By Topic

Training sequence and memory length selection for space-time Viterbi equalization

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)
Chih-Sheng Chou ; Department of Electronics Engineering, National Chiao-Tung University, Hsinchu, Taiwan ; David W. Lin

We consider signal and receiver design for space-time Viterbi equalization for wireless transmission. We propose a search method to find good training sequences, termed min-norm training sequences, for least-square channel estimation. Compared to either a maximum-length sequence or a randomly generated training sequence, the training sequence obtained can drastically reduce the channel estimation error. We also derive a simple lower bound on the achievable channel estimation error of any training sequence. Knowledge of this lower bound helps the search for min-norm training sequences in that it facilitates a measure of the goodness of the best sequence examined so far. For operation under the situation with unknown channel response lengths, we propose a simple method to select the memory length (tap number) in the Viterbi equalizer based on the SNR of the received signal. The resulting equalization performance is found to be comparable with the case where a preset, fixed memory length is used. However, the proposed method often results in use of a smaller tap number, which translates into a reduction in the computational complexity. Simulation results show that at symbol error rate below 10 (SNR > 5 dB) the amount of complexity reduction is of the order of 5% to 25% on the average, for typical wireless channels.

Published in:

Journal of Communications and Networks  (Volume:2 ,  Issue: 4 )