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

  • TANNO Shuhei
    Graduate School of Information Science and Technology, Hokkaido University
  • NISHIMURA Toshihiko
    Graduate School of Information Science and Technology, Hokkaido University
  • OHGANE Takeo
    Graduate School of Information Science and Technology, Hokkaido University
  • OGAWA Yasutaka
    Graduate School of Information Science and Technology, Hokkaido University

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<p>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.</p>

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