Cooperative Small Cell HetNets With Dynamic Sleeping and Energy Harvesting

被引:30
作者
Alqasir, Abdullah M. [1 ]
Kamal, Ahmed E. [2 ]
机构
[1] Qassim Univ, Coll Engn, Dept Elect Engn, Buraydah 52571, Saudi Arabia
[2] Iowa State Univ, Dept Elect & Comp Engn, Ames, IA 50011 USA
来源
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING | 2020年 / 4卷 / 03期
基金
美国国家科学基金会;
关键词
Energy efficiency; 5G; energy harvesting; smart grid; dynamic sleeping; generalized benders decomposition; network centrality;
D O I
10.1109/TGCN.2020.2985496
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
This paper considers a heterogenous wireless cellular network (HetNet) where many small base stations (SBS) coexist. SBSs can be deactivated and put to sleep to save energy and are equipped with two power sources, harvested energy (HE) and a grid power source, where an SBS will use its available HE to serve the associated users first. Then, the SBS will request any shortage of its energy from other active or deactivated SBSs that have a surplus of HE. Finally, if there is still an energy shortage, the SBS will use power drawn from the grid. This transfer of energy is facilitated through the use of the promising smart grid (SG)technology. We investigate the grid energy minimization problem by optimizing both the transmission power and activation/deactivation (dynamic sleeping) of the SBSs. However, since the formulated problem is a mixed integer nonLinear problem (MINLP), generalized Benders decomposition (GBD) is used to decompose the problem into two subproblems: user association and energy harvesting which are solved iteratively. Further, a new heuristic approach is proposed that provides a computationally efficient algorithm to solve and optimize the user association and energy harvesting problems of the system model. This approach uses network centrality to develop a measuring parameter, base station centrality (BSC), of SBS centrality in the network. BSC is presented to mark the SBSs that have the most potential to be deactivated without affecting the quality of service (QoS) of users. Finally, extensive simulations are performed to verify the superiority of the proposed BSC-based strategy over GBD in terms of operational cost.
引用
收藏
页码:774 / 782
页数:9
相关论文
共 21 条
[1]  
Alqasir A, 2018, IEEE ICC
[2]   Optimization of a Power Splitting Protocol for Two-Way Multiple Energy Harvesting Relay System [J].
Alsharoa, Ahmad ;
Ghazzai, Hakim ;
Kamal, Ahmed E. ;
Kadri, Abdullah .
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2017, 1 (04) :444-457
[3]  
[Anonymous], 2014, Convex Optimiza- tion
[4]   Branching and bounds tightening techniques for non-convex MINLP [J].
Belotti, Pietro ;
Lee, Jon ;
Liberti, Leo ;
Margot, Francois ;
Waechter, Andreas .
OPTIMIZATION METHODS & SOFTWARE, 2009, 24 (4-5) :597-634
[5]   Partitioning procedures for solving mixed-variables programming problems [J].
Benders, J. F. .
COMPUTATIONAL MANAGEMENT SCIENCE, 2005, 2 (01) :3-19
[6]   Centrality and network flow [J].
Borgatti, SP .
SOCIAL NETWORKS, 2005, 27 (01) :55-71
[7]  
Chang CY, 2014, IEEE ICC, P2690, DOI 10.1109/ICC.2014.6883730
[8]   Green Multicell Cooperation in Heterogeneous Networks With Hybrid Energy Sources [J].
Chiang, Yi-Han ;
Liao, Wanjiun .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2016, 15 (12) :7911-7925
[9]   Smart Grid - The New and Improved Power Grid: A Survey [J].
Fang, Xi ;
Misra, Satyajayant ;
Xue, Guoliang ;
Yang, Dejun .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2012, 14 (04) :944-980
[10]  
Geoffrion A. M., 1972, Journal of Optimization Theory and Applications, V10, P237, DOI 10.1007/BF00934810