CDIT-Based Constrained Resource Allocation for Mobile WiMAX Systems

<p/> <p>Adaptive resource allocation has been shown to provide substantial performance gain in OFDMA-based wireless systems, such as WiMAX, when full channel state information (CSI) is available at the transmitter. However, in some fading environments (e.g., fast fading), there may not b...

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Main Authors: Brah Felix, Louveaux Jerome, Vandendorpe Luc
Format: Article
Language:English
Published: SpringerOpen 2009-01-01
Series:EURASIP Journal on Wireless Communications and Networking
Online Access:http://jwcn.eurasipjournals.com/content/2009/425367
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spelling doaj-d39ff1899707460ea408e3f86796a0042020-11-25T00:30:19ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992009-01-0120091425367CDIT-Based Constrained Resource Allocation for Mobile WiMAX SystemsBrah FelixLouveaux JeromeVandendorpe Luc<p/> <p>Adaptive resource allocation has been shown to provide substantial performance gain in OFDMA-based wireless systems, such as WiMAX, when full channel state information (CSI) is available at the transmitter. However, in some fading environments (e.g., fast fading), there may not be a feedback link sufficiently fast to convey the CSI to the transmitter. In this paper, we consider resource allocation strategies for downlink multiuser mobile WiMAX systems, where the transmitter has only the channel distribution information (CDI), but no knowledge of the instantaneous channel realization. We address the problem of subchannel assignment and power allocation, to maximize the ergodic weighted-sum rate under long-term fairness, minimum data rate requirement and power budget constraints. This problem is formulated as a nonlinear stochastic constrained optimization problem. We provide an analytical solution based on the Lagrange dual decomposition framework. The proposed method has a complexity of <inline-formula> <graphic file="1687-1499-2009-425367-i1.gif"/></inline-formula>(<it>KM</it>) for <it>K</it> users and <it>M</it> subchannels. Simulation results are provided to compare the performance of this method with other allocation schemes and to illustrate the tradeoff between maximized weighted-sum rate and the constraints.</p>http://jwcn.eurasipjournals.com/content/2009/425367
collection DOAJ
language English
format Article
sources DOAJ
author Brah Felix
Louveaux Jerome
Vandendorpe Luc
spellingShingle Brah Felix
Louveaux Jerome
Vandendorpe Luc
CDIT-Based Constrained Resource Allocation for Mobile WiMAX Systems
EURASIP Journal on Wireless Communications and Networking
author_facet Brah Felix
Louveaux Jerome
Vandendorpe Luc
author_sort Brah Felix
title CDIT-Based Constrained Resource Allocation for Mobile WiMAX Systems
title_short CDIT-Based Constrained Resource Allocation for Mobile WiMAX Systems
title_full CDIT-Based Constrained Resource Allocation for Mobile WiMAX Systems
title_fullStr CDIT-Based Constrained Resource Allocation for Mobile WiMAX Systems
title_full_unstemmed CDIT-Based Constrained Resource Allocation for Mobile WiMAX Systems
title_sort cdit-based constrained resource allocation for mobile wimax systems
publisher SpringerOpen
series EURASIP Journal on Wireless Communications and Networking
issn 1687-1472
1687-1499
publishDate 2009-01-01
description <p/> <p>Adaptive resource allocation has been shown to provide substantial performance gain in OFDMA-based wireless systems, such as WiMAX, when full channel state information (CSI) is available at the transmitter. However, in some fading environments (e.g., fast fading), there may not be a feedback link sufficiently fast to convey the CSI to the transmitter. In this paper, we consider resource allocation strategies for downlink multiuser mobile WiMAX systems, where the transmitter has only the channel distribution information (CDI), but no knowledge of the instantaneous channel realization. We address the problem of subchannel assignment and power allocation, to maximize the ergodic weighted-sum rate under long-term fairness, minimum data rate requirement and power budget constraints. This problem is formulated as a nonlinear stochastic constrained optimization problem. We provide an analytical solution based on the Lagrange dual decomposition framework. The proposed method has a complexity of <inline-formula> <graphic file="1687-1499-2009-425367-i1.gif"/></inline-formula>(<it>KM</it>) for <it>K</it> users and <it>M</it> subchannels. Simulation results are provided to compare the performance of this method with other allocation schemes and to illustrate the tradeoff between maximized weighted-sum rate and the constraints.</p>
url http://jwcn.eurasipjournals.com/content/2009/425367
work_keys_str_mv AT brahfelix cditbasedconstrainedresourceallocationformobilewimaxsystems
AT louveauxjerome cditbasedconstrainedresourceallocationformobilewimaxsystems
AT vandendorpeluc cditbasedconstrainedresourceallocationformobilewimaxsystems
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