Resource allocation algorithm with limited feedback for multicast single frequency networks

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 th...

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Bibliographic Details
Published in:Frontiers of information technology & electronic engineering 2012-02, Vol.13 (2), p.146-154
Main Authors: Tang, Ming-wei, Wang, Xiao-xiang
Format: Article
Language:English
Subjects:
Algorithms
Allocations
Communications Engineering
Complexity
Computer Hardware
Computer Science
Computer Systems Organization and Communication Networks
Control algorithms
Control systems
Control theory
Electrical Engineering
Electronics and Microelectronics
Feedback
Feedback control
Instrumentation
Multicast
Multicasting
Multimedia
Networks
Resource allocation
Subcarriers
信道状态信息
功率分配
单频网络
反馈控制算法
多播服务
组播
资源分配算法
迭代策略
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Summary: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） require- ment 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.
ISSN:1869-1951
2095-9184
1869-196X
2095-9230
DOI:10.1631/jzus.C1100108