Research Article
Energy-Efficient Femtocells Active/Idle Control and Load Balancing in Heterogeneous Networks
@INPROCEEDINGS{10.1007/978-3-319-66628-0_23, author={Xiaoge Huang and Zhifang Zhang and Weipeng Dai and Qiong Huang and Qianbin Chen}, title={Energy-Efficient Femtocells Active/Idle Control and Load Balancing in Heterogeneous Networks}, proceedings={Communications and Networking. 11th EAI international Conference, ChinaCom 2016 Chongqing, China, September 24-26, 2016, Proceedings, Part II}, proceedings_a={CHINACOM}, year={2017}, month={10}, keywords={Energy efficient Femtocell Load balancing Stations active/idle switch}, doi={10.1007/978-3-319-66628-0_23} }
- Xiaoge Huang
Zhifang Zhang
Weipeng Dai
Qiong Huang
Qianbin Chen
Year: 2017
Energy-Efficient Femtocells Active/Idle Control and Load Balancing in Heterogeneous Networks
CHINACOM
Springer
DOI: 10.1007/978-3-319-66628-0_23
Abstract
In this paper, we present a network energy-efficient resource-allocation scheme for dense small cell heterogeneous networks by jointly controlling femtocell base stations active/idle strategies and load balancing with SINR constraints among users. The optimization problem is NP-hard, thus obtaining the optimal solution is extremely computationally complex. Therefore, we formulate the optimization problem to two sub-optimization problems: the load balancing design and the femtocell base stations active/idle switch strategies control. In load balancing design scheme, we optimize the load balancing of the small cell heterogeneous networks under the fixed femtocell base stations active/idle strategies. In femtocell base stations active/idle switch strategies scheme, we optimize the network energy efficiency while achieving the minimum service requirement among users. Combined with the optimal load balancing design, we solve the femtocell base stations active/idle switch strategies scheme by observation that the network energy efficiency is an increasing function of both user number and femtocell number. Simulation results show that the proposed algorithm could achieve a considerable performance improvement in terms of network energy efficiency compared with the traditional algorithms.