LDPC Re-Decoding and Interference Cancellation for 5G Receivers
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Solution Overview
Problem
In wireless communication systems, especially in 5G networks, there is a challenge in maintaining high data throughput and reliability due to channel noise, fading, and inter-symbol interference, which affects the performance of link quality in next-generation mobile communication and digital broadcasting.
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 the decoding result, a Cyclic Redundancy Check (CRC), and LDPC syndrome, along with interference cancellation or successive interference cancellation techniques in a system requiring encoding or re-encoding for parity, utilizing a parity check matrix.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LDPC decoding is performed to improve reliability, then error correction capability is enhanced, but decoding complexity increases
Solution Approach 1:
The LDPC decoding process is divided into multiple stages: initial decoding to generate preliminary decoded values, syndrome calculation based on these values, and conditional re-decoding only when syndrome indicates errors. This segmentation avoids full-complexity decoding for all packets, reducing average complexity while maintaining reliability.
Solution Approach 2:
Instead of always performing complete LDPC decoding, the system performs partial decoding first to generate initial decoded values, then uses syndrome checking to determine whether full decoding is necessary. This partial action approach reduces computational complexity for packets that don't require full error correction.
2Reliability
If re-encoding is performed based on decoding results to improve reliability, then link performance is enhanced, but processing time increases
Solution Approach 1:
The system performs preliminary decoding to obtain decoded values before final transmission or re-encoding. By preparing decoded values in advance and using syndrome checking to validate them, the system avoids time-consuming re-decoding operations and enables faster re-encoding when needed.
Solution Approach 2:
The syndrome calculation provides feedback on the quality of decoded values. When the syndrome indicates no errors, the system can proceed directly to re-encoding without additional decoding, reducing processing time. When errors are detected, feedback triggers targeted re-decoding only for affected portions.
3Measurement precision
If interference cancellation is applied to improve signal quality, then reception accuracy is enhanced, but computational load increases
Solution Approach 1:
The interference cancellation is applied selectively based on syndrome results. Instead of always performing complex interference cancellation operations, the system applies them only when syndrome checking indicates the presence of errors or interference, reducing average computational load while maintaining reception accuracy when needed.
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.