Resource Allocation for Energy Efficiency Optimization in Heterogeneous Networks

Heterogeneous network (HetNet) deployment is considered a de facto solution for meeting the ever increasing mobile traffic demand. However, excessive power usage in such networks is a critical issue, particularly for mobile operators. Characterizing the fundamental energy efficiency (EE) performance...

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Bibliographic Details
Published in:IEEE journal on selected areas in communications Vol. 33; no. 10; pp. 2104 - 2117
Main Authors: Tang, Jie, So, Daniel K. C., Alsusa, Emad, Hamdi, Khairi Ashour, Shojaeifard, Arman
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Array signal processing
Energy efficiency
energy efficiency (EE)
Green radio (GR)
heterogeneous network (HetNet)
Interference
Licenses
Optimization
Optimized production technology
Real-time systems
resource allocation
Resource management
energy efficiency (EE)
resource allocation
heterogeneous network (HetNet)
Green radio (GR)
ISSN:0733-8716, 1558-0008
Online Access:Get full text
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Summary:Heterogeneous network (HetNet) deployment is considered a de facto solution for meeting the ever increasing mobile traffic demand. However, excessive power usage in such networks is a critical issue, particularly for mobile operators. Characterizing the fundamental energy efficiency (EE) performance of HetNets is therefore important for the design of green wireless systems. In this paper, we address the EE optimization problem for downlink two-tier HetNets comprised of a single macro-cell and multiple pico-cells. Considering a heterogeneous real-time and non-real-time traffic, transmit beamforming design and power allocation policies are jointly considered in order to optimize the system energy efficiency. The EE resource allocation problem under consideration is a mixed combinatorial and non-convex optimization problem, which is extremely difficult to solve. In order to reduce the computational complexity, we decompose the original problem with multiple inequality constraints into multiple optimization problems with single inequality constraint. For the latter problem, a two-layer resource allocation algorithm is proposed based on the quasiconcavity property of EE. Simulation results confirm the theoretical findings and demonstrate that the proposed resource allocation algorithm can efficiently approach the optimal EE.
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ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2015.2435351