@inproceedings{aa67f9ef22564872bb3f193871c3e8df,
title = "A low-complexity near-ml decoding technique via reduced dimension list stack algorithm",
abstract = "In this paper, we propose a near maximum likelihood (ML) decoding technique, which reduces the computational complexity of the exact ML decoding algorithm. The computations needed for the tree search in the ML decoding is simplified by reducing the dimension of the search space prior to the tree search. In order to compensate performance loss due to the dimension reduction, a list stack algorithm (LSA) is considered, which produces a list of the top K closest points. The combination of both approaches, called reduced dimension list stack algorithm (RD-LSA), is shown to provide flexibility and offers a performance-complexity trade-off. Simulations performed for V-BLAST transmission demonstrate that significant complexity reduction can be achieved compared to the sphere decoding algorithm (SDA) while keeping the performance loss below an acceptable level.",
keywords = "Dimension reduction, MIMO, Maximum likelihood, Sphere decoding, Tree search",
author = "Jun, {Won Choi} and Shim Byonghyo and Singer, {Andrew C.} and Nam, {Ik Cho}",
year = "2008",
doi = "10.1109/SAM.2008.4606820",
language = "English",
isbn = "9781424422418",
series = "SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop",
pages = "41--44",
booktitle = "SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop",
note = "SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop ; Conference date: 21-07-2008 Through 23-07-2008",
}