Guided Search MIMO Detectors Aided by Lattice Reduction
Yuri Mendes Mostagi, Taufik Abrão & Paul Jean E. Jeszensky
Evento: XXX Simpósio Brasileiro de Telecomunicações (SBrT2012)
Keywords: MIMO systems ML estimation; sub-optimum de- tection search algorithms Lattice Reduction
AbstractUnder MIMO channels, the matched filter detection becomes inefficient to deal with high data throughput demanding systems. The performance or system capacity under conventional detection will be substantially degraded when the spatial diversity provided by multiple antennas can not be fully exploited and the detection process is unable to efficiently separate the signal from each antenna. The solution discussed in this paper seeks to establish more efficient detectors for MIMO systems with the aid of the lattice reduction (LR) technique. These detectors use information from the interfering signals in a way to improve the signal detection in the antenna of interest, thus providing advantages over the conventional system, at the expense of in- creasing complexity. The focus of this paper consists in comparing the characteristics of three representative sub-optimal detectors based on the maximum-likelihood function as well as on the guided search principle, previously analyzed in . In this way, the complexity × performance trade-off for the sphere detector (SD), the QR decomposition-based detector (QRD) the greedy search detector (GSD) and its variants, all of them aided (or not) by the LR technique are analyzed and its potential of use in MIMO systems is put in perspective.