Enhanced energy detection based spectrum sensing in cognitive radio networks using Random Matrix Theory
|Hu, Yim Fun
|Noras, James M.
|Ahmed A, Hu YF and Noras JM (2014) Noise Variance Estimation for Spectrum Sensing in Cognitive Radio Networks. Aasri Conference on Circuit and Signal Processing (Csp 2014) 23-25 Jul 2014, Manchester, UK: 37-43.
|Opportunistic secondary usage of underutilised radio spectrum is currently of great interest and the use of TV White Spaces (TVWS) has been considered for Long Term Evolution (LTE) broadband services. However, wireless microphones operating in TV bands pose a challenge to TVWS opportunistic access. Efficient and proactive spectrum sensing could prevent harmful interference between collocated devices, but existing spectrum sensing schemes such as energy detection and schemes based on Random Matrix Theory (RMT) have performance limitations. We propose a new blind spectrum sensing scheme with higher performance based on RMT supported by a new formula for the estimation of noise variance. The performance of the proposed scheme has been evaluated through extensive simulations on wireless microphone signals. The proposed scheme has also been compared to energy detection schemes, and shows higher performance in terms of the probability of false alarm (Pfa) and probability of detection (Pd).
|White space; Spectrum sensing; Cognitive radio networks; Eigen space analysis; Random matrix theory
|Enhanced energy detection based spectrum sensing in cognitive radio networks using Random Matrix Theory
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