On reduced-complexity soft demapping in MIMO systems with spatial multiplexing

We present a low complexity soft detection scheme well-suited to multi-input multi-output (MIMO) systems based on spatial domain multiplexing leading to layered space-time or space-frequency architecture. The proposed algorithm is based on trellis representation of the MIMO signals and a subsequent formulation of constrained-delay maximum a posterior (MAP) detection in conjunction with soft decision feedback (SDF). Decision feedback is broken into causal and noncausal parts in an effort to maximize the observation window while maintaining a reasonable computational load. Error rate simulations are conducted in the context of turbo-like iterative demapping and decoding (IDD). The resulting performance and required complexity are compared with those of maximum likelihood (ML) detection, sphere detection (SD), as well as the vertical BLAST (V-BLAST) processing scheme. We observe excellent performance/complexity tradeoffs with the proposed soft detection scheme for a number of modulation/channel scenarios.