Soft computing methods for WiMax Network Planning on 3D Geographical Information Systems
http://repository.vnu.edu.vn/handle/VNU_123/28686
In
this paper, we present an application of soft computing methods for the problem
of WiMax Network Planning on 3D Geographical Information Systems (3D GIS) that
optimizes both performance of the network (Coverage and Quality-of-Service) and
investment costs (the number of base stations and sectors).
A
pre-processing procedure using latest results of parallel Random Forest
classification algorithm to determine valid positions of base stations on a
terrain of 3D GIS is proposed.
Based
upon those positions, we design a generalized mathematical model taking into
account 3D obstacles in path loss calculation process.
In
order to generate optimal solutions of the model, a hybrid algorithm between
greedy BTP and improved Particle Swarm Optimization incorporated with parallel
computing is presented.
Experimental
validation of the proposed method in comparison with other relevant ones is
performed.
Title:
Soft computing methods for WiMax Network Planning on 3D Geographical Information Systems | |
Authors: | Le Hoang Son Pham Huy Thong |
Keywords: | 3D GIS Particle Swarm Optimization Parallel Random Forest Soft computing WiMax Network Planning |
Issue Date: | 2017 |
Publisher: | ACADEMIC PRESS INC ELSEVIER SCIENCE, 525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA |
Citation: | ISIKNOWLEDGE |
Abstract: | In this paper, we present an application of soft computing methods for the problem of WiMax Network Planning on 3D Geographical Information Systems (3D GIS) that optimizes both performance of the network (Coverage and Quality-of-Service) and investment costs (the number of base stations and sectors). A pre-processing procedure using latest results of parallel Random Forest classification algorithm to determine valid positions of base stations on a terrain of 3D GIS is proposed. Based upon those positions, we design a generalized mathematical model taking into account 3D obstacles in path loss calculation process. In order to generate optimal solutions of the model, a hybrid algorithm between greedy BTP and improved Particle Swarm Optimization incorporated with parallel computing is presented. Experimental validation of the proposed method in comparison with other relevant ones is performed. |
Description: | TNS07000 ; JOURNAL OF COMPUTER AND SYSTEM SCIENCES Volume: 83 Issue: 1 Pages: 159-179 Published: FEB 2017 |
URI: | http://repository.vnu.edu.vn/handle/VNU_123/28686 http://www.sciencedirect.com/science/article/pii/S0022000016300514 |
ISSN: | 0022-0000 1090-2724 |
Appears in Collections: | Bài báo của ĐHQGHN trong Web of Science |
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