基于观测矩阵优化的自适应压缩频谱感知  

Adaptive compressed spectrum sensing based on optimized measurement matrix

作　　者：王韦刚[1,2] 杨震[1] 顾彬[1] 胡海峰[1,3] 

机构地区：[1]南京邮电大学教育部宽带无线通信和传感网技术重点实验室,江苏南京210003 [2]南京邮电大学电子科学与工程学院,江苏南京210003 [3]东南大学移动通信国家重点实验室,江苏南京210008

出　　处：《通信学报》2014年第8期33-39,共7页Journal on Communications

基　　金：国家重点基础研究发展计划("973"计划)基金资助项目(2011CB302903);国家自然科学基金资助项目(60971129;61071092;61271335);南京邮电大学青蓝计划基金资助项目(NY210038);东南大学移动通信国家重点实验室开放研究基金资助项目(2011D04);江苏省博士后科研基金资助项目(1101125C);中国博士后科学基金面上基金资助项目(2012M511309)~~

摘　　要：推导了自适应压缩感知中的重构估算误差,研究了如何降低观测矩阵列向量之间的自相关性,分析了观测矩阵优化对压缩感知重构算法的影响。将观测矩阵优化与压缩感知自适应过程相结合,提出了基于观测矩阵优化的自适应压缩频谱感知算法。仿真结果证实,所提算法比传统算法重构时产生的均方误差(MSE)更低,在同一观测次数下检测概率更高,在达到同等接收操作性能(ROC)时所需观测次数更少。The estimation error of reconstruction by adaptive compressed sensing was derived, and the column vector autocorrelation of the observation matrix was reduced, and the impact of optimization process on compressed sensing reconstruction algorithm was analyzed. Combining the observation matrix optimization and adaptive process, the spectrum sensing algorithm of optimized adaptive compression based on observation matrix was proposed. The simulation results show that the mean square error （MSE） of proposed algorithm is lower than traditional algorithm, and the probability of detection of proposed algorithm is higher on the same number of observations, and the required number of observations is fewer when achieving the same receiver operating performance （ROC）.

关 键 词：认知无线电 压缩感知 频谱检测 观测矩阵 

分 类 号：TN92[电子电信—通信与信息系统]