By Topic

Low complexity implementations of sphere decoding for MIMO detection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Farnaz Shayegh ; Electrical and Computer Engineering Department, Concordia University, Montreal, Quebec, Canada ; Mohammad Reza Soleymani

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.

Published in:

Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on

Date of Conference:

4-7 May 2008