DocumentCode :
31797
Title :
Improving Small-Cell Performance Through Switched Multielement Antenna Systems in Heterogeneous Networks
Author :
Razavi, Rouzbeh ; Ho, Lester ; Claussen, Holger ; Lopez-Perez, David
Author_Institution :
Bell Labs., Alcatel-Lucent, Dublin, Ireland
Volume :
64
Issue :
7
fYear :
2015
fDate :
Jul-15
Firstpage :
3140
Lastpage :
3151
Abstract :
This paper introduces an effective yet simple and practical solution to improve small-cell performance in heterogeneous networks (HetNets). The proposed solution is based on deploying a switched multielement antenna (MEA) system capable of generating a variety of antenna patterns at small-cell base stations (BSs). Then, antenna patterns are assigned to user equipment (UE) in a dynamic basis. The antenna pattern selection for each UE is considered to be a supervised machine learning classification problem, in which the small-cell BS seek to find the optimal antenna pattern to serve each UE according to its measurement reports (i.e., UE radio-frequency fingerprint). Simulation results confirm the feasibility of the proposed approach, despite potential inaccuracies in UE measurement reports. Compared with the existing solutions comprising a single omnidirectional antenna (ODA), the proposed approach results in a 68% additional network-wide capacity increase. In addition, a technoeconomic analysis is presented in this paper, indicating the economic advantages of deploying the proposed scheme.
Keywords :
antenna arrays; antenna radiation patterns; cellular radio; learning (artificial intelligence); telecommunication computing; HetNet; antenna pattern selection; heterogeneous network; small-cell base station; small-cell performance improvement; supervised machine learning classification problem; switched multielement antenna system; user equipment; Antenna measurements; Directive antennas; Interference; Radio frequency; Switches; Training; Classification; heterogeneous networks (HetNets); interference management; machine learning; multielement antenna (MEA); picocells; radio frequency (RF) fingerprint; small cells;
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2014.2348319
Filename :
6879477
Link To Document :
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