摘要： 为在不完美频谱检测环境下对资源进行优化分配，提出一种分布式认知无线电网络资源分配算法。根据贝叶斯理论给出子载波状态信任指数与统计平均干扰功率的概念，利用拉格朗日对偶分解理论，将原分配问题分解为独立的子问题并进行求解，以实现多用户资源的有效分配。仿真结果表明，相对基于回避准则的优化算法，该算法能有效提高系统容量，且能更快地达到循环结束条件。

关键词: 认知无线电网络, 贝叶斯理论, 资源分配, 对偶分解理论, 不完美频谱检测

Abstract: To optimize resource allocation in imperfect spectrum detection environment,a distributed cognitive radio network resource allocation algorithm is proposed.Based on Bayesian theory,the concepts of subcarrier state trust index and statistical average interference power are given.By using Lagrange dual decomposition theory,the original allocation problem is decomposed into independent sub-problems and solved to achieve effective resource allocation for multiple users.Simulation results show that compared with the optimization algorithm based on avoidance criterion,the proposed algorithm can effectively improve the system capacity and achieve the end condition of the cycle faster.

Key words: cognitive radio network, Bayesian theory, resource allocation, dual decomposition theory, imperfect spectrum detection

中图分类号: 

• TP391