By Topic

Statistical learning and layered space-time architecture for point-to-point wireless communications

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)
M. Sellathurai ; McMaster Univ., Hamilton, Ont., Canada ; S. Haykin

The Bell Labs Layered Space-Time (BLAST) architecture has been proposed for high-capacity and spectrally-efficient wireless communications in an indoor environment. The method relies on multi-transmit and receive antennas to send and receive information-bearing signals in parallel. The architecture assumes a rich independent-ray scattering mechanism to make the parallel information separable at the receiving ends. In practice, with the increased number of parallel sub-streams, the scattering may be less favorable so that signal decoding algorithms are needed. We propose a statistical learning demodulating scheme for this task.

Published in:

Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on  (Volume:2 )

Date of Conference:

1-4 Nov. 1998