3D spatial evolutionary particle swarm algorithm based emergency communication spatial deployment optimization

Building emergency communication in disaster areas is a key problem that emergency response needs to solve. Ad hoc Network (ANET) can quickly establish communication networks when public communication infrastructure is disrupted. At present, ground emergency communication deployment based on ANET usually relies on the operator’s experience, which struggles to ensure high-quality deployment in complex urban environments. This paper proposes an ANET nodes spatial optimization deployment algorithm based on 3D Spatial Evolutionary Particle Swarm Optimization (3DSEPSO). A wireless communication transmission rate model that depends on surface buildings and trees is constructed using ground truth communication data. The algorithm incorporates a fitness evaluation model, particle chromosome structure, and an evolutionary mechanism to intelligently deploy ANET nodes. By considering the spatial distribution of buildings and trees, the algorithm can achieve optimal data transmission quality by using a given number of ANET nodes. Experimental results demonstrate that the proposed algorithm significantly outperforms empirical approaches and traditional methods in terms of data transmission rates and quality. Thus, the algorithm provides better support for emergency rescue teams by facilitating more effective and reliable emergency communication.