检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]杭州电子科技大学通信工程学院,杭州310018 [2]中国电子科技集团第36研究所通信系统信息控制技术国家级重点实验室,嘉兴314001
出 处:《电信科学》2014年第3期100-104,共5页Telecommunications Science
基 金:电科院预研基金资助项目(No.41101040102)
摘 要:针对基于压缩感知的传统频谱感知方法通常假设稀疏度已知,而实际频谱感知中信道稀疏度是未知且时变的这一问题,提出一种稀疏度自适应的宽带频谱感知算法。首先采用分布式压缩感知和RIP性质预估计稀疏度,然后通过置信系数更新估计得到频谱支撑集,即主用户正在使用的频谱。仿真结果表明,在低信噪比条件下,本方法的检测概率高于稀疏度已知的频谱感知方法,而仅损失极少的频谱利用率,且计算复杂度低。Traditional spectrum sensing based on compressed sensing assumes that the sparsity is. known, in fact,it is unknown and time-varying. To solve the problem, a sparsity adaptive algorithm for wideband spectrum sensing was proposed. First, the distributed compressed sensing and restricted isometry property principle were adopted to estimate an initial sparsity value. Then the confidence coefficient was used to update the sparsity and the spectrum support set was obtained, which was occupied by a primary user. Simulation results show that the proposed method has better spectrum detection performance than the spectrum sensing method with a known sparsity, and losses spectrum availability a little in low SNR, and its complexity is small.
关 键 词:压缩感知 频谱感知 稀疏度估计 约束等距性 置信系数
分 类 号:TN92[电子电信—通信与信息系统]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.51