Enhanced Successive Cancellation List Decoder for Long Polar Codes Targeting 6G Air Interface

2025-08-22

AI Summary

To address the high memory overhead and computational complexity of long polar codes (e.g., 8K) in successive-cancellation list (SCL) decoding for 6G air interfaces, this paper proposes a high-performance, low-overhead enhanced SCL decoding framework. Our method introduces three key innovations: (1) bias-enhanced SCL to improve path selection accuracy; (2) a generalized block-wise SCL architecture enabling flexible-granularity parallel decoding; and (3) input-distribution-aware adaptive decoding with simplified perturbation enhancement, achieving channel adaptation and effective list-size compression. Experimental results demonstrate that, for an 8K polar code with list size $L = 4$, the proposed decoder reduces memory consumption by 67% and cuts computational complexity by up to 5.4× compared to a conventional SCL decoder with $L = 16$, while incurring only a marginal 0.05 dB degradation in bit-error-rate performance. This yields substantial improvements in hardware energy efficiency.

Technology Category

• Machine Learning: Hardware-aware ML
• Search and Optimization: Learning to Search
• Natural Language Processing: Learning & Optimization for NLP

Application Category

• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Security and Privacy: Large-scale security measurements
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

The 6th generation communication standard's air interface requires innovation in channel coding to fulfill anticipated energy and area cost reduction requirements. In this paper, we propose algorithmic techniques to enable the implementation of long polar codes (e.g., length 8K bits) in next-generation communications standards by addressing key challenges in memory usage and computational complexity presented by successive decoding list (SCL) polar decoding. Perturbation-enhanced (PE) successive cancelation list (SCL) decoders with a list size of $L$ reach the decoding performance of the SCL decoder with a list size of $2L$. The proposed bias-enhanced (BE) SCL decoders, which simplifies the PE SCL decoder based on insights gained by an ablation study, returns similar decoding performance to PE SCL decoders. Also, proposed BE generalized partitioned SCL (GPSCL) decoders with a list size of $8$ have a $67%$ reduction in the memory usage and similar decoding performance compared to SCL decoders with a list size of $16$. Furthermore, input-distribution-aware (IDA) decoding is applied to BE GPSCL decoders. Up to $5.4 imes$ reduction in the computational complexity is achieved compared to SCL decoders with a list size of $16$. The degraded decoding performance is at most $0.05 ext{ dB}$ compared to BE GPSCL decoders without IDA decoding.

Problem

• Reducing memory usage in long polar codes decoding
• Lowering computational complexity for 6G air interface
• Maintaining performance while simplifying decoder architecture

Innovation

• Perturbation-enhanced SCL decoders double list efficiency
• Bias-enhanced SCL decoders simplify architecture maintaining performance
• Input-distribution-aware decoding reduces complexity 5.4 times