DocumentCode :
1378707
Title :
Delay-optimal power and subcarrier allocation for OFDMA systems via stochastic approximation
Author :
Lau, Vincent K N ; Cui, Ying
Author_Institution :
Dept. of ECE, Hong Kong Univ. of Sci. & Technol., Kowloon, China
Volume :
9
Issue :
1
fYear :
2010
fDate :
1/1/2010 12:00:00 AM
Firstpage :
227
Lastpage :
233
Abstract :
In this paper, we consider delay-optimal power and subcarrier allocation design for OFDMA systems with NF subcarriers, K mobiles and one base station. There are K queues at the base station for the downlink traffic to the K mobiles with heterogeneous packet arrivals and delay requirements. We shall model the problem as a K-dimensional infinite horizon average reward Markov Decision Problem (MDP) where the control actions are assumed to be a function of the instantaneous Channel State Information (CSI) as well as the joint Queue State Information (QSI). We propose an online stochastic value iteration solution using stochastic approximation. The proposed power control algorithm, which is a function of both the CSI and the QSI, takes the form of multi-level water-filling. We prove that under two mild conditions in Theorem 1, the proposed solution converges to the optimal solution almost surely (with probability 1) and the proposed framework offers a possible solution to the general stochastic NUM problem. By exploiting the birth-death structure of the queue dynamics, we obtain a reduced complexity decomposed solution with linear O(KNF) complexity and O(K) memory requirement.
Keywords :
frequency division multiple access; stochastic processes; telecommunication traffic; Markov decision problem; OFDMA systems; base station; channel state information; downlink traffic; multi-level water-filling; online stochastic value iteration solution; power allocation; power control algorithm; queue state information; stochastic approximation; subcarrier allocation; Base stations; Channel state information; Delay; Downlink; Infinite horizon; Power control; Power system modeling; Stochastic processes; Stochastic systems; Traffic control; Delay-optimal, resource allocation; Markov Decision Problem; stochastic learning, reduced complexity solution;
fLanguage :
English
Journal_Title :
Wireless Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1276
Type :
jour
DOI :
10.1109/TWC.2010.01.090031
Filename :
5374066
Link To Document :
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