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Soft-input soft-output (SISO) detection algorithms form the basis foriterative decoding. The computational complexity of SISO detection often posessignificant challenges for practical receiver implementations, in particular inthe context of multiple-input multiple-output (MIMO) wireless communicationsystems. In this paper, we present a low-complexity SISO sphere-decodingalgorithm, based on the single tree-search paradigm proposed originally forsoft-output MIMO detection in Studer, et al., IEEE J-SAC, 2008. The newalgorithm incorporates clipping of the extrinsic log-likelihood ratios (LLRs)into the tree-search, which results in significant complexity savings andallows to cover a large performance/complexity tradeoff region by adjusting asingle parameter. Furthermore, we propose a new method for correctingapproximate LLRs --resulting from sub-optimal detectors-- which (oftensignificantly) improves detection performance at low additional computationalcomplexity.

Soft-Input Soft-Output Single Tree-Search Sphere Decoding