Masked Distributed CRC Coding for Early-Terminating Polar Decoding
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Solution Overview
Problem
Current error detection coding methods, particularly in polar codes for 5G New Radio (NR) control channels, face challenges in efficient error detection and decoding, leading to high computational complexity and latency, especially in blind detection scenarios where early termination of decoding is not feasible with iterative codes like Turbo, convolutional, and LDPC codes.
Innovation Solution
The implementation of distributed cyclic redundancy check (CRC) codes, where multiple CRCs are calculated and distributed across the codeword, allowing for early termination of decoding upon failure detection in polar codes using Successive Cancellation (SC) or List decoding, reducing computational load and latency by enabling CRC checks during partial decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If distributed CRC codes are implemented in polar codes, then decoding latency and power consumption are reduced through early termination, but device complexity increases due to multiple CRC calculations and distribution
Solution Approach 1:
The information block is divided into multiple segments, each with its own CRC code. This segmentation allows the decoder to check CRCs independently for each segment, enabling early termination when a segment fails validation without needing to decode the entire block, thus reducing decoding latency and power consumption.
Solution Approach 2:
CRC codes are calculated and attached to each segment before encoding. This preliminary attachment of error detection codes to individual segments enables the receiver to perform validation checks during the decoding process, allowing early termination upon detecting errors in any segment, thereby reducing overall decoding time and energy consumption.
2Measurement precision
If multiple distributed CRCs are used for error detection, then detection accuracy improves, but false-alarm rate and missing detection rate performance may deteriorate
Solution Approach 1:
By dividing the information block into segments with individual CRC codes, the system achieves finer-grained error detection. Each segment's CRC independently validates its portion, improving overall detection accuracy while maintaining reliable performance through the collective validation of all segments.
Data Source
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AI summary
A first error-detecting code (EDC) is computed based on a first segment of a block of information that is to be encoded, and a second EDC is computed based on at least a second segment of the block of information. The first EDC is masked with a first masking segment and the second EDC with a second masking segment to generate a first masked EDC and a second masked EDC. The first masking segment and the second masking segment are associated with a target receiver of the block of information. A codeword is generated based on a code and an input vector that includes the first segment, the first masked EDC, the second segment, and the second masked EDC. This type of coding could be useful to support early termination of blind detection at a decoder, for example.