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Path Loss Predictions in the VHF and UHF Bands Within Urban Environments: Experimental Investigation of Empirical, Heuristics and Geospatial Models
- Source :
- BASE-Bielefeld Academic Search Engine, RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname, IEEE Access, Vol 7, Pp 77293-77307 (2019)
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers, 2019.
-
Abstract
- [EN] Deep knowledge of how radio waves behave in a practical wireless channel is required for effective planning and deployment of radio access networks in urban environments. Empirical propagation models are popular for their simplicity, but they are prone to introduce high prediction errors. Different heuristic methods and geospatial approaches have been developed to further reduce path loss prediction error. However, the efficacy of these new techniques in built-up areas should be experimentally verified. In this paper, the efficiencies of empirical, heuristic, and geospatial methods for signal fading predictions in the very high frequency (VHF) and ultra-high frequency (UHF) bands in typical urban environments are evaluated and analyzed. Electromagnetic field strength measurements are performed at different test locations within four selected cities in Nigeria. The data collected are used to develop path loss models based on artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and Kriging techniques. The prediction results of the developed models are compared with those of selected empirical models and field measured data. Apart from Egli and ECC-33, the root mean squared error (RMSE) produced by all other models under investigation are considered acceptable. Specifically, the ANN and ANFIS models yielded the lowest prediction errors. However, the empirical models have the lowest standard deviation errors across all the bands. The findings of this study will help radio network engineers to achieve efficient radio coverage estimation; determine the optimal base station location; make a proper frequency allocation; select the most suitable antenna; and perform interference feasibility studies.<br />This work was supported jointly by the funding received from IoT-Enabled Smart and Connected Communities (SmartCU) Research Cluster and the Center for Research, Innovation and Discovery (CUCRID) of Covenant University, Ota, Nigeria.
- Subjects :
- Geospatial analysis
General Computer Science
Computer science
ComputingMilieux_LEGALASPECTSOFCOMPUTING
Backpropagation
02 engineering and technology
Reuse
Permission
computer.software_genre
Radio propagation
03 medical and health sciences
Server
0202 electrical engineering, electronic engineering, information engineering
Path loss
General Materials Science
ANFIS
030304 developmental biology
0303 health sciences
Database
Artificial neural networks
General Engineering
020206 networking & telecommunications
ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES
Kriging
Ultra high frequency
lcsh:Electrical engineering. Electronics. Nuclear engineering
Heuristics
lcsh:TK1-9971
computer
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- BASE-Bielefeld Academic Search Engine, RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname, IEEE Access, Vol 7, Pp 77293-77307 (2019)
- Accession number :
- edsair.doi.dedup.....fb8c28dcbadaa88d806cebd1d2680e91