Research on Multi-Path Topology Link Routing Algorithm for RF Front-End Based on Machine Learning

Future mobile communications will feature multi-band and array designs, achieving full signal coverage through time-division or frequency-division strategies. Existing reconfigurable RF circuit algorithms are designed for single-frequency, single-channel systems and are unsuitable for large-scale multi-channel RF front-end arrays. This study addresses signal routing and rapid component configuration in RF front-end multi-path topology routing. To reduce power consumption and enhance communication quality under interference, we integrate component configuration and signal routing into a unified system. For signal routing, we propose a Monte Carlo Tree Search (MCTS) algorithm combined with a neural network. The component configuration adopts a Binary Particle Swarm Optimization (BPSO) algorithm, using the Signal-to-Interference-plus-Noise Ratio (SINR) as the fitness function. Simulations show that this system improves signal quality and reduces computation time by 26.1%.