Joint Optimization of 5.5G Cellular Networks Using Ray Tracing and PSO-MDE for Antenna Configuration and Power Allocation

Abstract

In the continuous evolution of mobile communication technology, 5.5G network is a key step towards future communication, which is gradually becoming the focus of academia and industry. To solve the complex signal propagation and serious multi-path interference in high frequency band, the improved particle swarm differential evolution algorithm and multi-objective differential evolution particle swarm optimization algorithm are proposed to maximum coverage and minimum power consumption in wireless sensor networks. This method improves the efficiency of solving complex optimization problems by maintaining the global search ability and enhancing the local search performance. The experiment was carried out on a customized simulation platform and tested for different scale sensor deployment scenarios. The research results indicated that the optimal coverage after optimizing the parameters of the community antenna occurred when the inertia factor was 0.4 and 0.7, at 0.641 and 0.640, respectively. The average optimal coverage was 0.633 and 0.632 when the inertia factor was 0.6 and 0.7, respectively. The designed algorithm performed the best in reducing transmission power, computational efficiency, and exploring solution space. The minimum total transmission power reached 33.5dBm, the maximum number of Pareto front points reached 240, and the calculation time was the shortest, at 530s. The research results show that the proposed optimization algorithm can effectively improve the coverage and energy efficiency of the 5.5G network, providing an effective solution for network optimization.