Model Design and Simulation of Radio and Television Spectrum Resource Allocation Based on Self-learning Mechanism
Spectrum resources are indispensable resources in the field of radio and television,as well as in the entire wireless communication field.How to improve the utilization rate of spectrum resources through efficient resource allocation is an eternal issue in the history of communication.The self-learning mechanism is a strategy in game theory.This article designs and simulates a radio and television spectrum resource allocation model through a feedback based self-learning mechanism,which is applied to improve the efficiency of spectrum allocation in radio and television resource spectrum allocation.As the number of iterations increases,from the perspectives of memory length,number of users,and different frequency bands occupied by users,the influence of self-learning mechanism on the efficiency of spectrum resource allocation is observed through calculation and simulation of parameters such as user gain and spectrum utilization.It is then concluded that the optimized self-learning mechanism is superior to traditional self-learning mechanism in terms of allocation efficiency and convergence speed.
self-learning mechanismradio and television spectrum resourcespectral efficiency
万方数据
维普
