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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xianda Li Xing Zhang Wenbo Wang |
| Copyright Year | 2014 |
| Description | Author affiliation: Wireless Signal Process. & Network Lab., Beijing Univ. of Posts & Telecommun., Beijing, China (Xianda Li; Xing Zhang; Wenbo Wang) |
| Abstract | With the exponential growth of wireless network data traffic and mobile users, traditional single layer homogeneous network cannot meet the increasing high-speed traffic demand. As a solution, heterogeneous networks (HetNet) are considered as a promising architecture to fulfill the challenge. At the same time, energy consumption problem has become one of the most challenging problems due to the fast expansion of wireless network scale. Traditionally, network operators are more concerned about the coverage and capacity problem when planning cellular networks, rather than the energy efficiency of the network. In this paper, we propose an energy-efficient micro base station (BS) planning strategy based on realistic traffic data in HetNet architecture. A genetic algorithm (GA) is introduced to solve the optimization problem. By carefully selecting algorithm parameters, the algorithm can produce a set of near optimum solutions. The simulation results show that the energy efficiency and traffic coverage ratio are both improved by the deployment of micro BSs. |
| Sponsorship | IEEE Vietnam Sect. |
| Starting Page | 122 |
| Ending Page | 127 |
| File Size | 1410321 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479929030 |
| DOI | 10.1109/ComManTel.2014.6825591 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-04-27 |
| Publisher Place | Vietnam |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Base stations Energy consumption HetNet Sociology Genetic Algorithm Cell Planning Planning Statistics Energy Efficiency Optimization Genetic algorithms |
| Content Type | Text |
| Resource Type | Article |
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