Serial and Parallel LLR Updates Using Damped LLR for LDPC Coded Massive MIMO Detection with Belief Propagation

Shuhei TANNO  Toshihiko NISHIMURA  Takeo OHGANE  Yasutaka OGAWA  

IEICE TRANSACTIONS on Communications   Vol.E100-B   No.8   pp.1277-1284
Publication Date: 2017/08/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.2016FGP0012
Type of Manuscript: Special Section PAPER (Special Section on Radio Access Technologies for 5G Mobile Communications System)
Category: Wireless Communication Technologies
massive MIMO,  belief propagation,  LDPC code,  factor graph,  bipartite graph,  tripartite graph,  

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Detecting signals in a very large multiple-input multiple-output (MIMO) system requires high complexy of implementation. Thus, belief propagation based detection has been studied recently because of its low complexity. When the transmitted signal sequence is encoded using a channel code decodable by a factor-graph-based algorithm, MIMO signal detection and channel decoding can be combined in a single factor graph. In this paper, a low density parity check (LDPC) coded MIMO system is considered, and two types of factor graphs: bipartite and tripartite graphs are compared. The former updates the log-likelihood-ratio (LLR) values at MIMO detection and parity checking simultaneously. On the other hand, the latter performs the updates alternatively. Simulation results show that the tripartite graph achieves faster convergence and slightly better bit error rate performance. In addition, it is confirmed that the LLR damping in LDPC decoding is important for a stable convergence.