Title
Energy Efficiency Optimization Based on eICIC for Wireless Heterogeneous Networks
Abstract
To solve the problem of load imbalance and system interference in heterogeneous networks (HetNets), an energy efficiency (EE) optimized strategy based on enhanced intercell interference coordination (eICIC) technology is proposed. The optimization of the EE of the system is established by taking into account four components which are the connection between the users and base stations (BSs), almost blank subframe (ABS) ratio, resource allocation in the frequency domain, and the power transmission of the macro BSs (MBSs). In our optimized strategy, the user’s optimal BS connection status are determined according to the overall EE change of the system, and the allocation of subframes and resource blocks of the MBSs both in the time domain and frequency domain are optimized, respectively. We use the Gauss–Seidel method to iteratively solve the optimization problem. Simulation results show that the optimized strategy outperforms other solutions in terms of EE and user fairness in average. The proposed optimization strategy increases the system EE by 24.2% and 19.1%, respectively, when compared with the maximal reference signal received power (MAX-RSRP) and the low power-ABS (LP-ABS) strategies. The Jain fairness index of our proposed optimization strategy is averagely increased by 33.8% and 23.4%, respectively. In addition, the proposed strategy can further improve the user satisfaction and the performance in the system.
Year
DOI
Venue
2019
10.1109/JIOT.2019.2936499
IEEE Internet of Things Journal
Keywords
Field
DocType
Optimization,Resource management,Base stations,Interference,Frequency-domain analysis,Internet of Things,Heterogeneous networks
Frequency domain,Time domain,Base station,Wireless,Efficient energy use,Computer science,Resource allocation,Heterogeneous network,Optimization problem,Distributed computing
Journal
Volume
Issue
ISSN
6
6
2327-4662
Citations 
PageRank 
References 
1
0.35
0
Authors
5
Name
Order
Citations
PageRank
Jun Li11138.46
Xiumin Wang2816.61
Zhengquan Li380.76
Hao Wang4440127.79
Lei Li510.35