By Topic

Multiuser Transmit Beamforming Design for SINR Maximization in Cooperative MIMO Systems

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)
Songnan Xi ; School of Electrical and Computer Engieering, Purdue University, ; Michael D. Zoltowski

Multiusermultiple-input multiple-output (MIMO) systems are considered in this paper. Increasing interest in cooperative communication has made it of great significance to explore howto utilize, at multiple transmitters, the full multiuser channel state information, which is the collection of the channel state information between each of the users and the base station. Thus, we continue our research on uplink transmit beamforming design for multiple users inMIMO systems, assuming complete cooperation among users such that the full multiuser channel state information is known not only to the receiver but also to all the transmitters. We propose an algorithm for designing optimal beamforming weights in terms of maximizing the signal-to-interference-noise ratio (SINR). Through statistical modelling, we decouple the original mathematically intractable optimization problem and achieved a closed-form solution. As in our previous work, the minimum mean-squared error (MMSE) receiver with ordered successive interference cancellation (SIC) is adopted for multiuser detection. The proposed scheme is compared with the jointly optimized transceiver design and our previously proposed eigen-beamforming algorithm. Simulation results demonsrate that our algorithm, with much less computational burden than the jointly optimized approach, accomplishes either almost the same or even better performance than the jointly optimized transceiver for various MIMO channels, and always works better than our previously proposed algorithm.

Published in:

2007 IEEE/SP 14th Workshop on Statistical Signal Processing

Date of Conference:

26-29 Aug. 2007