LDPC Receiver Decoding with Interference Cancellation for Noisy Signals
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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, particularly in high-speed digital communication systems that require high data throughput and reliability.
Innovation Solution
The method involves performing low-density parity check (LDPC) decoding and subsequent interference cancellation or successive interference cancellation using a receiver, which includes a transceiver and a controller for processing signals and determining LDPC syndrome values to remove interference and improve decoding accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LDPC decoding is performed to improve decoding accuracy in noisy environments, then reliability is improved, but device complexity increases due to the need for syndrome calculation and interference cancellation mechanisms
Solution Approach 1:
The decoding process is segmented into distinct functional modules: syndrome calculation unit, CRC check unit, interference cancellation unit, and successive 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 calculation is performed preliminarily before the main decoding process. By calculating the syndrome value in advance and using it to guide subsequent interference cancellation operations, the system prepares necessary information beforehand to improve decoding efficiency and accuracy without adding excessive complexity during the main processing stage.
2Reliability
If interference cancellation is performed to remove noise and fading effects, then signal quality is improved, but loss of time increases due to additional processing steps
Solution Approach 1:
The syndrome calculation is performed preliminarily before the main decoding process. By calculating the syndrome value in advance and using it to guide subsequent interference cancellation operations, the system prepares necessary information beforehand to improve decoding efficiency and accuracy without adding excessive complexity during the main processing stage.
Solution Approach 2:
The decoder uses feedback mechanisms where CRC check results and syndrome values are fed back to guide the interference cancellation process. This feedback allows the system to adaptively adjust decoding operations based on detected error patterns, improving signal quality while avoiding unnecessary processing steps.
3Adaptability or versatility
If successive interference cancellation is implemented to handle multiple layers, then adaptability is improved, but device complexity increases due to multiple decoding passes
Solution Approach 1:
The decoding process is segmented into distinct functional modules: syndrome calculation unit, CRC check unit, interference cancellation unit, and successive 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 decoder is designed with universal functionality to handle multiple signal layers through successive interference cancellation. The same core decoding modules are reused across different layers, with each layer processed through the same syndrome calculation and interference cancellation sequence, making the system adaptable to multi-layer configurations without requiring entirely separate decoding paths for each layer.
Data Source
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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 first parity bits to determine second parity bits; identifying a part of the first LDPC information bits, and decoding a second layer signal.