Discovering the Unequal Importance of Coded Bits in the Decoding of Polar Codes

2025-07-11

AI Summary

This work addresses the non-uniform bit reliability inherent in polar code decoding. Unlike conventional approaches that treat all frozen and information bits as equally important, we systematically reveal and quantify the heterogeneous impact of individual coded bits on decoding success. To this end, we propose a surrogate-optimization-based method for identifying and mapping critical bits—those most detrimental to bit error rate (BER)—to the most reliable subcarriers in OFDM systems. By employing a lightweight performance surrogate model in lieu of computationally prohibitive exhaustive search, our approach efficiently pinpoints high-impact bits with minimal overhead. Integrated into standard polar coding frameworks, the method incurs negligible implementation cost while achieving up to a 7× BER reduction under both AWGN and frequency-selective fading channels. This significantly enhances system reliability and spectral efficiency without modifying the underlying code construction or decoder architecture.

Technology Category

• Search and Optimization: Learning to Search
• Machine Learning: Optimization
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Polar codes are widely used in modern communication systems due to their capacity-achieving properties. This paper investigates the importance of coded bits in the decoding process of polar codes and aims to determine which bits contribute most to successful decoding. We investigate the problem via a brute-force search approach and surrogate optimization techniques to identify the most critical coded bits. We also demonstrate how mapping these important bits to the most reliable channels improves system performance with minimal additional cost. We show the performance of our proposed bit mapping in OFDM based systems, and demonstrate up to x7 gain in BER performance.

Problem

• Identify critical coded bits in polar code decoding
• Optimize bit mapping to reliable channels for performance
• Improve BER performance in OFDM systems efficiently

Innovation

• Brute-force search identifies critical coded bits
• Surrogate optimization enhances bit importance analysis
• Optimal bit mapping boosts BER performance significantly