Spectrum Sensing For Cognitive Radios Through Differential Entropy

EAI Endorsed Transactions on Cognitive Communications

H. N. Shankar¹  R. Muralishankar²  Sanjeev Gurugopinath³ 

[1] Department of Electrical and Electronics Engineering, CMR Institute of Technology, Bengaluru 560037.;Department of Electronics and Communication Engineering, CMR Institute of Technology, Bengaluru 560037. [e-mail];Department of Electronics and Communication Engineering, PES University, Bengaluru 560085.;

关键词: Spectrum sensing;    goodness-of-fit;    differential entropy;    maximum entropy principle;    non-Gaussian noise.;   

DOI  :  10.4108/eai.5-4-2016.151147

来源: DOAJ

【 摘 要 】

In this work, we present a novel Goodness-of-Fit Test driven by differential entropy for spectrum sensing in cognitive radios, under three different noise models – Gaussian, Laplacian and mixture of Gaussians. We analyze the proposed detector under Gaussian noise which models the worst-case. We then analyze by considering the Laplacian noise process which has tails heavier than that of the Gaussian. We generalize the analysis considering the noise to be a mixture of Gaussians, which is often the case with noise and interference in communication systems. We analyze the performance under each of these cases for a large class of practically relevant fading channel models and primary signal models, with emphasis on low Signal-to-Noise ratio regimes. Towards this end, we derive closed form expressions for the distribution of the test statistic under the null hypothesis and the detection threshold that satisfies a constraint on the probability of false-alarm. Through Monte Carlo simulations, we demonstrate that our detection strategy outperforms an existing spectrum sensing technique based on order statistics.

【 授权许可】

Unknown