GSM-R wireless field strength coverage prediction algorithm based on PSO-RBF neural network algorithm

In the wake of successive construction new railway lines, lines and existing are adjacent, approached surpassed. early stage line construction, if influence adjacent is not considered in subsequent planning, original need to be adjusted, reconstruction base station (BS) coverage along increases hardness buliding invested funds. Therefore, a Global System for Mobile Communications – Railway (GSM-R) wireless field strength prediction model based on particle swarm optimization (PSO) algorithm optimized radial basis function neural network (RBFNN) was proposed. Aiming at problem slow convergence caused by improper selection parameters structure RBFNN, PSO used optimize combined with actual measurement data site, PSO-RBFNN established simulate predict coverage. The results show that effect best, followed worst HATA model, which very beneficial future GSM-R provides feasible idea.