DocumentCode :
2132218
Title :
Low complexity implementations of sphere decoding for MIMO detection
Author :
Shayegh, Farnaz ; Soleymani, Mohammad Reza
Author_Institution :
Electr. & Comput. Eng. Dept., Concordia Univ., Montreal, QC
fYear :
2008
fDate :
4-7 May 2008
Abstract :
A new low complexity sphere decoding method for multiple-input multiple-output (MIMO) maximum-likelihood (ML) detection is proposed. One method that reduces the complexity of sphere decoding is the decoding order of MIMO sphere decoder using the soft-output signal of a suboptimum receiver as a reference. We refer to this method as ordered sphere decoder and we try to reduce its complexity. In order to do this, we use the reliability information of the transmitted vector to do channel ordering. This means that we make decisions on the elements of the transmitted vector starting from its most reliable element. To this end, we arrange the reliabilities in an increasing order. This ordering will define a permutation. The elements of the reference signal and also the columns of the channel matrix will be arranged according to this permutation. Then, we detect the permuted transmitted vector using ordered sphere decoder with the new permuted channel matrix and reference signal. In our proposed method, we start detecting the transmitted vector from its most reliable element and for each element, we start from the most probable transmitted symbol based on the information from the reference signal. This kind of ordering will help finding the candidate transmitted vectors quickly. Our method results in reducing the complexity of sphere decoder specially in low signal to noise ratios without compromising the performance of ML detection.
Keywords :
MIMO communication; maximum likelihood decoding; maximum likelihood estimation; receivers; telecommunication channels; MIMO detection; channel matrix; multiple-input multiple-output maximum-likelihood detection; sphere decoding; suboptimum receiver; vector detection; Data communication; Error correction; Lattices; MIMO; Maximum likelihood decoding; Maximum likelihood detection; Polynomials; Signal to noise ratio; Transmitting antennas; Wireless communication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on
Conference_Location :
Niagara Falls, ON
ISSN :
0840-7789
Print_ISBN :
978-1-4244-1642-4
Electronic_ISBN :
0840-7789
Type :
conf
DOI :
10.1109/CCECE.2008.4564650
Filename :
4564650
Link To Document :
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