基于信道分类和自适应调制编码的认知无线电决策引擎

摘要

在多径信道条件下，针对单载波频域均衡(SC-FDE)认知系统不能通过多目标优化策略进行决策的问题，该文提出一种基于信道分类和自适应调制编码(AMC)的认知无线电决策引擎。该决策引擎首先对当前信道进行分类，确定当前信道状态；然后根据当前信道状态下的策略切换表选取最优传输策略(MCS)，并计算该策略的使用时长(MCSD)。一旦当前策略的持续时间超过了其使用时长，认知决策引擎就会对最优策略进行更新。仿真结果表明，该决策引擎能够提供最优的传输策略以提高频谱效率，使SC-FDE认知系统更好地适应无线信道复杂的电磁环境。%It can not make decision by multi-objective optimization over the multipath channel for Single Carrier Frequency Domain Equalization (SC-FDE) cognitive systems. In order to solve the issue, a novel cognitive radio decision engine is proposed based on channel classification and Adaptive Modulation and Coding (AMC). Firstly, the channel is classified to determine the current channel state by the proposed engine. Then, the optimal Modulation and Coding Scheme (MCS) is selected in the MCS switching table according to the current channel state, and its Modulation and Coding Scheme Duration (MCSD) is calculated. Once the current MCS lasts longer than its MCSD, the cognitive radio decision engine will update the optimal MCS. The simulation results show that the proposed cognitive radio decision engine can provide the optimal transmission strategy to improve the spectral efficiency for SC-FDE cognitive systems. Therefore, the engine makes SC-FDE cognitive systems adapt to the complex electromagnetic environment better.