6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

A Tree Based Recovery Algorithm for Block Sparse Signals

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  • @INPROCEEDINGS{10.4108/icst.crowncom.2011.246253,
        author={Wenbin  Guo and Xing  Wang and Yang  Lu and Wenbo  Wang},
        title={A Tree Based Recovery Algorithm for Block Sparse Signals},
        proceedings={6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2012},
        month={5},
        keywords={},
        doi={10.4108/icst.crowncom.2011.246253}
    }
    
  • Wenbin Guo
    Xing Wang
    Yang Lu
    Wenbo Wang
    Year: 2012
    A Tree Based Recovery Algorithm for Block Sparse Signals
    CROWNCOM
    IEEE
    DOI: 10.4108/icst.crowncom.2011.246253
Wenbin Guo1,*, Xing Wang1,*, Yang Lu1,*, Wenbo Wang1,*
  • 1: Wireless Signal Processing and Network Lab, Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts & Telecommunications (BUPT), Beijing 100876, P. R. China
*Contact email: gwb@bupt.edu.cn, wangxing613@126.com, luyangnnu@126.com, wbwang@bupt.edu.cn

Abstract

The structure of block sparsity in multi-band signals is prevalent. Performance of recovery algorithms that taking advantage of the block sparsity structure is promising in the compressed sensing framework. In this paper, we propose a binary tree based recovery algorithm for block-sparse signals, where we exploit the fact that each block may have zero and nonzero elements both. The proposed algorithm improves the current algorithms through iteratively separating the recovered blocks of signals into two smaller blocks. Therefore, greedy searching based algorithm is possible to obtain more accurate basis for signal recovery. Simulations are performed and the results show the improvements over current block-based recovery algorithms.