Abstract
In cognitive radio technology, spectrum sensing enables users to sense the environment and find spectrum holes. Cooperative sensing is a good idea for reliable detection of primary users in shadowed environments. In this study, spatial spectral joint detection with some constraints that keep the interference at the primary user below a suitable level is considered as the optimization problem for collaborative sensing. Convex optimization is able to obtain near-optimal solutions because of the non-convexity nature of the optimization problem. In this paper, we use artificial immune system (based on the clonal selection theory) to obtain the optimal solutions without any reformulations or mathematical costs. Numerical results show that our proposed algorithm outperforms the genetic algorithm used in the previous works.
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References
Federal Communication Commission (2002) Spectrum Policy Task Force, Rep. ET Docket no. 02-135
Mitola J, Maguire GQ (1999) Cognitive radio: making software radios more personal. IEEE Pers Commun 6:13–18
Zhang W, Letaief KB (2008) Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks. IEEE Trans Wireless Commun 7(12):4761–4766
Urkowitz H (1967) Energy detection of unknown deterministic signals. Proc IEEE 55(4):523–531
Kay SM (1998) Fundamental of statistical signal processing: detection theory. Prentice-Hall, Englewood Cliffs
Enserink S, Cochran D (1994) A cyclostationary feature detector. In Proc, 28th Asilomar Conf. Signals, Syst. Comput., Pacific Grove, CA, vol, 2, pp. 806–810
Sahaie A, Cabric D (2005) A tutorial on spectrum sensing: fundamental limits and practical challenges. In Proc. IEEE Symp. New Frontiers Dynamic Spectrum Access Networks (DySPAN), Baltimore, MD
Tian Z, Giannakis GB (2006) A wavelet approach to wideband spectrum sensing for cognitive radio networks. In Proc. 1st Int. Conf. Cognitive Radio Oriented Wireless Networks Communication (CrownCom), Mykonos Island, Greece, pp. 1–5
Hur Y, Park J, Woo W, Lim K, Lee C-H, Kim HS, Laskar J (2006) A wideband analog multi-resolution spectrum sensing (MRSS) technique for cognitive radio (CR) systems. In Proc. IEEE Int. Symp. Circuits Systems (ISCAS), Island of Kos, Greece, pp. 4090–4093
Quan Z, Cui S, Sayed A (2009) Optimal multiban joint detection for spectrum sensing in cognitive radio networks. IEEE Trans Sig Process 57(3):1128–1140
Sanna M, Murroni M (2011) Optimization of non-convex multiband cooperative sensing with genetic algorithms. IEEE J Sel Top Sig Process 5(1):87–96
Goldsmith A (2006) Wireless communication. Cambridge University Press, Cambridge
de Castro LN, Von Zoben FJ (2002) Learning and optimization using the clonal selection principle. IEEE Trans Evol Comput 6(3):239–251
Dasgupta D, Fernando L (2009) Immuonological computations. CRC Press, Boca Raton
Joines J, Honck C (1994) On the use of non stationary penalty functions to solve nonlinear constrained optimization problems with GA. in Proc. Congr. Evol. Comput., Orlando, FL, pp. 579–584
Tessema B, Yen G (2009) An adaptive penalty formulation for constrained evolutionary optimization. IEEE Trans Syst Man Cybern 39(3):565–578
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Saeedzarandi, M., Azmi, P. Cooperative multiband joint detection in cognitive radio networks using artificial immune system. Ann. Telecommun. 68, 239–246 (2013). https://doi.org/10.1007/s12243-012-0318-7
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DOI: https://doi.org/10.1007/s12243-012-0318-7