LAUSR

Decentralized baseband processing (DBP) architectures can alleviate the extremely high interconnect data rates and chip input/output (I/O) bandwidth bottlenecks of the conventional centralized massive multiple-input multiple-output (M-MIMO) system. Nonetheless, fully decentralized (FD) detectors suffer significant performance loss compared with the centralized counterparts due to the constrained information-sharing between antenna clusters, especially for systems with a large number of antenna clusters and/or high-order modulation. In this article, we propose an enhanced message-passing-based FD detection method by utilizing an information-lossless factor graph (FG) transformation scheme. As an illustrative example, the expectation propagation (EP) algorithm is considered in this work. In each antenna cluster, the FG is transformed to a less-loopy one and the effective interference of users is suppressed. Based on the message-passing principle of the EP algorithm, we devise an efficient non-linear fusion scheme in the central processing unit (CPU). In addition, a compensation factor accounting for the cluster profile is introduced to mitigate the inaccuracy of message-passing caused by DBP, thus further enhancing the detection performance. Numerical results demonstrate that the proposed enhanced FD detector obtains significantly better performance than the counterpart with even lower computational complexity, especially in a large number of antenna clusters and/or high-order modulation scenarios.