By Topic

Implementation of a Markov Chain Monte Carlo Based Multiuser/MIMO Detector

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)
Stephen Andrew Laraway ; L-3 Commun., Salt Lake City, UT ; Behrouz Farhang-Boroujeny

Multiuser/multiple-input-multiple-output detectors that use Markov chain Monte Carlo (MCMC) simulation techniques to obtain likelihood of information bits have been developed recently. In this paper, we explore the implementation details of one such detector and present an efficient hardware architecture of it. The first step in development of this architecture is to derive a log-domain version of the Gibbs sampler, an efficient method of obtaining samples of MCMC simulator. This formulation is numerically stable and can operate with low precision. The log- domain formulation also lends itself to a hardware architecture that involves only addition, subtraction, and compare operations. Moreover, pipelining is introduced in the proposed architecture straightforwardly. We also explore the word-length requirement of the developed architecture through computer simulations.

Published in:

IEEE Transactions on Circuits and Systems I: Regular Papers  (Volume:56 ,  Issue: 1 )