By Topic

Joint sequence detection and phase estimation using the EM algorithm

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)
Nassar, C.R. ; Dept. of Electr. Eng., McGill Univ., Montreal, Que., Canada ; Soleymani, M.R.

In burst communications, each burst of data arrives with a different, unknown carrier phase. Traditional methods of data detection in the presence of unknown phase are inappropriate here. Recently, several authors have proposed a variety of methods to detect data bursts with an unknown phase. One very successful method is based on the EM algorithm, an iterative statistical method. In our paper, we show that data recovery with the EM algorithm corresponds to carrying out joint maximum likelihood (ML) data detection and phase estimation using an iterative method. At a time when the EM algorithm is growing in both popularity and applicability, this paper provides an important engineering perspective on the EM algorithm, putting it in a traditional detection and estimation framework. Additionally, this paper offers novel, alternative methods to tackle the limitations of the EM algorithm, and presents new, detailed simulation results demonstrating its quality performance

Published in:

Electrical and Computer Engineering, 1994. Conference Proceedings. 1994 Canadian Conference on

Date of Conference:

25-28 Sep 1994