Performance Analysis of a Prediction-Sensing Based Cooperative Energy Harvesting CRN Over Rician Fading Channels

Abstract

In this work, we investigate a prediction-sensing based cooperative energy harvesting cognitive radio network (EH-CRN) over a Rician fading environment. Incorporating a prediction based sensing mechanism provides enhanced protection to the quality-of-service (QoS) of the primary user (PU) subsequently leading to an improved spectrum efficiency. The complex channel model in analysing the performance of the prediction-sensing based EH-CRN is taken to be as Rician considering the envisioned higher frequency communication systems. An optimal sensing time is also evaluated whereat the secondary network throughput is the maximum. The system behaviour is analysed in terms of two standard performance indices viz., outage probability (OP) and the symbol error rate (SER). The exact analytical expression for both the OP and SER in a Rician fading channel environment is obtained. The impact of Rician fading factor, signal-to-noise ratio (SNR), number of cooperative cognitive radio nodes, data rate parameter and prediction error on the detection probability, harvested energy, normalized throughput, OP and SER is analysed and discussed. The SER for different digital modulation techniques are also obtained. Monte Carlo simulations verify the correctness of the analytical modelling of the system. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.