Method and System for Reliable Data Communications with Adaptive Multi-Dimensional Modulations for Variable-Iteration Decoding

Abstract

In an advanced adaptive modulation and coding (AMC) scheme, the code rate and the parity-check matrix (PCM) for low-density parity-check (LDPC) codes are adapted according to modulation formats and variable-iteration receivers. The degree distribution for the PCM adaptation is designed by heuristic optimization to minimize the required SNR via an extrinsic information transfer (EXIT) trajectory analysis for finite-iteration decoding. The method uses dynamic window decoding by generating spatially coupled PCM for quasi-cyclic LDPC convolutional coding. The method also provides a way to jointly optimize labeling and decoding complexity for high-order and high-dimensional modulations. The problem to use a large number of different LDPC codes for various modulation formats and variable-iteration decoding is also dealt with by linearly dependent PCM adaptation across iteration count to keep using a common generator matrix. This PCM adaptation can improve a convergence speed of belief propagation decoding and mitigate an error floor issue.

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