.png){kind=icon}
返回
GaussianSource Coding Based on P-LDPC Code
.png){kind=icon}
PRE
AI
DOI：10.1109/TCOMM.2023.3245660.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A lossy source coding system based on the protograph low-density parity-check (P-LDPC) code is proposed for Gaussian source compression. In the proposed system, the conventional belief propagation (BP) algorithm is modified to be a concatenated BP-inverse BP (BP-iBP) for encoding and decoding, where the iBP is constructed by a fully-connected layer of a neural network. Compared to the existing approximate message passing algorithm, the proposed BP-iBP realizes a float to-bit compression with low complexity for arbitrary Gaussian sources. The BP-iBP is implemented based on the linking relation of the protograph; therefore, it is necessary to optimally design the protograph to obtain better rate-distortion function (RDF) performance. Regarding the coding optimal procedure, a mutual information iteration convergence (MIIC) algorithm is designed as the optimal criterion to determine the source P-LDPC code with minimum distortion. Inspired by the plane construction of quantum stabilizer code, a lattice topological splicing (LTS) algorithm is proposed for regularly building the protograph to reduce the code searching complexity. By using the MIIC and the LTS algorithms, the BP-iBP based on the designed P-LDPC code maintains good distortion performance close to the RDF limit.
Keyword:
Codes
Source coding
Encoding
Distortion
Open area test sites
Decoding
Resource description framework
Lossy source coding
P-LDPC code
belief propagation algorithm
rate-distortion function
optimal coding algorithm
期刊
IF:
8.3
论文数:
1.2W
被引数:
3.6W
机构
引用论文
Performance Analysis of Distortion-Acceptable Cooperative Communications in Wireless Sensor Networks for Internet of Things.png)
IEEE SENSORS JOURNAL
OAAI
IEEE SENSORS JOURNALIF4.5
OAAI分享收藏
查看更多内容