Sparse binary matrixes of QC-LDPC code for compressed sensing

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.

Deterministic Construction of Compressed Sensing Measurement Matrix with Arbitrary Sizes via QC-LDPC and Arithmetic Sequence Sets

“…In recent years, many researchers have put forward many principles and methods to construct [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33] and optimize [34][35][36] measurement matrices. This paper mainly studies the construction method of deterministic measurement matrices.…”

“…This paper mainly studies the construction method of deterministic measurement matrices. Dimakis et al [19], Jiang et al [20] and Xia et al [23] used the binary matrix obtained from the LDPC code as the measurement matrix. Zeng et al introduced a deterministic structure which combines orthogonal matrices and a chaos-based Toeplitz matrix [24].…”