Joint optimization of power consumption and load balancing in wireless dynamic network architecture. Sugathapala, I., Glisic, S., Juntti, M., & Tran, L., N. In 2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017, pages 121-125, 2017.
abstract   bibtex   
© 2017 IEEE. The concept of the wireless dynamic network architecture (DNA) stands for a system design, which allows terminals to convert into temporary access points (APs) when necessary. In this paper, we propose a framework to solve the problem of load balancing in DNA. Particularly, the user association in DNAs is optimized to minimize the number of active APs and the network cost in terms of tradeoff between power and load, while ensuring users' quality of service (QoS). In general, such a problem is a non-convex mixed integer nonlinear program in the sense that its continuous relaxation is a non-convex problem. To solve this optimization, we use the standard continuous relaxation method and approximate the relaxed problem by a series of second order cone programs with the aid of successive convex approximation (SCA) framework. Numerical results show that the proposed algorithm converges within a few iterations and jointly minimizes the network cost and the number of APs in the network.
@inProceedings{
 title = {Joint optimization of power consumption and load balancing in wireless dynamic network architecture},
 type = {inProceedings},
 year = {2017},
 identifiers = {[object Object]},
 keywords = {AP and power consumption minimization,Convex optimization,Downlink beamforming,Load balancing,SOCP,User association},
 pages = {121-125},
 id = {0437c144-2c8a-3e3d-aa21-b81cdc165a8a},
 created = {2017-08-10T13:58:20.843Z},
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 abstract = {© 2017 IEEE. The concept of the wireless dynamic network architecture (DNA) stands for a system design, which allows terminals to convert into temporary access points (APs) when necessary. In this paper, we propose a framework to solve the problem of load balancing in DNA. Particularly, the user association in DNAs is optimized to minimize the number of active APs and the network cost in terms of tradeoff between power and load, while ensuring users' quality of service (QoS). In general, such a problem is a non-convex mixed integer nonlinear program in the sense that its continuous relaxation is a non-convex problem. To solve this optimization, we use the standard continuous relaxation method and approximate the relaxed problem by a series of second order cone programs with the aid of successive convex approximation (SCA) framework. Numerical results show that the proposed algorithm converges within a few iterations and jointly minimizes the network cost and the number of APs in the network.},
 bibtype = {inProceedings},
 author = {Sugathapala, Inosha and Glisic, Savo and Juntti, Markku and Tran, Le Nam},
 booktitle = {2017 IEEE International Conference on Communications Workshops, ICC Workshops 2017}
}

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