By Topic

Space-time block codes: ML detection for unknown channels and unstructured interference

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

3 Author(s)
Larsson, E.G. ; Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA ; Stoica, Petre ; Jian Li

Space-time coding (STC) schemes for communication systems employing multiple transmit and receive antennas have been attracting increased attention. The so-called linear space-time block codes (STBC) have been of particular interest due to their good performance and low decoding complexity. In this paper we take a systematic maximum-likelihood (ML) approach to the decoding of STBC for unknown propagation channels and unknown noise and interference conditions. We derive a low-complexity ML decoding algorithm based on cyclic maximization of the likelihood function. Furthermore, we discuss the design of optimal training sequences and optimal information transfer to an outer decoder. Numerical examples demonstrate the performance of our algorithm.

Published in:

Signals, Systems and Computers, 2001. Conference Record of the Thirty-Fifth Asilomar Conference on  (Volume:2 )

Date of Conference:

4-7 Nov. 2001