Abstract
A joint source channel coding (JSCC) scheme based on source and channel low density parity check (LDPC) codes, which is named as the D-LDPC system, has attracted a lot of attention recently. However, it suffers from a high error-floor. By introducing a linking matrix connecting variable nodes of source LDPC and check nodes of channel LDPC, the error-floor can be lowered effectively. However, the water-fall performance was lost with the increasing of the size of linking matrix. In this paper, a detailed analysis about the impact of this linking matrix on the water-fall region is conducted. Some design principles for the linking matrix are proposed, by which several linking matrices for different source statistics will be designed to improve the water-fall performance from the perspective of both the source and channel LDPC codes. The extrinsic information transfer (EXIT) analysis and numerical simulations will be compared to verify the superiority of the proposed linking matrices.
Highlights
Low density parity check (LDPC) code employed as channel coding has exhibited performance close to capacity over a binary symmetric memoryless channel [1]
A joint source-channel coding (JSCC) scheme named as double LDPC (D-LDPC) was proposed in [4], where two LDPC codes were used as source coding and channel coding, respectively
As the error floor was caused by the lost of original source information, a linking matrix connecting variable nodes (VNs) of source LDPC and check nodes (CNs) of channel LDPC was introduced [16], where more available information was provided for joint decoding
Summary
Low density parity check (LDPC) code employed as channel coding has exhibited performance close to capacity over a binary symmetric memoryless channel [1]. As the error floor was caused by the lost of original source information, a linking matrix connecting VNs of source LDPC and CNs of channel LDPC was introduced [16], where more available information was provided for joint decoding Some improvements in both water-fall and error-floor region were obtained by an information-shorten algorithm [17], but it. An adaptive scheme for image transmission in Internet of Things (IoTs) scenarios was proposed [18] Simple analysis of this linking matrix was presented in [19], which showed its function to lower the error-floor as the number of edges in this linking matrix increases, but it gave rise to the loss of water-fall performance. Where Ms ×Ns Hs matrix is the source PLDPC code, Mc ×Nc Hc matrix is the channel PLDPC code, Mc × Nadd Hl linking matrix represents the linkage relationship between the VNs of source code and the CNs of channel code and Ms × Ms IH is the corresponding identity matrix
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