By Topic

Performance improvement via AR modeling based linear prediction for time division duplex (TDD) smart antenna 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 $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)
Yigit, H. ; Kocaeli Universitesi, Izmit, Turkey ; Kavak, A.

In time-division-duplex (TDD) mode wireless communication, downlink performance of a smart antenna system (SAS) can be degraded due to variation of spatial signatures especially in vehicular scenarios. To mitigate this, prediction based downlink beamforming can be applied, which relies on using updated weight vectors via linear prediction of spatial signatures in the downlink interval based on their autoregressive modeling in the uplink interval. Here, we demonstrate the effectiveness of employing predicted spatial signatures as downlink weight vectors under varying mobile speed (V), multipath angle spread (Δθ), prediction filter order (P) and multipath number (L). We observe that in fixed Doppler shift conditions, i.e., Doppler shifts in the multipaths are integer multiple of Doppler shift in the dominant path, prediction based beamforming achieves better SNR improvements in the received signal at the mobile terminal with increasing V, P, and L. However its performance is not significantly affected by the variation in Δθ.

Published in:

Signal Processing and Communications Applications Conference, 2004. Proceedings of the IEEE 12th

Date of Conference:

28-30 April 2004