# Information Bottleneck Decoding of Rate-Compatible 5G-LDPC Codes

## TL;DR

This paper introduces an information bottleneck-based decoding method for 5G LDPC codes that improves performance under low-precision constraints, achieving near double-precision decoding accuracy with reduced complexity.

## Contribution

It extends the IB decoding approach to rate-compatible PBRL LDPC codes, including puncturing, and demonstrates effective decoding with only 4-bit messages.

## Key findings

- Outperforms offset min-sum decoding algorithms.
- Operates within 0.2 dB of double-precision belief propagation.
- Effective for various code rates in 5G standards.

## Abstract

The new 5G communications standard increases data rates and supports low-latency communication that places constraints on the computational complexity of channel decoders. 5G low-density parity-check (LDPC) codes have the so-called protograph-based raptor-like (PBRL) structure which offers inherent rate-compatibility and excellent performance. Practical LDPC decoder implementations use message-passing decoding with finite precision, which becomes coarse as complexity is more severely constrained. Performance degrades as the precision becomes more coarse. Recently, the information bottleneck (IB) method was used to design mutual-information-maximizing lookup tables that replace conventional finite-precision node computations. Additionally, the IB approach exchanges messages represented by integers with very small bit width. This paper extends the IB principle to the flexible class of PBRL LDPC codes as standardized in 5G. The extensions includes puncturing and rate-compatible IB decoder design. As an example of the new approach, a 4-bit information bottleneck decoder is evaluated for PBRL LDPC codes over a typical range of rates. Bit error rate simulations show that the proposed scheme outperforms offset min-sum decoding algorithms and operates within 0.2 dB of double-precision sum-product belief propagation decoding.