DocumentCode
3582867
Title
Sparse binary matrixes of QC-LDPC code for compressed sensing
Author
Xiao-Yan Jiang ; Zheng-Guang Xie
Author_Institution
Sch. of Electron. Inf., Nan tong Univ., Nantong, China
fYear
2014
Firstpage
284
Lastpage
288
Abstract
To overcome the shortcoming that random measurement matrix is hard for hardware implementation. A new structural and sparse deterministic measurement matrix based on parity check matrix in quasi-cyclic low-density parity-check code was proposed by studying the theory of compressed sensing. To verify the performance of the new matrix, reconstruction experiments were conducted. Experimental results show that, compared with the commonly used matrixes, the proposed matrix has lower reconstruction error under the same reconstruction algorithm and compression ratio. The proposed method achieves certain improvement in Peak Signal-to-Noise Ratio. Especially, if it was applied to hardware implementation, the need for physical storage space and the complexity of the hardware implementation should be greatly reduced due to the properties of quasi-cyclic and symmetric in the structure.
Keywords
compressed sensing; cyclic codes; matrix algebra; parity check codes; QC-LDPC code; compressed sensing; parity check matrix; peak signal-to-noise ratio; physical storage space; quasicyclic low-density parity-check code; random measurement matrix; reconstruction error; sparse binary matrices; sparse deterministic measurement matrix; structural deterministic measurement matrix; Complexity theory; Compressed sensing; Decoding; Hardware; Parity check codes; Sparse matrices; Symmetric matrices; Compressed sensing; deterministic measurement matrix; parity check matrix; random measurement matrix;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Active Media Technology and Information Processing (ICCWAMTIP), 2014 11th International Computer Conference on
Print_ISBN
978-1-4799-7207-4
Type
conf
DOI
10.1109/ICCWAMTIP.2014.7073409
Filename
7073409
Link To Document