CLC number: TN929.5
On-line Access: 2012-01-19
Received: 2011-04-27
Revision Accepted: 2011-11-16
Crosschecked: 2011-12-29
Cited: 1
Clicked: 8268
Ming-wei Tang, Xiao-xiang Wang. Resource allocation algorithm with limited feedback for multicast single frequency networks[J]. Journal of Zhejiang University Science C, 2012, 13(2): 146-154.
@article{title="Resource allocation algorithm with limited feedback for multicast single frequency networks",
author="Ming-wei Tang, Xiao-xiang Wang",
journal="Journal of Zhejiang University Science C",
volume="13",
number="2",
pages="146-154",
year="2012",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1100108"
}
%0 Journal Article
%T Resource allocation algorithm with limited feedback for multicast single frequency networks
%A Ming-wei Tang
%A Xiao-xiang Wang
%J Journal of Zhejiang University SCIENCE C
%V 13
%N 2
%P 146-154
%@ 1869-1951
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1100108
TY - JOUR
T1 - Resource allocation algorithm with limited feedback for multicast single frequency networks
A1 - Ming-wei Tang
A1 - Xiao-xiang Wang
J0 - Journal of Zhejiang University Science C
VL - 13
IS - 2
SP - 146
EP - 154
%@ 1869-1951
Y1 - 2012
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1100108
Abstract: The single frequency network (SFN) can provide a multimedia broadcast multicast service over a large coverage area. However, the application of SFN is still restricted by a large amount of feedback. Therefore, we propose a multicast resource allocation scheme based on limited feedback to maximize the total rate while guaranteeing the quality of service (QoS) requirement of real-time services. In this scheme, we design a user feedback control algorithm to effectively reduce feedback load. The algorithm determines to which base stations the users should report channel state information. We then formulate a joint subcarrier and power allocation issue and find that it has high complexity. Hence, we first distribute subcarriers under the assumption of equal power and develop a proportional allocation strategy to achieve a tradeoff between fairness and QoS. Next, an iterative water-filling power allocation is proposed to fully utilize the limited power. To further decrease complexity, a power iterative scheme is introduced. Simulation results show that the proposed scheme significantly improves system performance while reducing 68% of the feedback overhead. In addition, the power iterative strategy is suitable in practice due to low complexity.
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