Energy efficient deployment of multiple UAV mounted base stations: a machine learning-based approach Online publication date: Mon, 07-Nov-2022
by Dilip Mandloi; Rohit Sharma; Rajeev Arya
International Journal of Ultra Wideband Communications and Systems (IJUWBCS), Vol. 5, No. 3, 2022
Abstract: This paper presents an energy efficient approach for the deployment of multiple 5G enabled unmanned aerial vehicle-mounted base stations (UmBSs) in the area where existing network infrastructure has got demolished due to a natural disaster. In our proposed approach, K-means, a machine learning-based technique, is used to position UmBSs based upon which their transmit power is optimised by solving a convex optimisation problem under the constraints of maximum transmit power of UmBS, maximum height of UmBS, and channel capacity. To ensure the QoS requirements, the association of UEs and UmBS is subjected to the constraint of minimum signal to interference plus noise ratio (SINR) threshold. The effectiveness of the proposed approach is demonstrated in terms of average SINR, average channel capacity, and the number of users served. The performance of the proposed approach is compared with the two baseline approaches through MATLAB simulations.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Ultra Wideband Communications and Systems (IJUWBCS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook