电子学报2017，Vol.45Issue(7)：1553-1558,6.DOI:10.3969/j.issn.0372-2112.2017.07.002
一种计算有效的Nystrom特征子空间匹配主用户频谱感知新算法
A New Computationally Efficient Nystrom Feature Subspace Matching Algorithm for the Primary User Spectrum Sensing
摘要
Abstract
Considering the high computational burden of the previous kernel spectrum sensing methods,this paper proposes a computationally more efficient Nystrom subspace matching (NSM) algorithm.Based on the independent identically distributed observations,the subset is randomly chosen to implement the Nystrom approximation and reconstruct the related kernel features in a high-dimensional Euclidean space.Then,the related Nystrom subspaces respectively for the primary users and the secondary users are modified,and the Frobenius range between these two subspaces can be computed to determine whether the primary users exist or not.Compared to the previous kernel subspace matching methods,the novel version reduces the computational complexity by 66% while provides almost the same detection performance.Computer simulations are conducted to evaluate the performance of the proposed algorithm.关键词
频谱感知/核空间/Nystrom近似/特征子空间匹配Key words
spectrum sensing/kernel space/nystrom approximation/feature subspace matching分类
信息技术与安全科学引用本文复制引用
陈若男,孙晓颖,刘国红..一种计算有效的Nystrom特征子空间匹配主用户频谱感知新算法[J].电子学报,2017,45(7):1553-1558,6.基金项目
国家自然科学基金(No.61171137) （No.61171137）
国家重点研发计划(No.2016YFB1001304) （No.2016YFB1001304）
