Publication
Title
Spatial-mode selection based on channel mean feedback for a robust joint linear precoder and decoder-MMSE design
Author
Abstract
The joint linear precoder and decoder Minimum Mean Squared Error (MMSE) design represents a low complexity yet powerful solution for spatial multiplexing MIMO systems. Its performance can be further boosted through optimally selecting the number of spatial streams to be used according to the available Channel State Information (CSI), so-called spatial-mode selection. The performance of both the latter MMSE design and the related spatial-mode selection criteria, however, critically depends on the availability of timely CSI at both transmitter and receiver. In practice, the latter assumption can be severely challenged, due to channel time variations that lead to imperfect CSI at the transmitter. State-of-the-art designs mistakenly use this imperfect CSI to design the linear precoder and rely on the receiver to reduce the induced degradation. We have alternatively proposed a robust Bayesian joint linear precoder and decoder solution that takes into account the uncertainty on the true channel, given the channel mean feedback at the transmitter. In this paper, we further improve the performance of our aforementioned robust design using a new spatial-mode selection criterion based on channel mean feedback. We also illustrate, via Monte-Carlo analysis, the robustness of the resulting improved design to channel time variations, which outperforms the state-of-the-art approach.
Language
English
Source (journal)
2004 IEEE 5TH WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS
COMMUNICATIONS
Source (book)
5th IEEE Workshop on Signal Processing Advances in Wireless, Communications, JUL 11-14, 2004, Lisbon, PORTUGAL
Publication
New york : Ieee , 2004
ISBN
0-7803-8337-0
Volume/pages
(2004) , p. 233-237
ISI
000226768600049
UAntwerpen
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 03.01.2013
Last edited 23.08.2022
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