LDPC Re-Encoding for Interference Cancellation in 5G Decoding
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Solution Overview
Problem
In wireless communication systems, existing technologies face challenges in effectively decoding signals due to noise, fading, and inter-symbol interference, which degrade link performance and hinder high-speed digital communication requirements.
Innovation Solution
The implementation of a method and apparatus that performs decoding using Low Density Parity Check (LDPC) codes, followed by re-encoding based on LDPC syndrome and Cyclical Redundancy Check (CRC) detection, for interference cancellation in systems requiring encoding or re-encoding for parity, specifically in 5G communication systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LDPC decoding is performed to reconstruct distorted information, then reliability is improved, but device complexity increases due to the need for syndrome calculation and CRC detection
Solution Approach 1:
The decoding process is segmented into distinct functional modules: syndrome calculation unit, CRC detection unit, and interference cancellation unit. Each module performs a specific function, allowing the complex decoding process to be managed through modular components rather than a monolithic structure.
Solution Approach 2:
The syndrome is calculated preliminarily during the decoding process before final error correction is applied. This preliminary syndrome calculation enables subsequent interference cancellation operations to use pre-computed error information, reducing the overall computational burden during critical decoding phases.
2Reliability
If re-encoding is performed based on LDPC syndrome and CRC detection, then interference cancellation is improved, but loss of time increases due to additional processing steps
Solution Approach 1:
The syndrome is calculated in advance during the initial decoding phase, and this pre-computed syndrome information is then reused in the interference cancellation phase. This eliminates the need to recalculate syndromes multiple times, significantly reducing processing time while maintaining interference cancellation effectiveness.
Solution Approach 2:
The syndrome information is computed, used for error detection and correction, and then retained for interference cancellation operations. Rather than discarding the syndrome after initial decoding, it is recovered and reused in subsequent processing stages, improving efficiency without sacrificing performance.
3Adaptability or versatility
If support for variable length and rate LDPC codes is implemented, then adaptability is improved, but device complexity increases due to multiple parity check matrices
Solution Approach 1:
The decoding apparatus is designed with universal components that can handle multiple code lengths and rates. The syndrome calculation unit and CRC detection unit are configured to work with different parity check matrices through parameter configuration rather than requiring separate hardware for each code type, enabling multi-functionality without proportional increases in complexity.
Solution Approach 2:
The system dynamically selects and configures the appropriate parity check matrix based on the required code length and rate. Rather than maintaining fixed structures for each code variant, the apparatus adapts its configuration dynamically, allowing flexible support for variable length and rate LDPC codes through a single versatile decoding framework.
Data Source
AI summary
Disclosed are a communication scheme and a system thereof for converging IoT technology and a 5G communication system for supporting a high data transmission rate beyond that of a 4G system. The disclosure can be applied to intelligent services (for example, services related to a smart home, smart building, smart city, smart car, connected car, health care, digital education, retail business, security, and safety) based on the 5G communication technology and the IoT-related technology. A decoding method includes: performing decoding through an inner code; detecting an error through an outer code; determining a re-encoding method; and performing re-encoding. A method for processing a signal includes decoding a first layer signal to determine first LDPC information bits, encoding the first LDPC information bits and a first parity bits to determine second parity bits; identifying a part of the first LDPC information bits, and decoding a second layer signal.