NDLI: Optimal WCDMA network planning by multiobjective evolutionary algorithm with problem-specific genetic operation

Content Provider	Springer Nature Link
Author	Gu, Fangqing Liu, Hai lin Cheung, Yiu Ming Xie, Shengli
Copyright Year	2014
Abstract	The wideband code division multiple access (WCDMA) network planning problem requires to determine the location and the configuration parameters of the base stations (BSs) so as to maximize the capacity and minimize the installation cost. This problem can be formulated as a complex set covering problem. Compared to the classical set covering problems, the coverage area of each BS is unknown in advance. This makes that the selection of each BS location and configuration parameters is determined by the location and configuration parameters of the neighbor BSs. Accordingly, we will conduct a competition and cooperation model based on the re-covered area of the BSs to measure the relationship of the BSs. Then, an efficient genetic operation based on this model is proposed to generate new-quality solutions. Further, four BS configuration parameters, i.e., the antenna height, antenna tilt, sector orientation and pilot signal power, are taken into account as well. Since there are too many combination levels of the configuration parameters, an encoding method based on orthogonal design is presented to reduce the search space. Subsequently, we merge the proposed encoding method and genetic operation into the multiobjective evolutionary algorithm-based decomposition (MOEA/D-M2M) to solve the WCDMA network planning problem. Simulation results show the efficacy of the proposed encoding and genetic operation in comparison with the existing counterpart.
Starting Page	679
Ending Page	703
Page Count	25
File Format	PDF
ISSN	02191377
Journal	Knowledge and Information Systems
Volume Number	45
Issue Number	3
e-ISSN	02193116
Language	English
Publisher	Springer London
Publisher Date	2014-10-31
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Set covering problem Wireless network planning Multiobjective evolutionary algorithm Orthogonal design Information Systems and Communication Service IT in Business
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Information Systems Human-Computer Interaction Hardware and Architecture Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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