Low Density Parity Check Accumulate Research Articles

Graphics processing unit-accelerated joint-bitplane belief propagation algorithm in DSC

The M-ary source with nonstationary correlation can be encoded with a single binary low-density parity-check (LDPC) code and decoded together in distributed source coding. The joint-bitplane belief propagation (JBBP) is a useful decoding algorithm for multiple bitplanes of an M-ary source. However, it suffers from the drawbacks of low computational efficiency and long execution time. Motivated by the evolution of the Graphics Processing Unit (GPU) and the inherent parallel characteristic of the JBBP, we propose a novel approach for the computationally intensive processing of the JBBP algorithm on GPU using the compute unified device architecture programming model. Two different parallel modes are utilized for the belief passing between different nodes of the JBBP. It is found that the bottlenecks of the JBBP lie in computing the overall probability mass functions (pmfs) of symbol nodes and the overall beliefs of bit nodes. Thus, a data partitioning method is leveraged to split a large array of pmfs into small pieces which can be loaded into L1 cache instead of global memory. The optimal block size is selected which not only assigns as large L1 cache as possible for individual thread, but also guarantees multiple active warps in each stream multiprocessor. Experimental results show that when the length-6336 (length-50,688, resp.) LDPC accumulate (LDPCA) code is used to compress the source, the JBBP decoder can achieve about 20$$\times $$× (41$$\times $$×, resp.) speedup on GPU compared with the original C code on CPU. Better performance would be further obtained with longer LDPCA codes. Moreover, the parallel JBBP is also applied in hyperspectral image compression and video coding and it shows good speedup performance.

Reliability-Based Deblocking Filter for Wyner-Ziv Video Coding

In Wyner-Ziv coding, video signals are reconstructed by correcting side information generated by block-based motion estimation/compensation at the decoder. The correction is not always accurate due to the limited number of parity bits and early stopping of low-density parity check accumulate (LDPCA) decoding in distributed video coding, or due to the limited number of measurements in distributed compressive video sensing. The blocking artifacts caused by blockbased processing are usually conspicuous in smooth areas and degrade the perceptual quality of the reconstructed video. Conventional deblocking filters try to remove the artifacts by treating both sides of the block boundary equally; however, coding errors generated by block-based processing BRare not necessarily the same on both sides of the block boundaries. Such a block-wise difference is exploited in this paper to improve deblocking for Wyner-Ziv frameworks by designing a filter where the deblocking strength at each block can be non-identical, depending on the reliability of the reconstructed pixels. Test results show that the proposed filter not only improves subjective quality by reducing the coding artifacts considerably, but also gains rate distortion performance.

부호율 적응적 분산 소스 부호화를 위한 극부호의 설계

본 논문에서는 비대칭 Slepian-Wolf 부호화에 극부호를 적용하는 방법을 고려하며, 부호율 적응성을 갖도록 극부호를 설계하는 방법을 제시한다. 제안된 극부호 기반 분산 소스 부호화에 연속제거 리스트 복호 기법을 적용하는 경우에 Slepian-Wolf의 한계에 매우 근접함을 확인하였으며, 이는 기존의 저밀도 패리티 검사 부호를 이용한 구현보다 현저하게 향상된 것이다.

Rate-adaptive BCH codes for distributed source coding

This paper considers Bose-Chaudhuri-Hocquenghem (BCH) codes for distributed source coding. A feedback channel is employed to adapt the rate of the code during the decoding process. The focus is on codes with short block lengths for independently coding a binary source X and decoding it given its correlated side information Y. The proposed codes have been analyzed in a high-correlation scenario, where the marginal probability of each symbol, X i in X, given Y is highly skewed (unbalanced). Rate-adaptive BCH codes are presented and applied to distributed source coding. Adaptive and fixed checking strategies for improving the reliability of the decoded result are analyzed, and methods for estimating the performance are proposed. In the analysis, noiseless feedback and noiseless communication are assumed. Simulation results show that rate-adaptive BCH codes achieve better performance than low-density parity-check accumulate (LDPCA) codes in the cases studied.

Improved Low-Density Parity Check Accumulate (LDPCA) Codes

We present improved constructions for Low-Density Parity-Check Accumulate (LDPCA) codes, which are rate-adaptive codes commonly used for distributed source coding (DSC) applications. Our proposed constructions mirror the traditional LDPCA approach; higher rate codes are obtained by splitting the check nodes in the decoding graph of lower rate codes, beginning with a lowest rate mother code. In a departure from the uniform splitting strategy adopted by prior LDPCA codes, however, the proposed constructions introduce non-uniform splitting of the check nodes at higher rates. Codes are designed by a global minimization of the average rate gap between the code operating rates and the corresponding theoretical lower bounds evaluated by density-evolution. In the process of formulating the design framework, the paper also contributes a formal definition of LDPCA codes. Performance improvements provided by the proposed non-uniform splitting strategy over the conventional uniform splitting approach used in prior work are substantiated via density evolution based analysis and DSC codec simulations. Optimized designs for our proposed constructions yield codes with a lower average rate gap than conventional designs and alleviate the trade-off between the performance at different rates inherent in conventional designs. A software implementation is provided for the codec developed.

Design of Binary LDPCA Codes with Source Revealing Rate-Adaptation

In this letter, we consider binary low density parity check accumulate (LDPCA) codes with source revealing rate-adaptation for distributed source coding (DSC) applications. We propose an effective algorithm for selecting source symbols to the source revealing. Numerical results demonstrate that the proposed scheme significantly outperforms the conventional LDPCA codes in the high compression rate region in asymmetric DSC systems.

Design of degree distributions for LDPCA codes

A degree distribution design method of low-density parity-check accumulate (LDPCA) codes is proposed for rate-compatible asymmetric Slepian-Wolf coding (SWC) of correlated binary memoryless sources. The degree distribution is designed by seeking the simultaneous optimum at the lowest and the highest compression rates of the specified range with density evolution algorithm. The experimental results show that the coding efficiency of codes constructed with the designed degree distribution is close to the Slepian-Wolf limit over the entire target range and better than all other reported results of the rate-compatible asymmetric SWC.

Rate-adaptive codes for distributed source coding

Source coding with correlated decoder side information is considered. We impose the practical constraint that the encoder be unaware of even the statistical dependencies between source and side information. Two classes of rate-adaptive distributed source codes, both based on low-density parity-check (LDPC) codes, are developed and their design is studied. Specific realizations are shown to be better than alternatives of linear encoding and decoding complexity. The proposed rate-adaptive LDPC accumulate (LDPCA) codes and sum LDPC accumulate (SLDPCA) codes (of length 6336 bits) perform within 10% and 5% of the Slepian–Wolf bound in the moderate and high rate regimes, respectively.