A data driven approach in less expensive robust transmitting coverage and power optimization

Parnianifard, A, Mumtaz, S ORCID: https://orcid.org/0000-0001-6364-6149, Chaudhary, S, Imran, MA and Wuttisittikulkij, L, 2022. A data driven approach in less expensive robust transmitting coverage and power optimization. Scientific Reports, 12: 17725. ISSN 2045-2322

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Abstract

This paper aims the development of a new reduced-cost algorithm for a multi-objective robust transmitter placement under uncertainty. Toward this end, we propose a new hybrid Kriging/Grey Wolf Optimizer (GWO) approach combined with robust design optimization to estimate the set of Pareto frontier by searching robustness as well as accuracy (lower objective function) in a design space. We consider minimization of the energy power consumption for transmitting as well as maximization of signal coverage in a multi-objective robust optimization model. The reliability of the model to control signal overlap for multiple transmitting antennas is also provided. To smooth computational cost, the proposed method instead of evaluating all receiver test points in each optimization iteration approximates signal coverages using Kriging interpolation to obtain optimal transmitter positions. The results demonstrate the utility and the efficiency of the proposed method in rendering the robust optimal design and analyzing the sensitivity of the transmitter placement problem under practically less-expensive computational efforts (350% and 320% less than computational time elapsed using standalone GWO and NSGAII respectively).

Item Type:	Journal article
Publication Title:	Scientific Reports
Creators:	Parnianifard, A., Mumtaz, S., Chaudhary, S., Imran, M.A. and Wuttisittikulkij, L.
Publisher:	Springer
Date:	2022
Volume:	12
ISSN:	2045-2322
Identifiers:	Number Type 10.1038/s41598-022-21490-z DOI 1622197 Other
Rights:	This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	25 Nov 2022 15:46
Last Modified:	25 Nov 2022 15:46
URI:	https://irep.ntu.ac.uk/id/eprint/47509

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