Load-Aware Energy Efficiency Optimization in Dense Small Cell Networks

2017 ◽  
Vol 21 (2) ◽  
pp. 366-369 ◽  
Author(s):  
Shie Wu ◽  
Zhimin Zeng ◽  
Hailun Xia
Keyword(s):  
Energy Efficiency ◽  
Small Cell ◽  
Small Cell Networks ◽  
Efficiency Optimization ◽  
Cell Networks

Energy Efficiency Optimization in LTE-U Based Small Cell Networks

2019 ◽  
Vol 68 (2) ◽  
pp. 1963-1967 ◽  
Author(s):  
Rui Yin ◽  
Yunfeng Zhang ◽  
Fang Dong ◽  
Anding Wang ◽  
Chau Yuen
Keyword(s):  
Energy Efficiency ◽  
Small Cell ◽  
Small Cell Networks ◽  
Efficiency Optimization ◽  
Cell Networks

scholarly journals IMPSO and Linear Programming-Based Energy-Efficient Cell Association Algorithm for Backhaul-Constrained Ultra-Dense Small-Cell Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Huilin Jiang ◽  
Wenxiang Zhu ◽  
Xiang Song ◽  
Guilu Wu
Keyword(s):  
Energy Efficiency ◽  
Linear Programming ◽  
Optimization Problem ◽  
Small Cell ◽  
Small Cells ◽  
Small Cell Networks ◽  
Efficiency Optimization ◽  
Cell Association ◽  
Backhaul Link ◽  
Cell Networks

This paper studies the energy efficiency optimization problem for coordinated multipoint (CoMP)-enabled and backhaul-constrained ultra-dense small-cell networks (UDNs). Energy efficiency is an eternal topic for future wireless communication networks; however, taking actual bottleneck of the backhaul link and the coordinated network architecture into consideration, it is difficult to find an effective way to improve the energy efficiency of the network. Aiming at this problem, we propose to combine cell association, subchannel allocation, backhaul resource allocation, and sleep/on of the cells together to develop an optimization algorithm for energy efficiency in UDN and then solve the formulated energy efficiency optimization problem by means of improved modified particle swarm optimization (IMPSO) and linear programming in mathematics. Simulation results indicate that nearly 13 % energy cost saving and 21 % energy efficiency improvement can be obtained by combining IMPSO with linear programming, and the backhaul link data rate can be improved by 30 % as the number of small cells increases. From the results, it can be found that by combining IMPSO with linear programming, the proposed algorithm can improve the network energy efficiency effectively at the expense of limited complexity.

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