Heterogeneous network (HetNet) is now considered to be a promising technique for enhancing the coverage and reducing the transmit power consumption of the next 5G system. Deploying small cells such as femtocells in the current macrocell networks achieves great spatial reuse at the cost of severe cross-tier interference from concurrent transmission. In this situation, two novel energy efficient power control and resource allocation schemes in terms of energy efficiency (EE)-fairness and EE-maximum, respectively, are investigated in this paper. In the EE-fairness scheme, we aim to maximize the minimum EE of the femtocell base stations (FBSs). Generalized Dinkelbach's algorithm (GDA) is utilized to tackle this optimization problem and a distributed algorithm is proposed to solve the subproblem in GDA with limited intercell coordination, in which only a few scalars are shared among FBSs. In the EE-maximum scheme, we aim to maximize the global EE of all femtocells which is defined as the aggregate capacity over the aggregate power consumption in the femtocell networks. Leveraged by means of the lower-bound of logarithmic function, a centralized algorithm with limited computational complexity is proposed to solve the global EE maximization problem. Simulation results show that the proposed algorithms outperform previous schemes in terms of the minimum EE, fairness and global EE.
Guodong ZHANG
Southeast University
Wei HENG
Southeast University
Jinming HU
Southeast University
Tian LIANG
Southeast University
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Guodong ZHANG, Wei HENG, Jinming HU, Tian LIANG, "Energy Efficient Power Control and Resource Allocation in Downlink OFDMA HetNets with Cross-Tier Interference Constraint" in IEICE TRANSACTIONS on Communications,
vol. E99-B, no. 7, pp. 1599-1608, July 2016, doi: 10.1587/transcom.2015EBP3436.
Abstract: Heterogeneous network (HetNet) is now considered to be a promising technique for enhancing the coverage and reducing the transmit power consumption of the next 5G system. Deploying small cells such as femtocells in the current macrocell networks achieves great spatial reuse at the cost of severe cross-tier interference from concurrent transmission. In this situation, two novel energy efficient power control and resource allocation schemes in terms of energy efficiency (EE)-fairness and EE-maximum, respectively, are investigated in this paper. In the EE-fairness scheme, we aim to maximize the minimum EE of the femtocell base stations (FBSs). Generalized Dinkelbach's algorithm (GDA) is utilized to tackle this optimization problem and a distributed algorithm is proposed to solve the subproblem in GDA with limited intercell coordination, in which only a few scalars are shared among FBSs. In the EE-maximum scheme, we aim to maximize the global EE of all femtocells which is defined as the aggregate capacity over the aggregate power consumption in the femtocell networks. Leveraged by means of the lower-bound of logarithmic function, a centralized algorithm with limited computational complexity is proposed to solve the global EE maximization problem. Simulation results show that the proposed algorithms outperform previous schemes in terms of the minimum EE, fairness and global EE.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.2015EBP3436/_p
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@ARTICLE{e99-b_7_1599,
author={Guodong ZHANG, Wei HENG, Jinming HU, Tian LIANG, },
journal={IEICE TRANSACTIONS on Communications},
title={Energy Efficient Power Control and Resource Allocation in Downlink OFDMA HetNets with Cross-Tier Interference Constraint},
year={2016},
volume={E99-B},
number={7},
pages={1599-1608},
abstract={Heterogeneous network (HetNet) is now considered to be a promising technique for enhancing the coverage and reducing the transmit power consumption of the next 5G system. Deploying small cells such as femtocells in the current macrocell networks achieves great spatial reuse at the cost of severe cross-tier interference from concurrent transmission. In this situation, two novel energy efficient power control and resource allocation schemes in terms of energy efficiency (EE)-fairness and EE-maximum, respectively, are investigated in this paper. In the EE-fairness scheme, we aim to maximize the minimum EE of the femtocell base stations (FBSs). Generalized Dinkelbach's algorithm (GDA) is utilized to tackle this optimization problem and a distributed algorithm is proposed to solve the subproblem in GDA with limited intercell coordination, in which only a few scalars are shared among FBSs. In the EE-maximum scheme, we aim to maximize the global EE of all femtocells which is defined as the aggregate capacity over the aggregate power consumption in the femtocell networks. Leveraged by means of the lower-bound of logarithmic function, a centralized algorithm with limited computational complexity is proposed to solve the global EE maximization problem. Simulation results show that the proposed algorithms outperform previous schemes in terms of the minimum EE, fairness and global EE.},
keywords={},
doi={10.1587/transcom.2015EBP3436},
ISSN={1745-1345},
month={July},}
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TY - JOUR
TI - Energy Efficient Power Control and Resource Allocation in Downlink OFDMA HetNets with Cross-Tier Interference Constraint
T2 - IEICE TRANSACTIONS on Communications
SP - 1599
EP - 1608
AU - Guodong ZHANG
AU - Wei HENG
AU - Jinming HU
AU - Tian LIANG
PY - 2016
DO - 10.1587/transcom.2015EBP3436
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2016
AB - Heterogeneous network (HetNet) is now considered to be a promising technique for enhancing the coverage and reducing the transmit power consumption of the next 5G system. Deploying small cells such as femtocells in the current macrocell networks achieves great spatial reuse at the cost of severe cross-tier interference from concurrent transmission. In this situation, two novel energy efficient power control and resource allocation schemes in terms of energy efficiency (EE)-fairness and EE-maximum, respectively, are investigated in this paper. In the EE-fairness scheme, we aim to maximize the minimum EE of the femtocell base stations (FBSs). Generalized Dinkelbach's algorithm (GDA) is utilized to tackle this optimization problem and a distributed algorithm is proposed to solve the subproblem in GDA with limited intercell coordination, in which only a few scalars are shared among FBSs. In the EE-maximum scheme, we aim to maximize the global EE of all femtocells which is defined as the aggregate capacity over the aggregate power consumption in the femtocell networks. Leveraged by means of the lower-bound of logarithmic function, a centralized algorithm with limited computational complexity is proposed to solve the global EE maximization problem. Simulation results show that the proposed algorithms outperform previous schemes in terms of the minimum EE, fairness and global EE.
ER -