王洪玉

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:天津大学

学位:博士

所在单位:信息与通信工程学院

学科:通信与信息系统. 信号与信息处理

办公地点:大连理工大学创新园大厦B510

联系方式:电子邮箱:whyu@dlut.edu.cn 办公电话:0411-84707675 移动电话:13842827170

电子邮箱:whyu@dlut.edu.cn

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A refunding strategy: opportunistic user association with congestion-based pricing in macro-femto hybrid network

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论文类型:期刊论文

发表时间:2017-01-03

发表刊物:EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING

收录刊物:SCIE、EI、Scopus

卷号:2017

期号:1

ISSN号:1687-1499

关键字:Heterogeneous network; Backhaul; User association; Congestion pricing; Utility maximization

摘要:Femtocell technology addresses the severe problems of poor network capacity and indoor coverage. Meanwhile, the emergence of high-capacity air interfaces and dense deployment of small cells result in increasingly high backhaul cost in cellular wireless networks. Purchasing on leased lines can guarantee the service provision during busy hours, however, purchased capacity goes to waste in off-peak time. Hybrid mode is the most promising one among all femtocell access modes which allows macro users to associate with adjacent femtocells with idle bandwidth resources. Femto holder (FH) is egoistic and unwilling to share bandwidth with transferred users from macrocells without any compensation, thus the successful implementation of hybrid access becomes a challenging problem. In this paper, we present an economic refunding framework to motivate hybrid access in femtocells. Macro users can opportunistically associate with adjacent femtocells with excess backhaul capacity. FH can receive certain refunding from wireless service provider (WSP) in exchange for traffic offloading. FH employs congestion pricing policy so as to control the cell load in the femtocell. Within this framework, we design a general utility maximization problem for user association that enables macro users to associate with femtocells based on traffic status, cell load, and access price. Dual decomposition is used to obtain an approximate solution. The impact of congestion pricing on the aggregate throughput and load balancing is also analyzed. Extensive simulations show the proposed scheme achieves a remarkable throughput gain compared with that with no compensation and compensation with usage-based pricing policy. Load balancing is substantially improved as well.