6th IEEE International Conference on Electronics, Circuits and Systems. Washington DC (USA), 1999, p. 1009 - 1012.
  15. BILMES, J. A., LI, X. et al. The vocal joystick: a voice-based human-computer interface for individuals with motor impairments. In Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing. Morristown (NJ, USA), 2005, p. 995 - 1002.
  16. BRØNDSTED, T., AUGUSTENSEN, S., FISKER, B., HANSEN, C., KLITGAARD, J., NIELSEN, L., RASMUSSEN, T. A system for recognition of hummed tunes. In Proceedings of the COST G-6 Conference on Digital Audio Effects. Limerick (Ireland), 2001.
  17. ZHU, Y., SHASHA, D., ZHAO, X. Query by humming: In action with its technology revealed. In Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data. New York (USA), 2003, p. 675 - 675.
  18. LU, G., HANKINSON, T. A technique towards automatic audio classification and retrieval. In Proceedings of the 4th International Conference on Signal Processing. Beijing (China), 1998, p. 1142 - 1145.
  19. DAVIS, S., MERMELSTEIN, P. Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1980, vol. 28, no. 4, p. 357 - 366.
  20. PENG, H., LONG, F., DING, C. Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and minredundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, vol. 27, no. 9, p. 1226 - 1238.

Keywords: Non-verbal vocal interaction, Speech, MFCC, Neural network, Segmentation, Multi-layer perceptron