Polar SCL Decoding With Soft Outputs From Candidate Distances
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Solution Overview
Problem
Current polar code decoders, such as SC and SCL, primarily provide hard-decision outputs, with soft-output methods like SCAN and BP being computationally expensive and requiring multiple iterations.
Innovation Solution
Modifying the SCL decoder to produce soft-outputs by comparing a list of candidate codewords against the noisy codeword received, calculating soft-outputs based on the distance differences of closest candidate codewords, and optionally using cyclic redundancy checks (CRC) to validate decoding paths and prevent error propagation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If soft-output methods like SCAN and BP are used to improve error correction performance, then reliability is improved, but device complexity and computational cost increase significantly
Solution Approach 1:
The patent segments the decoding process into two distinct phases: (1) generating a list of candidate codewords using modified SCL decoding, and (2) computing soft-outputs by comparing these candidates against the received signal. This segmentation allows the system to avoid the iterative complexity of SCAN and BP methods while achieving soft-output functionality through a single-pass candidate evaluation process.
Solution Approach 2:
The patent employs cyclic redundancy checks (CRC) as a disposable validation mechanism to quickly eliminate invalid candidate codewords without requiring complex iterative computations. The CRC serves as a lightweight filter that discards erroneous candidates early in the process, preventing error propagation and reducing the computational burden of subsequent soft-output calculations.
2Measurement precision
If multiple iterations are performed to generate soft-outputs, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary action by generating and validating a list of candidate codewords before computing the final soft-outputs. The modified SCL decoding phase pre-processes the received signal to identify plausible candidates, and CRC validation pre-filters these candidates to ensure correctness. This preliminary processing eliminates the need for multiple iterative passes, achieving accurate soft-outputs in a single computational stage.
3Reliability
If CRC validation is applied to all candidate codewords, then reliability is improved, but productivity decreases due to additional validation steps
Solution Approach 1:
The patent applies partial action by performing CRC validation selectively rather than exhaustively on all possible codeword combinations. The modified SCL decoding generates a limited list of candidate codewords (typically L candidates where L is small, e.g., 4 or 8), and CRC validation is applied only to these pre-selected candidates. This partial validation approach maintains high reliability by filtering erroneous candidates while preserving productivity by avoiding comprehensive validation of the entire code space.
Data Source
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AI summary
A receiver includes a polar decoder for decoding an encoded codeword transmitted over a communication channel. The receiver includes a front end to receive over a communication channel a codeword including a sequence of bits modified with noise of the communication channel and a soft decoder operated by a processor to produce a soft output of the decoding. The codeword is encoded by at least one polar encoder with a polar code. The processor is configured to estimate possible values of the bits of the received codeword using a successive cancelation list (SCL) decoding to produce a set of candidate codewords, determine a distance between each candidate codeword and a soft input to the soft decoder, and determine a likelihood of a value of a bit in the sequence of bits using a difference of distances of the candidate codewords closest to the received codeword and having opposite values at the position of the bit.