SUMIS: Near-Optimal Soft-In Soft-Out MIMO Detection With Low and Fixed Complexity
作者：
关键词: Sorting 、 Subspace topology 、 Mathematical optimization 、 Channel state information 、 Decoding methods 、 Algorithm 、 Computational complexity theory 、 Mathematics 、 MIMO 、 Signal processing 、 Interference (wave propagation)
摘要: The fundamental problem of interest here is soft-input–soft-output multiple-input–multiple-output (MIMO) detection. We propose a method, referred to as subspace marginalization with interference suppression (SUMIS), that yields unprecedented performance at low and fixed (deterministic) complexity. Our method provides well-defined tradeoff between computational complexity performance. Apart from an initial sorting step consisting selecting channel-matrix columns, the algorithm involves no searching nor algorithmic branching; hence has completely predictable run-time allows for highly parallel implementation. numerically assess SUMIS in different practical settings: full/partial channel state information, sequential/iterative decoding, low/high rate outer codes. also comment on how performs systems large number transmit antennas.
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