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In this paper, the authros are concerned with low-complexity detection in large Multiple-Input Multiple-Output (MIMO) systems with tens of transmit/receive antennas. Their new contributions in this letter are two-fold. First, they propose a low-complexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, they obtain a lower bound on the Maximum-Likelihood (ML) bit error performance using the local neighborhood search. The advantages of the proposed ML lower bound are: it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, it is tight at moderate-to-high SNRs, and it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition.
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