By Topic

Graph-Based Iterative Gaussian Detection with Soft Channel Estimation for 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
$31 $31
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)
Wo, Tianbin ; Information and Coding Theory Lab, Faculty of Engineering, University of Kiel, Germany ; Liu, Chunhui ; Hoeher, Peter Adam

Conventionally, the uncertainties of channel coefficients are neglected, that is the estimated values of channel coefficients are taken as the true values in the stage of data detection. In the communications community, it is still an open question how to take into account the channel uncertainty for data detection/decoding, especially in a low-complexity manner. In this paper, we propose a low-complexity receiver algorithm which utilizes soft channel information. Channel coefficients are treated as variables and estimated in an element-wise manner. Their uncertainties are represented by the variances. Instead of performing channel estimation and data detection in a separate manner, this algorithm does everything in one stage, i.e., channel estimation and data detection/decoding are carried out simultaneously over a general factor graph. The feasibility of this algorithm is verified by means of Monte-Carlo simulations both in bit error ratio (BER) and channel estimation mean squared error (MSE).

Published in:

Source and Channel Coding (SCC), 2008 7th International ITG Conference on

Date of Conference:

14-16 Jan. 2008