Novel Multitaper spectrum optimization technique for Cooperative Spectrum Sensing in Cognitive Radio Networks

Recent years have seen a huge increase in the use of wireless systems and huge applicability of these devices has made their presence inevitable. An exclusive assignment of the radio spectrum allows less flexibility to use the vacant bands, thereby causing under utilization of the available resources. For the deployment of new services it has become increasingly important that secondary users use the whites spaces without affecting the security of primary users. Spectrum utilization can be considerably increased with dynamic spectrum utilization methods. In this paper we propose multitaper method for spectral estimation using Slepian Sequences to generate an optimal approximation for estimation of wide band signals. Detection of the holes in spectrum with efficient energy detection algorithm has been studied for decades to optimize the performance of the system by evaluation appropriate voting rule for optimal threshold. However this traditional approach faces challenges in detection of primary and secondary users in presence of noise. Our work proposes a novel technique to reduce the number of the cognitive radios for a specified error bound in a vast noisy environment. The traditional periodogram technique used in energy detection algorithm has been studied and compared with the proposed novel multitaper spectrum sensing module to prove the efficacy of the proposed system. Comparisons have been carried out on the basis of variation of threshold, SNR, probability of detection and probability of false alarm. The extensive experimentation done in MATLAB prove the efficacy and credibility of the proposed work.