Informed message update for iterative MIMO demapping and turbo decoding

Dan Zhang, I-Wei Lai, Konstantinos Nikitopoulos, Gerd Ascheid

Abstract: In this paper, the iterative scheduling issue for multiple-input multiple-output (MIMO) systems with turbo codes is addressed based on the informed asynchronous scheduling, initially used for scheduling low-density parity-check (LDPC) decoding. For the iterative MIMO demapping and turbo decoding, the convergence behavior by using the informed asynchronous scheduling is first demonstrated to be similar to the standard sequential scheduling. As the extrinsic log-likelihood ratio (LLR) calculation at both the MIMO demapper and turbo decoder costs high complexity, an informed message update (IMU) rule is further proposed to select only a subset of extrinsic LLRs for updates within each iteration. By avoiding the re-calculations for the extrinsic LLRs with small changes between successive iterations, significant complexity savings are achieved with negligible error rate performance loss.