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