Cart (Loading....) | Create Account
Close category search window
 

A polynomial complexity algorithm for near-optimal signal detection in linear Gaussian vector channels

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
$31 $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)
Qingyi Quan ; Key Lab. of Universal Wireless Commun., WSPN Lab., Beijing Univ. of Posts & Telecommun., Beijing, China ; Suzi Xie

A near-optimal signal detection algorithm with complexity of O(K log K) is proposed for K -input, K -output linear Gaussian vector channels. The proposed algorithm is based on the searching for a monotone sequence with maximum likelihood, under the ranking of sufficient statistics. It is proved that the algorithm can reach the optimal detection result in the case that all cross-correlation values in the linear Gaussian vector channel are identical. Also some simulation results are provided for the case that the crosscorrelation values are different. The simulation results show that the performance of the proposed algorithm degrades with the divergence of the cross-correlation values in the linear vector channels. Finally, a method of modifying the correlation matrix is suggested by an example. In this method, a transformation is derived for reducing the divergence of the cross-correlation values of the correlation matrix. A simulation result shows that the proposed algorithm is enhanced further with the transformation.

Published in:

Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on  (Volume:9 )

Date of Conference:

9-11 July 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.