认知无线电中基于感知时间和K秩准则的优化

发布时间：2018-06-09 16:07

本文选题：认知无线电 + 频谱感知　；参考：《计算机技术与发展》2015年12期

【摘要】：认知无线电系统中,通过次用户间的协作频谱感知可以大大增加系统的检测概率,但同时也增加了系统的能量消耗。为了提高认知无线电系统的综合性能,文中分别对系统的错误概率和能量效率进行优化。文中次用户采用K秩融合准则来进行协作,所以影响系统性能的参数可以是K、参与协作的次用户数N和感知时间τ。而优化问题可以分为两个阶段:第一阶段,给定τ,通过使错误概率最小来得到最优的K和N;第二阶段,给定K和N,通过使能量效率最小来得到最优的τ。文中利用数学推导,证明了两个优化问题均存在最优值,最后再利用联合迭代算法可以得到综合最优的K、N和τ。仿真结果验证了之前的理论分析,并表明在最优参数下系统的综合性能明显提高。
[Abstract]:In cognitive radio systems, cooperative spectrum sensing among secondary users can greatly increase the detection probability of the system, but it also increases the energy consumption of the system. In order to improve the comprehensive performance of cognitive radio system, the error probability and energy efficiency of the system are optimized in this paper. In this paper, the K-rank fusion criterion is used to coordinate the secondary users, so the parameters that affect the performance of the system can be K, the number of secondary users participating in the collaboration, and the perceptual time 蟿. The optimization problem can be divided into two stages: in the first stage, given 蟿, the optimal K and N are obtained by minimizing the error probability; in the second stage, given K and N, the optimal 蟿 is obtained by minimizing the energy efficiency. In this paper, the mathematical derivation is used to prove that there exists an optimal value for both optimization problems. Finally, by using the joint iterative algorithm, we can obtain the synthetic optimal Kon N and 蟿. The simulation results verify the previous theoretical analysis and show that the comprehensive performance of the system is improved obviously under the optimal parameters.
【作者单位】：南京邮电大学通信与信息工程学院;
【基金】：国家“973”重点基础研究发展计划项目(2013CB329005) 国家自然科学基金资助项目(61471201)
【分类号】：TN925

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