SUMIS: Near-Optimal Soft-In Soft-Out MIMO Detection with Low and Fixed Complexity
2014 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 62, no 12, 3084-3097 p.Article in journal (Refereed) Published
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 a well-defined tradeoff between computational complexity and performance. Apart from an initial sorting step consisting of selecting channel-matrix columns, the algorithm involves no searching nor algorithmic branching; hence the algorithm has a completely predictable run-time and allows for a highly parallel implementation. We numerically assess the performance of SUMIS in different practical settings: full/partial channel state information, sequential/iterative decoding, and low/high rate outer codes. We also comment on how the SUMIS method performs in systems with a large number of transmit antennas.
Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2014. Vol. 62, no 12, 3084-3097 p.
IdentifiersURN: urn:nbn:se:liu:diva-103671DOI: 10.1109/TSP.2014.2303945ISI: 000338122400005OAI: oai:DiVA.org:liu-103671DiVA: diva2:689996