Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/12536
Title: Low-bit rate feedback strategies for iterative IA-precoded MIMO-OFDM-based systems
Author: Teodoro, Sara
Silva, Adão
Dinis, Rui
Gameiro, Atílio
Issue Date: 1-Feb-2014
Publisher: Hindawi
Abstract: Interference alignment (IA) is a promising technique that allows high-capacity gains in interference channels, but which requires the knowledge of the channel state information (CSI) for all the system links. We design low-complexity and low-bit rate feedback strategies where a quantized version of some CSI parameters is fed back from the user terminal (UT) to the base station (BS), which shares it with the other BSs through a limited-capacity backhaul network. This information is then used by BSs to perform the overall IA design. With the proposed strategies, we only need to send part of the CSI information, and this can even be sent only once for a set of data blocks transmitted over time-varying channels. These strategies are applied to iterative MMSE-based IA techniques for the downlink of broadband wireless OFDM systems with limited feedback. A new robust iterative IA technique, where channel quantization errors are taken into account in IA design, is also proposed and evaluated. With our proposed strategies, we need a small number of quantization bits to transmit and share the CSI, when comparing with the techniques used in previous works, while allowing performance close to the one obtained with perfect channel knowledge.
Peer review: yes
URI: http://hdl.handle.net/10773/12536
DOI: 10.1155/2014/619454
ISSN: 1537-744X
Appears in Collections:DETI - Artigos

Files in This Item:
File Description SizeFormat 
619454.pdf1.72 MBAdobe PDFView/Open


FacebookTwitterLinkedIn
Formato BibTex MendeleyEndnote Degois 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.