Wireless Receiver Decoding with Alternative Path Integrity Checks
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Solution Overview
Problem
Conventional decoding methods in wireless communications networks are inefficient due to channel impairments and insufficient protection, leading to errors in decoded messages.
Innovation Solution
A method and system that generates an active state metric matrix, calculates a differential metric matrix, identifies maximum likelihood and alternative paths, and examines the integrity of decoded data strings to obtain a correct decoded data string, utilizing a Maximum Likelihood decoder and an Error Detection Code decoder.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional decoding methods are used, then the decoding process is simple, but decoding efficiency is low and errors occur due to channel impairments and insufficient protection
Solution Approach 1:
The patent performs preliminary error detection using CRC before committing to full decoding resources. By checking the syndrome value early in the process, the system can identify erroneous codewords and request retransmission before investing significant computational resources in decoding, thus improving both efficiency and reliability
Solution Approach 2:
The patent implements a feedback mechanism where the CRC check results are used to control the decoding process. If the syndrome value indicates an error, the system feeds back this information to trigger a retransmission request, creating a closed-loop system that adapts to channel conditions and improves overall decoding accuracy
2Reliability
If maximum likelihood decoding is used, then decoded data accuracy is improved, but system resource consumption increases
Solution Approach 1:
The patent applies partial maximum likelihood decoding by first performing a lightweight CRC check (partial action) before committing to full ML decoding. This two-stage approach applies decoding effort selectively - only when necessary - thereby reducing overall resource consumption while maintaining accuracy when errors are present
Solution Approach 2:
The patent segments the decoding process into distinct stages: syndrome calculation, CRC error detection, and conditional ML decoding. By dividing the process into manageable segments with clear decision points, the system can allocate resources efficiently at each stage rather than committing all resources upfront
3Reliability
If error detection code is applied, then data integrity is improved, but decoding time and resource usage increase
Solution Approach 1:
The patent performs error detection using CRC as a preliminary step before full decoding. By calculating the syndrome value and checking for errors early in the process, the system can quickly identify and handle erroneous packets without investing time in complete decoding of corrupted data
Solution Approach 2:
The patent extracts and handles error detection separately from the main decoding process. By isolating the CRC check as a distinct, lightweight operation that can be performed independently, the system minimizes the time impact on the overall decoding pipeline while maintaining data integrity
Data Source
AI summary
Techniques are provided herein to improve the decoding efficiency in a wireless receiver to obtain a correctly decoded data string. A state metric matrix from a received codeword is used to generate active state metric matrices for time instances of the received codeword, and then a differential metric matrix is generated from information in the active state metric matrices. Based on the differential metric matrix a maximum likelihood path and one or more alternative paths are identified. A first decoded data string corresponding to the maximum likelihood path and a plurality of second decoded data strings corresponding to the one or more alternative paths are derived. Integrity of the respective decoded data strings is examined to obtain the correct decoded data string based on the first and second decoded data strings.