JOURNAL ARTICLE

Equal Gain Combining for Cooperative Spectrum Sensing in Cognitive Radio Networks

Doha HamzaSonia Aı̈ssaGhassane Aniba

Year: 2014 Journal:   IEEE Transactions on Wireless Communications Vol: 13 (8)Pages: 4334-4345   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Sensing with equal gain combining (SEGC), a novel cooperative spectrum sensing technique for cognitive radio networks, is proposed. Cognitive radios simultaneously transmit their sensing results to the fusion center (FC) over multipath fading reporting channels. The cognitive radios estimate the phases of the reporting channels and use those estimates for coherent combining of the sensing results at the FC. A global decision is made at the FC by comparing the received signal with a threshold. We obtain the global detection probabilities and secondary throughput exactly through a moment generating function approach. We verify our solution via system simulation and demonstrate that the Chernoff bound and central limit theory approximation are not tight. The cases of hard sensing and soft sensing are considered and we provide examples in which hard sensing is advantageous to soft sensing. We contrast the performance of SEGC with maximum ratio combining of the sensors' results and provide examples where the former is superior. Furthermore, we evaluate the performance of SEGC against existing orthogonal reporting techniques such as time division multiple access (TDMA). SEGC performance always dominates that of TDMA in terms of secondary throughput. We also study the impact of phase and synchronization errors and demonstrate the robustness of the SEGC technique against such imperfections. © 2002-2012 IEEE.

Keywords:
Cognitive radio Computer science Multipath propagation Robustness (evolution) Time division multiple access Fading Fusion center Algorithm Electronic engineering Telecommunications Computer network Topology (electrical circuits) Wireless Channel (broadcasting) Decoding methods Electrical engineering Engineering

Metrics

79
Cited By
10.66
FWCI (Field Weighted Citation Impact)
29
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cognitive Radio Networks and Spectrum Sensing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Distributed Sensor Networks and Detection Algorithms
Physical Sciences →  Computer Science →  Computer Networks and Communications
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
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