Memory-Reduced Look-Up Tables for Efficient ADMM Decoding of LDPC Codes

This is the authors' abstract. We don't add key points for this paper.

The Euclidean projection involved in the decoding of low-density parity-check (LDPC) codes with the alternating direction method of multipliers (ADMM) can be simplified by jointly using uniform quantization and look-up tables (LUTs). However, the memory requirement for the original LUT-based ADMM decoding is comparatively large. In this letter, a nonuniform quantization method is proposed to save the memory cost by minimizing the mean square error of the outputs of Euclidean projections during quantization. Simulation results over two exemplified LDPC codes show that the proposed method can achieve similar error-rate performances when compared with the original LUT-based ADMM decoding by using significantly less memory units.