Multi-slot based spectrum sensing with improved energy detector for cognitive radio network in presence of Rayleigh fading

In this paper, the performance of multi-slot based spectrum sensing is investigated in a cooperative scenario where each cognitive radio (CR) user is equipped with an improved energy detector (IED). Two levels of fusion are employed: (i) sub-local decisions obtained in multiple mini slots are combined using OR logic fusion at a CR to obtain a local decision (ii) local decisions from CRs are combined using Majority logic fusion at FC to obtain final decision about the presence of PU. Both the sensing channel (S-channel) and reporting channel (R-channel) are assumed to be Rayleigh faded. Each CR sends its local decision over R-channel to FC after BPSK modulation. The performance of the cooperative spectrum sensing (CSS) using multi-slot and IED is assessed in terms of detection probability and false alarm probability. Furthermore, throughput of a CR is also evaluated under the proposed spectrum sensing scheme. Novel analytical expressions for the detection performance are developed. Performance of multi-slot based sensing is also compared with spectrum sensing without slotted sensing time. Impact of several sensing parameters such as sensing threshold, number of mini-slot, sensing channel SNR (SSNR), reporting channel SNR (RSNR) and IED parameters (p) on the detection performance of CR is indicated. The impact of multi-slot and IED parameter on throughput is also investigated.

[1]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[2]  Yonghong Zeng,et al.  Sensing-Throughput Tradeoff for Cognitive Radio Networks , 2008, IEEE Trans. Wirel. Commun..

[3]  Mohamed-Slim Alouini,et al.  On the Energy Detection of Unknown Signals Over Fading Channels , 2007, IEEE Transactions on Communications.

[4]  Tao Jiang,et al.  Novel multiple slots energy detection for spectrum sensing in cognitive radio networks , 2009, 2009 15th Asia-Pacific Conference on Communications.

[5]  Ian F. Akyildiz,et al.  Cooperative spectrum sensing in cognitive radio networks: A survey , 2011, Phys. Commun..

[6]  Yunfei Chen,et al.  Improved energy detector for random signals in gaussian noise , 2010, IEEE Transactions on Wireless Communications.

[7]  I. S. Gradshteyn,et al.  Table of Integrals, Series, and Products , 1976 .

[8]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[9]  Ranjan K. Mallik,et al.  Cooperative spectrum sensing with an improved energy detector in cognitive radio network , 2011, 2011 National Conference on Communications (NCC).

[10]  Tao Jiang,et al.  Multi-slot spectrum sensing with backward SPRT in cognitive radio networks , 2009, 2009 International Conference on Wireless Communications & Signal Processing.

[11]  Friedrich Jondral,et al.  Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency , 2004, IEEE Communications Magazine.

[12]  Ananthram Swami,et al.  Distributed Spectrum Sensing and Access in Cognitive Radio Networks With Energy Constraint , 2009, IEEE Transactions on Signal Processing.

[13]  Srinivas Nallagonda,et al.  Cooperative spectrum sensing with censoring of cognitive radios in Rayleigh fading under majority logic fusion , 2013, 2013 National Conference on Communications (NCC).

[14]  Arun Pachai Kannu,et al.  Throughput Optimal Multi-Slot Sensing Procedure for a Cognitive Radio , 2013, IEEE Communications Letters.