Optimization of Received Signal Strength in Wireless Underground Sensor Networks Based on Chaotic Multi-Objective Particle Swarm Optimization Algorithm

The transmission characteristics of electromagnetic wave signals in farmland soil had been found to be quite complex, making it difficult to identify suitable soil environments where wireless underground sensor network nodes could achieve strong signal reception. To scientifically and accurately optimize signal reception strength for underground-to-aboveground and underground-to-underground communication modes, main soil conditions had been selected as relevant factors. Experimental data on signal reception strength under different soil conditions had been collected, and a regression equation had been established. A multi-objective particle swarm optimization algorithm was improved using chaotic initialization, linearly decreasing inertia weight, and asymmetric learning factors. It had been demonstrated by experimental results that the improved algorithm could effectively enhance convergence speed, avoid falling into local optima, and better handle multi-objective problems. Compared to traditional algorithms, signal reception strength had been improved by 147.28% and 9.16%, respectively, effectively determining soil environments suitable for both communication modes. This had provided technical support for the deployment and establishment of wireless underground sensor networks.