Optimizing Capacity-Throughput Tradeoff for Enhanced Spectrum Sensing in CSS Based Cognitive Home Area Network

This work considers the application of cooperative spectrum sensing (CSS) in a Home Area Network (HAN) operating in a cognitive radio (CR) environment. Here, first of all, the effect of optimal number of secondary users on error function for cooperative communication is analyzed. Secondly, the joint effects of throughput and error function optimization on the number of secondary users for the available voting rules have been observed. Thirdly, a new voting rule has been proposed by modifying the capacity and throughput parameters of the channel for efficient communication in a HAN. Finally, the performance of the proposed model has been evaluated and compared with the existing voting rules on the basis of number of Secondary Users, minimum and maximum error threshold, channel capacity, and channel throughput.

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