Convergence Optimized Joint Detection and Decoding for LDPC Coded SC-MIMO Systems

With the increasing requirement for high-speed transmission, multiple input multiple out (MIMO) technologies have been proposed. Beneficial from low peak-to-average power ratio (PAPR), single carrier (SC) MIMO systems are suitable for long-distance transmission. However, one of the significant challenges of SC-MIMO systems is the vast complexity of channel equalization and signal detection, especially for the intersymbol interference (ISI) caused by the frequency-selective fading channels. Due to acceptable complexity and near maximum likelihood (ML) detection performance, the Gaussian approximate interference (GAI) based belief propagation (BP) algorithm has attracted lots of attention. With the help of extrinsic information feedback from low-density parity check (LDPC) codes, iterative detection and decoding (IDD) scheme has been proposed, which has a near to approximate maximum a posterior (MAP) detection performance. Nevertheless, the IDD scheme still suffers from relatively slow convergence resulting from complex connections on the factor graph. Combined with the joint detection and decoding (JDD) scheme and two optimization methods, namely dynamic message damping and layered message updating, a convergence optimized joint detection and decoding (CO-JDD) algorithm is proposed in this paper. Evaluation results show that the proposed CO-JDD algorithm has 2dB bit error rate (BER) performance gains compared with IDD scheme. Besides, the proposed CO-JDD algorithm also has a 70% iteration reduction compared with the IDD scheme.