Twisted-Pair Superposition Coding for Low-Complexity Short-Block Decoding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing channel coding methods for Ultra-Reliable Low Latency Communication (URLLC) in 5G networks face challenges in achieving low latency and high performance due to high decoding complexity and inflexible code rate structures, particularly for short block lengths, where codes like BCH and Polar codes require high algorithm complexity and CRC assistance, leading to increased redundancy and inflexibility.
Innovation Solution
The proposed twisted-pair superposition transmission (TPST) coding scheme constructs codes by superimposing basic codes in a twisted manner, using a successive cancellation list decoding algorithm with early termination based on empirical divergence functions, and a rate allocation method to search for codes with good performance within a specific SNR region, eliminating the need for CRC and allowing flexible code rate structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If BCH codes or Polar codes are used for short block length URLLC, then error correction performance is improved, but decoding complexity increases significantly
Solution Approach 1:
The code is segmented into an inner code (TBCC or Polar code) and an outer code (CRC), where each layer performs specific functions. The inner code handles basic error correction while the outer code provides additional protection, allowing the system to achieve high reliability without requiring excessively complex single-stage decoding algorithms.
Solution Approach 2:
The patent employs a composite coding structure combining TBCC/Polar codes with CRC codes. This composite approach leverages the strengths of both code types: the error correction capability of the inner code and the error detection capability of the outer code, achieving near-ML performance with manageable decoding complexity through sequential processing.
2Reliability
If CRC is added as an outer code to assist list decoding, then decoding accuracy is improved, but coding redundancy increases and code rate decreases
Solution Approach 1:
Instead of using full-strength CRC codes that would significantly reduce code rate, the patent employs a simplified outer CRC code with reduced redundancy. This partial action approach provides sufficient error detection capability to distinguish correct candidates in the decoding list while minimizing the impact on code rate and maintaining efficient data transmission.
3Reliability
If TBCC with large encoding memory is used, then error correction performance is improved, but decoding complexity increases due to enormous number of states
Solution Approach 1:
The patent segments the TBCC structure into smaller memory units, reducing the number of states in the trellis from exponential to manageable levels. By using multiple smaller memory sections instead of one large memory, the system achieves comparable error correction performance with significantly reduced decoding complexity and lower computational burden.
4Reliability
If sequential decoding or list decoding algorithms are used to approach RCU bound, then error correction performance is improved, but algorithm complexity increases
Solution Approach 1:
The decoding process is segmented into two distinct stages: first decoding the inner TBCC/Polar code to generate a list of candidate codewords, then using the outer CRC code to identify the correct candidate. This segmentation transforms a single complex sequential decoding problem into two simpler decoding stages, reducing overall algorithm complexity while maintaining performance near the RCU bound.
Data Source
AI summary
The present disclosure discloses a new coding scheme, which is constructed by superimposing together a pair of basic codes in a twisted manner. A SCL decoding algorithm is proposed for the TPST codes, which may be early terminated by a preset threshold on the empirical divergence functions (EDF) to trade off performance with decoding complexity. The SCL decoding of TPST is based on the efficient list decoding of the basic codes, where the correct candidate codeword in the decoding list is distinguished by employing a typicality-based statistical learning aided decoding algorithm. Lower bounds for the two layers of TPST are derived, which may be used to predict the decoding performance and to show the near-ML performance of the proposed SCL decoding algorithm. The construction of TPST codes may be generalised by allowing different basic codes for the two layers.