2014/04/15 by Tadilo Endeshaw Bogale, Bogale, Tadilo Endeshaw, Luc Vandendorpe +3
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Applications (stat.AP) #Cognitive Radio Networks and Spectrum Sensing #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences
paper · pdf · doi:10.48550/arxiv.1404.4006
openalex publication_date 2014/04/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes novel spectrum sensing algorithm, and examines the\nsensing throughput tradeoff for cognitive radio (CR) networks under noise\nvariance uncertainty. It is assumed that there are one white sub-band, and one\ntarget sub-band which is either white or non-white. Under this assumption,\nfirst we propose a novel generalized energy detector (GED) for examining the\ntarget sub-band by exploiting the noise information of the white sub-band,\nthen, we study the tradeoff between the sensing time and achievable throughput\nof the CR network. To study this tradeoff, we consider the sensing time\noptimization for maximizing the throughput of the CR network while\nappropriately protecting the primary network. The sensing time is optimized by\nutilizing the derived detection and false alarm probabilities of the GED. The\nproposed GED does not suffer from signal to noise ratio (SNR) wall (i.e.,\nrobust against noise variance uncertainty) and outperforms the existing signal\ndetectors. Moreover, the relationship between the proposed GED and conventional\nenergy detector (CED) is quantified analytically. We show that the optimal\nsensing times with perfect and imperfect noise variances are not the same. In\nparticular, when the frame duration is 2s, and SNR is -20dB, and each of the\nbandwidths of the white and target sub-bands is 6MHz, the optimal sensing times\nare 28.5ms and 50.6ms with perfect and imperfect noise variances, respectively.\n