Matrix Of LDPC Code Research Articles

New Optical Codes Based on Construction of Parity Check Matrix of LDPC Codes

Abstract In this paper, new spectral optical codes based on the construction parity check matrix of LDPC codes were designed and implemented in an optical code-division multiple access communication system. Two types optical family codes can be obtained with respectively a cross correlation of λ c = 0 {\lambda _c} = 0 and λ c = 1 {\lambda _c} = 1 . In each case, the codes can either be decoded using the direct detection or the balanced detection. Performance was evaluated by referring to the Q factor, the bit error rate and the eye pattern diagrams using Optisystem 9.0.

Measurement Matrix Construction Algorithm for Compressed Sensing based on QC-LDPC Matrix

The measurement matrix of compressed sensing has a significant impact for sampling and reconstruction algorithm of the original signal. At present, the majority of the measurement matrix is randomly constructed, and it is difficulty for hardware implementation in the practical applications. In this paper, we use the sparse characteristic of parity- check matrix of LDPC codes, construct measurement matrix based on QC-LDPC (Quasi-cyclic low-density parity-check) matrix, which is a structural and sparse deterministic measurement matrix. The simulation results show that, the measurement matrix is proposed in this paper not only can obtain a better reconstructed image quality, but also it can reduce the complexity of hardware implementation for quasi-cyclic.

An Efficient LDPC Encoder for CMMB Using RU Method

An efficient LDPC encoder based on classic RU method is presented for CMMB in this paper. The RU method uses an optimized greedy algorithm for approximate triangulation with sparse matrix of LDPC codes. Simulation results show that this improved method can reduce encoding complexity effectively and save hardware resource for implementation.

A New LDPC Encoder for CMMB Based On RU Algorithm

A low complexity LDPC encoder based on classic RU Algorithm is presented for CMMB. The RU Algorithm uses an optimized greedy algorithm for approximate triangulation with sparse matrix of LDPC codes. Results show that this optimized algorithm can reduce complexity of encoding and the consumption of hardware resource effectively.