Soft-output sphere decoding: Performance and implementation aspects


Christoph Studer, Markus Wenk, Andreas Burg, and Helmut Bölcskei


Proc. of Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, pp. 2071-2076, Nov. 2006, (invited paper).

DOI: 10.1109/ACSSC.2006.355132

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Multiple-input multiple-output (MIMO) detection algorithms providing soft information for a subsequent channel decoder pose significant implementation challenges due to their high computational complexity. In this paper, we show how sphere decoding can be used as an efficient tool to implement soft-output MIMO detection with flexible trade-offs between computational complexity and (error rate) performance. In particular, we demonstrate that single tree search, ordered QR decomposition, channel matrix regularization, and log-likelihood ratio clipping are the key ingredients for realizing soft-output MIMO detectors with near max-log performance at a computational complexity that is reasonably close to that of hard-output sphere decoding.


MIMO, soft-output, sphere decoding


Minor corrections compared to the version in the proceedings to reflect that the LLRs in (2) are normalized (to avoid dependence on noise variance) and the clipping constraint in (11) refers to the normalized LLRs.

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