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Minimum-Integer Computation Finite Alphabet Message Passing Decoder: From Theory to Decoder Implementations towards 1

Tobias Monsees1, Oliver Griebel2, Matthias Herrmann2

  • 1Department of Communications Engineering, University of Bremen, 28359 Bremen, Germany.

Entropy (Basel, Switzerland)
|July 8, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces the Minimum-Integer Computation (MIC) decoder for Low-Density Parity Check (LDPC) codes, achieving high communication performance with reduced complexity. The novel MIC decoder offers superior efficiency and performance compared to existing methods for high-throughput applications.

Keywords:
LDPC codedecodingfinite alphabet message passingimplementation efficiencyinformation bottleneck

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Area of Science:

  • Digital Communications
  • Error Correction Coding
  • VLSI Design

Background:

  • Message Passing (MP) decoding in Low-Density Parity Check (LDPC) codes involves exchanging extrinsic information between Check Nodes (CNs) and Variable Nodes (VNs).
  • Practical implementations face limitations due to message quantization, typically using a small number of bits.
  • Finite Alphabet Message Passing (FA-MP) decoders aim to maximize Mutual Information (MI) with low bit precision, approaching high-precision Belief Propagation (BP) performance.

Purpose of the Study:

  • To develop a novel Minimum-Integer Computation (MIC) decoder design for LDPC codes.
  • To replace complex multidimensional Lookup Tables (mLUTs) with efficient low-bit integer computations.
  • To achieve communication performance equivalent to mLUT decoders with significantly lower implementation complexity.

Main Methods:

  • Leveraging the framework of Mutual Information-Maximizing Quantized Belief Propagation (MIM-QBP) and Reconstruction-Computation-Quantization (RCQ).
  • Utilizing the Log-Likelihood Ratio (LLR) separation property for information maximizing quantizers.
  • Deriving a criterion for bit resolution to exactly represent mLUT mappings and implementing low-bit integer computations.

Main Results:

  • The MIC decoder achieves the exact communication performance of the corresponding mLUT decoder.
  • Demonstrated significantly lower implementation complexity compared to mLUT-based decoders.
  • Outperformed previous FA-MP and Min-Sum (MS) decoders in routing complexity, area, and energy efficiency in 28 nm FD-SOI technology.

Conclusions:

  • The MIC decoder offers a highly efficient solution for LDPC decoding, balancing performance and complexity.
  • This design is suitable for high-throughput applications, such as those requiring up to 1 Tb/s.
  • The MIC decoder represents a significant advancement in energy-efficient and area-efficient digital communication systems.