Spectral efficiency enhancement and energy optimization in 5G networks via stochastic optimization-inspired by modified slime mould algorithm

Spectral efficiency enhancement and energy optimization in 5G networks via stochastic optimization-inspired by modified slime mould algorithm

연구 분야: Networking

학회: International Journal of Information Technology

In the context of implementing Fifth Generation (5G) wireless networks, Energy Efficiency (EE), along with Spectral Efficiency (SE), are critical to consider. Simultaneously sharing the infrastructure between various operators was also observed to be a trend on wireless communication networks. Evaluating network performance is challenging, given factors like transmission time and power control. While the previous efforts have emphasized equalizing radio resources among access links and backhauls of millimetre wave (mmWave) small cells in 5G cellular systems. The focus was primarily on network throughput rather than Energy Efficiency (EE). Consequently, it has become imperative to consider both EE and SE as vital parameters to design 5G systems. This study introduces a novel approach, the Modified Slime Mould Algorithm (MSMA), which optimizes EE by maximizing SE. This optimization is achieved by fine-tuning parameters such as transmit power and bandwidth in 5G networks. The performance of the proposed network was evaluated through cost function and statistical analyses. The developed spectral efficiency enhancement model in the 5G network significantly improved SE when compared to Artificial Gorilla Troops Optimizer (AGTO), Jaya Algorithm (JA), Harris Hawks Optimization (HHO), and Slime Mould Algorithm (SMA) techniques.