The increasing interest for wireless communication services and scarcity of
radio spectrum resources have created the need for a more flexible and efficient
usage of the radio frequency bands. Cognitive Radio (CR) emerges as an
important trend for a solution to this problem. Spectrum sensing is a crucial
function in a CR system. Cooperative spectrum sensing can overcome fading
and shadowing effects, and hence increase the reliability of primary user detection.
In this paper we consider a system model of a dedicated detect-andforward
wireless sensor network (DetF WSN) for cooperative spectrum sensing
with k-out-of-n decision fusion in the presence of reporting channels errors.
Using this model we consider the design of a spatial reuse media access
control (MAC) protocol based on TDMA/OFDMA to resolve conflicts and
conserve resources for intra-WSN communication. The influence of the MAC
protocol on spectrum sensing performance of the WSN is a key consideration.
Two design approaches, using greedy and adaptive simulated annealing
(ASA) algorithms, are considered in detail. Performance results assuming a
grid network in a Rician fading environment are presented for the two design
approaches.
References
[1]
Letaief, K. and Zhang, W. (2009) Cooperative Communications for Cognitive Radio Networks. Proceedings of the IEEE, 97, 878-893.
https://doi.org/10.1109/JPROC.2009.2015716
[2]
Akyildiz, I.F., Lee, W.-Y., Vuran, M.C. and Mohanty, S. (2006) NeXt Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey. Computer Networks, 50, 2127-2159. https://doi.org/10.1016/j.comnet.2006.05.001
[3]
Stevenson, C.R., et al. (2009) IEEE 802.22: The First Cognitive Radio Wireless Regional Area Network Standard. IEEE Communications Magazine, 47, 130-138.
https://doi.org/10.1109/MCOM.2009.4752688
[4]
Abinader, F., Almeida, E.P., Chaves, F.S., Cavalcante, A.M., Vieira, R.D., Paiva, R.C., Sobrinho, A.M., Choudhury, S., Tuomaala, E., Doppler K., et al. (2014) Enabling the Coexistence of LTE and Wi-Fi in Unlicensed Bands. Communications Magazine, IEEE, 52, 54-61. https://doi.org/10.1109/MCOM.2014.6957143
[5]
Zhang, H., Chu, X., Guo, W. and Wang, S. (2015) Coexistence of Wi-Fi and Heterogeneous Small Cell Networks Sharing Unlicensed Spectrum. Communications Magazine, IEEE, 53, 158-164. https://doi.org/10.1109/MCOM.2015.7060498
[6]
Tandra, R. and Sahai, A. (2008) SNR Walls for Signal Detection. IEEE Journal of Selected Topics in Signal Processing, 2, 4-17.
https://doi.org/10.1109/JSTSP.2007.914879
[7]
Duan, D., Yang, L. and Principe, J.C. (2010) Cooperative Diversity of Spectrum Sensing for Cognitive Radio Systems. IEEE Transactions on Signal Processing, 58, 3218-3227. https://doi.org/10.1109/TSP.2010.2044612
[8]
Atapattu, S., Tellambura, C. and Jiang, H. (2011) Energy Detection Based Cooperative Spectrum Sensing in Cognitive Radio Networks. IEEE Transactions on Wireless Communications, 10, 1232-1241. https://doi.org/10.1109/TWC.2011.012411.100611
[9]
Mishra, S.M., Sahai, A. and Brodersen, R. (2006) Cooperative Sensing among Cognitive Radios. 2006 IEEE International Conference on Communications, Istanbul, 11-15 June 2006, 1658-1664. https://doi.org/10.1109/ICC.2006.254957
[10]
Han, Z., Fan, R. and Jiang, H. (2009) Replacement of Spectrum Sensing in Cognitive Radio. IEEE Transactions on Wireless Communications, 8, 2819-2826.
https://doi.org/10.1109/TWC.2009.080603
[11]
Shankar, S.N., Cordeiro, C. and Challapali, K. (2005) Spectrum Agile Radios: Utilization and Sensing Architectures. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks,Baltimore, 8-11 November 2005, 160-169.
[12]
Sahai, A., Mishra, S.M., Tandra, R. and Hoven, N. (2006) Sensing for Communication: The Case of Cognitive Radio. Allerton Conference on Communication, Control, and Computing, Allerton Park, Monticello, 27-29 September 2006, 1035-1037.
[13]
Akyildiz, I.F., Lo, B.F. and Balakrishnan, R. (2011) Cooperative Spectrum Sensing in Cognitive Radio Networks: A Survey. Physical Communication, 4, 40-62.
https://doi.org/10.1016/j.phycom.2010.12.003
[14]
Bachir, A., Dohler, M., Watteyne, T. and Leung, K.K. (2010) MAC Essentials for Wireless Sensor Networks. IEEE Communications Surveys and Tutorials, 12, 222- 248. https://doi.org/10.1109/SURV.2010.020510.00058
[15]
Demirkol, I., Ersoy, C. and Alagoz, F. (2006) MAC Protocols for Wireless Sensor Networks: A Survey. IEEE Communications Magazine, 6, 115-121.
https://doi.org/10.1109/MCOM.2006.1632658
[16]
Chaudhari, S., Lunden, J., Koivunen, V. and Poor, H.V. (2012) Cooperative sensing with Imperfect Reporting Channels: Hard Decisions or Soft Decisions? IEEE Transactions on Signal Processing, 60, 18-28.
https://doi.org/10.1109/TSP.2011.2170978
[17]
Goldsmith, A. (2005) Wireless Communications. Cambridge University Press, New York. https://doi.org/10.1017/CBO9780511841224
[18]
Simon, M.K. and Alouini, M.-S. (2005) Digital Communication over Fading Channels. John Wiley & Sons, Hoboken.
[19]
Iyer, A., Rosenberg, C. and Karnik, A. (2009) What Is the Right Model for Wireless Channel Interference. IEEE Transactions on Wireless Communications, 8, 2662- 2671. https://doi.org/10.1109/twc.2009.080720
[20]
Ghasemi, A. and Sousa, E.S. (2005) Collaborative Spectrum Sensing for Opportunistic Access in Fading Environments. First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, Baltimore, 8-11 November 2005, 131-136.
[21]
Digham, F.F., Alouini, M.-S. and Simon, M.K. (2003) On the Energy Detection of Unknown Signals over Fading Channels. IEEE International Conference on Communications,, 5, 3575-3579. https://doi.org/10.1109/icc.2003.1204119
[22]
Varshney, P.K. (1997) Distributed Detection and Data Fusion. In: Burrus, C., Ed., Springer, New York. https://doi.org/10.1007/978-1-4612-1904-0
[23]
Hong, Y. (2013) On Computing the Distribution Function for the Poisson Binomial Distribution. Computational Statistics and Data Analysis, 59, 41-51.
https://doi.org/10.1016/j.csda.2012.10.006
[24]
Fernandez, M. and Williams, S. (2010) Closed-Form Expression for the Poisson-Binomial Probability Density Function. Aerospace and Electronic Systems, IEEE Transactions on, 46, 803-817. https://doi.org/10.1109/TAES.2010.5461658
[25]
Cidon, I. and Sidi, M. (1989) Distributed Assignment Algorithm for Multihop Packet Radio Networks. IEEE Transactions on Computers, 38, 1353-1361.
https://doi.org/10.1109/12.35830
[26]
Sagduyu, Y. and Ephremides, A. (2004) The Problem of Medium Access Control in Wireless Sensor Networks. IEEE Wireless Communications, 11, 44-53.
https://doi.org/10.1109/MWC.2004.1368896
[27]
Ausiello, G., Crescenzi, P., Gambosi, G., Kann, V., Marchetti-Spaccamela, A. and Protasi, M. (2012) Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties. Springer Science & Business Media, Berlin.
[28]
Maniezzo, V. and Carbonaro, A. (2000) An Ants Heuristic for the Frequency Assignment Problem. Future Generation Computer Systems, 16, 927-935.
https://doi.org/10.1016/S0167-739X(00)00046-7
[29]
Krumke, S.O., Marathe, M.V. and Ravi, S. (2001) Models and Approximation Algorithms for Channel Assignment in Radio Networks. Wireless Networks, 7, 575-584.
https://doi.org/10.1023/A:1012311216333
[30]
ElBatt, T. and Ephremides, A. (2004) Joint Scheduling and Power Control for Wireless Ad Hoc Networks. IEEE Transactions on Wireless Communications, 3, 74-85. https://doi.org/10.1109/TWC.2003.819032
[31]
Alicherry, M., Bhatia, R., and Li, L.E. (2005) Joint Channel Assignment and Routing for Throughput Optimization in Multi-Radio Wireless Mesh Networks. Proceedings of the 11th Annual International Conference on Mobile Computing and Networking, 28 August-2 September, 2005, 58-72.
https://doi.org/10.1145/1080829.1080836
[32]
Subramanian, A.P., Gupta, H., Das, S.R. and Cao, J. (2008) Minimum interference Channel Assignment in Multiradio Wireless Mesh Networks. Mobile Computing, IEEE Transactions on, 7, 1459-1473. https://doi.org/10.1109/TMC.2008.70
[33]
Papadimitriou, C.H. and Steiglitz, K. (1998) Combinatorial Optimization: Algorithms and Complexity. Courier Corporation, North Chelmsford.
[34]
Blum, C. and Roli, A. (2003) Metaheuristics in Combinatorial Optimization: Overview and Conceptual Comparison. ACM Computing Surveys (CSUR), 35, 268-308.
https://doi.org/10.1145/937503.937505
[35]
Brelaz, D. (1979) New Methods to Color the Vertices of a Graph. Communications of the ACM, 22, 251-256. https://doi.org/10.1145/359094.359101
Avanthay, C., Hertz, A. and Zufferey, N. (2003) A Variable Neighborhood Search for Graph Coloring. European Journal of Operational Research, 151, 379-388.
https://doi.org/10.1016/S0377-2217(02)00832-9
[38]
Ingber, L., Petraglia, A., Petraglia, M.R., Machado, M.A.S., et al. (2012) Adaptive Simulated Annealing. Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing. Springer, New York, 33-62.
[39]
Bertsimas, D., Tsitsiklis, J., et al. (1993) Simulated Annealing. Statistical Science, 8, 10-15. https://doi.org/10.1214/ss/1177011077
[40]
Szu, H. and Hartley, R. (1987) Fast Simulated Annealing. Physics Letters A, 122, 157-162. https://doi.org/10.1016/0375-9601(87)90796-1
[41]
Baum, D.S., Hansen, J. and Salo, J. (2005) An Interim Channel Model for Beyond- 3G Systems: Extending the 3GPP Spatial Channel Model (SCM). Vehicular Technology Conference (spring), 5, 3132-3136.
https://doi.org/10.1109/vetecs.2005.1543924
[42]
Unnikrishnan, J. and Veeravalli, V.V. (2008) Cooperative Sensing for Primary Detection in Cognitive Radio. IEEE Journal of Selected Topics in Signal Processing, 2, 18-27.
https://doi.org/10.1109/JSTSP.2007.914880
[43]
Fertin, G., Godard, E. and Raspaud, A. (2003) Acyclic and K-Distance Coloring of the Grid. Information Processing Letters, 87, 51-58.
https://doi.org/10.1016/S0020-0190(03)00232-1
[44]
Kuo, W. and Zuo, M.J. (2003) Optimal reliability Modeling: Principles and Applications, John Wiley & Sons, Hoboken.