A Ladybug Beetle Coati Optimized Joint Energy and Spectral Efficiency Maximization in Cooperative Cognitive Radio Networks

Due to the rise in information rate prerequisite and the heterogeneity level, the alteration in network traffic in the upcoming wireless communication (WC) encompasses innovative challenges in the case of energy efficiency (EE) and spectrum management. Recently, multiple current frameworks have anticipated and expressed the cooperative spectrum sharing (CSS) technique in CR networks (CRN). Nevertheless, none of the frameworks provided effective solutions to maximize EE-SE performance and failed compatible with recent WC applications. Hence, the proposed framework introduces a novel hybridized metaheuristic-aided Ladybug Beetle Coati optimizer (LB-CO) technique for maximizing the EE-SE performance in the CRN system. The Python simulation tool is utilized for the experimentation process and various performance measures like EE by varying transmission power (TP) under different SNR conditions, and normalized SE by varying TP are examined and compared with other techniques. The overall EE of 14.78kb/J for 8dB SNR value and 80kHz BW and the normalized SE of 0.61bits/s/Hz is obtained by the suggested framework for enhancing the performance of the CRN system.