Robust Power Allocation Algorithms for Wireless Relay Networks
Name
Quek-2010-Robust Power Allocat.pdf
Size
279.55 KB
Format
Adobe PDF
Checksum (MD5)
adf3b4e6c0a23e32a569c35c06cd2fb0
Author(s) • •
Quek, Tony Q. S.
Win, Moe Z.
Chiani, Marco
Date Issued
July 2010
Journal
IEEE transaction on communications
Publisher
Institute of Electrical and Electronics Engineers / IEEE Communications Society
Citation
Quek, Tony Q.S., Moe Z. Win, and Marco Chiani. “Robust Power Allocation Algorithms for Wireless Relay Networks.” Communications, IEEE Transactions on 58.7 (2010): 1931-1938. Copyright © 2010, IEEE
Version
Final published version
Abstract
Resource allocation promises significant benefits in
wireless networks. In order to fully reap these benefits, it is
important to design efficient resource allocation algorithms. Here,
we develop relay power allocation (RPA) algorithms for coherent
and noncoherent amplify-and-forward (AF) relay networks. The
goal is to maximize the output signal-to-noise ratio under
individual as well as aggregate relay power constraints. We show
that these RPA problems, in the presence of perfect global channel
state information (CSI), can be formulated as quasiconvex
optimization problems. In such settings, the optimal solutions
can be efficiently obtained via a sequence of convex feasibility
problems, in the form of second-order cone programs. The
benefits of our RPA algorithms, however, depend on the quality
of the global CSI, which is rarely perfect in practice. To address
this issue, we introduce the robust optimization methodology
that accounts for uncertainties in the global CSI. We show
that the robust counterparts of our convex feasibility problems
with ellipsoidal uncertainty sets are semi-definite programs. Our
results reveal that ignoring uncertainties associated with global
CSI often leads to poor performance, highlighting the importance
of robust algorithm designs in practical wireless networks.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/tcomm.2010.07.080277