Sciweavers

Share
GLOBECOM
2010
IEEE

Layered Tabu Search Algorithm for Large-MIMO Detection and a Lower Bound on ML Performance

10 years 10 months ago
Layered Tabu Search Algorithm for Large-MIMO Detection and a Lower Bound on ML Performance
In this paper, we are concerned with low-complexity detection in large multiple-input multiple-output (MIMO) systems with tens of transmit/receive antennas. Our new contributions in this paper are two-fold. First, we propose a lowcomplexity algorithm for large-MIMO detection based on a layered low-complexity local neighborhood search. Second, we 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 i) it is easily obtained for MIMO systems with large number of antennas because of the inherent low complexity of the search algorithm, ii) it is tight at moderate-to-high SNRs, and iii) it can be tightened at low SNRs by increasing the number of symbols in the neighborhood definition. Interestingly, the proposed detection algorithm based on the layered local search achieves bit error performances which are quite close to this lower bound for large number of antennas and higher-order QA...
N. Srinidhi, Tanumay Datta, Ananthanarayanan Chock
Added 11 Feb 2011
Updated 11 Feb 2011
Type Journal
Year 2010
Where GLOBECOM
Authors N. Srinidhi, Tanumay Datta, Ananthanarayanan Chockalingam, B. Sundar Rajan
Comments (0)
books