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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

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Journal of Zhejiang University SCIENCE C 2012 Vol.13 No.2 P.146-154

http://doi.org/10.1631/jzus.C1100108


Resource allocation algorithm with limited feedback for multicast single frequency networks


Author(s):  Ming-wei Tang, Xiao-xiang Wang

Affiliation(s):  MOE Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China

Corresponding email(s):   tangmingwei.bupt@gmail.com

Key Words:  Multicast, Single frequency networks (SFN), Orthogonal frequency division multiplexing access (OFDMA), Resource allocation


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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.

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%DOI 10.1631/jzus.C1100108

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T1 - Resource allocation algorithm with limited feedback for multicast single frequency networks
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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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Reference

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