LDPC Convolutional Packet Coding for Sequential Erasure Recovery
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Solution Overview
Problem
Existing erasure correction methods, such as Reed-Solomon codes, are inadequate for handling a large number of packet erasures in applications like moving image streaming, particularly when packet erasures exceed the correction capability or occur sequentially due to fading in radio communication paths, leading to ineffective error correction.
Innovation Solution
The implementation of a low-density parity-check convolutional code (LDPC-CC) erasure correction coding apparatus and method, which arranges information data according to a constraint length and coding rate to generate parity packets, enhancing erasure correction capability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Reed-Solomon code is used for erasure correction, then correction performance can be improved by increasing block length, but calculation amount and circuit scale increase
Solution Approach 1:
The patent changes the fundamental parameters of the error correction code from Reed-Solomon block code to LDPC convolutional code, adopting a different coding structure with sparse parity-check matrices that enables efficient decoding algorithms (such as belief propagation) with lower computational complexity and smaller circuit scale while maintaining or improving erasure correction performance
Solution Approach 2:
The patent substitutes the algebraic decoding mechanism of Reed-Solomon codes with the iterative probabilistic decoding mechanism of LDPC codes, replacing the traditional syndrome-based decoding approach with belief propagation algorithms that operate on factor graphs, thereby reducing the mechanical complexity of the decoding circuit
2Reliability
If Reed-Solomon code block length is increased to improve correction performance, then more packets can be corrected, but calculation amount increases
Solution Approach 1:
The patent changes the code structure from block code to convolutional code with memory, using sparse parity-check matrices that enable iterative decoding with fixed computational complexity per iteration, allowing the processing of long sequences without proportionally increasing total calculation amount
3Productivity
If LDPC code is used for packet erasure correction, then encoding and decoding can be performed with feasible time and calculation cost, but correction performance may be insufficient for large numbers of sequential erasures
Solution Approach 1:
The patent introduces time-varying periodic structures in the LDPC convolutional code, where the parity-check matrix changes periodically over time, allowing the code to adapt to different erasure patterns and improve correction capability for sequential erasures while maintaining efficient decoding through structured iterative algorithms
Data Source
AI summary
A loss correction encoding device having an improved capability of loss correction using LDPC-CC includes a rearranging unit that rearranges information data contained in n information packets according to the constraint length Kmax and the encoding rate (q−1)/q of a check polynomial of the loss correction code used in a loss correction encoding unit. Specifically, the rearranging unit rearranges the information data in such a way that continuous Kmax×(q−1) pieces of information data after rearrangement are contained in different information packets. The rearranging unit distributes the information data to information blocks from a information packets, where n satisfies the formula Kmax×(q−1)≤n.