A Useful Performance Metric for Compressed Channel Sensing

被引：5
|
作者：
Sharp, Matthew [1 ]
Scaglione, Anna [2 ]
机构：
[1] Cornell Univ, Ithaca, NY 14853 USA
[2] Univ Calif Davis, Davis, CA 95616 USA
来源：
IEEE TRANSACTIONS ON SIGNAL PROCESSING | 2011年 / 59卷 / 06期
基金：
美国国家科学基金会;
关键词：
Channel estimation; compressed sensing; system identification; sparsity; SPARSE; RECOVERY;
D O I：
10.1109/TSP.2011.2123892
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Recently, new progress has been made in using basis expansion models for system identification with compressed sensing. To aid the application of these methodologies, we introduce a metric, called localized coherence, for choosing input signals that result in better estimation performance. Its definition is motivated through the analysis of the normalized mean Euclidean error of the channel estimate and its efficacy is demonstrated through numerical simulations.
引用
收藏
页码：2982 / 2988
页数：7
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