Compressed Sensing Using Sparse Binary Measurements: A Rateless Coding Perspective

被引：0

作者：

Vukobratovic, Dejan ^{[1
]}

Sejdinovic, Dino ^{[2
,3
]}

Pizurica, Aleksandra ^{[4
]}

机构：

[1] Univ Novi Sad, Dept Power Elect & Commun Engn, Novi Sad 21000, Serbia

[2] Univ Oxford, Dept Stat, Oxford OX1 2JD, England

[3] Univ Oxford, Univ Coll, Oxford OX1 2JD, England

[4] Univ Ghent, Dept Telecommun & Informat Proc, B-9000 Ghent, Belgium

来源：

2015 IEEE 16TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC) | 2015年

关键词：

compressed sensing; rateless codes; iterative decoding; density evolution; EXIT charts; CODES;

D O I：

暂无

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：

Compressed Sensing (CS) methods using sparse binary measurement matrices and iterative message-passing recovery procedures have been recently investigated due to their low computational complexity and excellent performance. Drawing much of inspiration from sparse-graph codes such as Low-Density Parity-Check (LDPC) codes, these studies use analytical tools from modern coding theory to analyze CS solutions. In this paper, we consider and systematically analyze the CS setup inspired by a class of efficient, popular and flexible sparse-graph codes called rateless codes. The proposed rateless CS setup is asymptotically analyzed using tools such as Density Evolution and EXIT charts and fine-tuned using degree distribution optimization techniques.

引用

页码：86 / 90

页数：5

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