Sensing-Throughput analysis in NOMA-based CR Network

TL;DR

This paper analyzes the throughput of NOMA-based cognitive radio networks employing SWIPT, comparing perfect and imperfect sensing scenarios, and introduces an optimization algorithm for sensing time to maximize throughput.

Contribution

It develops a golden selection search algorithm for optimal sensing time in NOMA-CR networks with SWIPT, considering both perfect and imperfect sensing conditions.

Findings

Optimal sensing time improves throughput significantly.

Imperfect sensing reduces achievable throughput.

The proposed algorithm effectively maximizes network throughput.

Abstract

The Cognitive Radio (CR) network provides the solution to the spectrum deficiency problem by enhancing the spectrum utilization. In recent years, Non-orthogonal multiple access (NOMA) has also gained significant interest in improving the spectrum efficiency of 5G networks. The simultaneous wireless information and power transfer (SWIPT) is a technique for the transfer of wireless information and power simultaneously for the power-limited wireless networks. In this paper, we are doing a comparative analysis between the obtainable throughput and standard throughput with perfect cancellation in the SIC receiver and also developed the golden selection search algorithm to acquire the optimal sensing time for maximizing the throughput in NOMA based CR network by using the SWIPT technique. In addition to the sensing time optimization has also simulated the throughput with the interference probability in perfect and imperfect sensing case.