Research on Optimal Resource Allocation of Wireless Communication System Based on Linear Programming and Genetic Algorithm

Abstract

This paper proposes a resource optimization allocation model for wireless communication system, focusing on the resource block allocation and performance optimization method with multi-algorithm fusion. Firstly, the channel model and rate calculation mechanism are constructed to calculate SINR based on path loss and Rayleigh fading, and the transmission rate is determined by Shannon's formula, which provides basic parameters for resource allocation. Secondly, multi-layer optimization strategy is adopted: greedy algorithm completes the initial resource block allocation by priority, linear programming optimizes the throughput on the initial scheme, simulated annealing algorithm searches for the global optimum through the energy function and the perturbation mechanism, and subsequently also replaces the simulated annealing with genetic algorithm to improve the efficiency by combining the elite retention and the dynamic mutation rate. Finally, the performance is verified by dynamic task and multi-base station interference model to analyze the changes of throughput, QoS and other indicators. The role of this model is to achieve efficient resource allocation and performance balance, and the advantage lies in the integration of the advantages of multiple algorithms, taking into account the local optimization and global search, to improve the throughput under the limited resources, and to adapt to the needs of dynamic communication scenarios.