
FOLLOWUS
MOE Key Laboratory of Universal Wireless Communications, Beijing University of Posts and Telecommunications, Beijing 100876, China
[ "Ming-wei TANG, E-mail: tangmingwei.bupt@gmail.com" ]
收稿:2011-04-27,
修回:2011-12-29,
纸质出版:2012-02
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Resource allocation algorithm with limited feedback for multicast single frequency networks[J]. 信息与电子工程前沿(英文), 2012,13(2):146-154.
Ming-wei TANG, Xiao-xiang WANG. Resource allocation algorithm with limited feedback for multicast single frequency networks[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(2): 146-154.
Resource allocation algorithm with limited feedback for multicast single frequency networks[J]. 信息与电子工程前沿(英文), 2012,13(2):146-154. DOI: 10.1631/jzus.C1100108.
Ming-wei TANG, Xiao-xiang WANG. Resource allocation algorithm with limited feedback for multicast single frequency networks[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(2): 146-154. DOI: 10.1631/jzus.C1100108.
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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