Energy efficiency 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 the mobile operators. Characterizing the fundamental energy efficiency (EE) perform...

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Vydané v:2015 IEEE International Conference on Communications (ICC) s. 1 - 6
Hlavní autori: Jie Tang, So, Daniel K. C., Alsusa, Emad, Hamdi, Khairi, Shojaeifard, Arman
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.06.2015
Predmet:
Downlink
Interference
Optimization
Real-time systems
Resource management
Signal to noise ratio
Uplink
ISSN:1550-3607
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Popis
Shrnutí: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 the 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.
ISSN:1550-3607
DOI:10.1109/ICC.2015.7248289