University of Oulu

C. K. Singh, P. K. Upadhyay, J. Lehtomäki and M. Juntti, "Outage Performance with Deep Learning Analysis for UAV-Borne IRS Relaying NOMA Systems with Hardware Impairments," 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall), London, United Kingdom, 2022, pp. 1-7, doi: 10.1109/VTC2022-Fall57202.2022.10012811.

Outage performance with deep learning analysis for UAV-borne IRS relaying NOMA systems with hardware impairments

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Author: Singh, Chandan Kumar1; Upadhyay, Prabhat Kumar1,2; Lehtomäki, Janne2;
Organizations: 1Department of Electrical Engineering, Indian Institute of Technology Indore, Indore 453552, Madhya Pradesh, India
2Centre for Wireless Communications (CWC), University of Oulu, 90014 Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2023-02-14


While intelligent reflecting surfaces (IRSs) and non-orthogonal multiple access (NOMA) techniques have shown great potential to boost the spectral and energy efficiency for future wireless networks, unmanned aerial vehicles (UAVs) are committed for enhancing the wireless connectivity with fast and flexible deployment. In this regard, we study an integration of an IRS in UAV-enabled wireless relaying system using NOMA transmissions. We also count on the impacts of residual hardware impairments (HIs) in user devices and imperfect successive interference cancellation (SIC) in NOMA, which are inevitable in practical system implementation. We analyze the system performance by deriving the closed-form expressions of outage probability (OP) and system throughput over the line-of-sight (LoS) Rician fading channels for the aerial links. We further pursue asymptotic OP analysis to reveal useful insights on the achievable diversity order. Above all, we present a deep neural network (DNN) framework for OP prediction with a short execution time under the dynamic stochastic environment. Our results validate the theoretical proposition and accentuate the performance advantages of the proposed UAV-borne IRS relaying NOMA system.

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Series: IEEE Vehicular Technology Conference
ISSN: 1090-3038
ISSN-L: 1090-3038
ISBN: 978-1-6654-5468-1
ISBN Print: 978-1-6654-5469-8
Pages: 1 - 7
Article number: 10012811
DOI: 10.1109/vtc2022-fall57202.2022.10012811
Host publication: 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)
Conference: IEEE Vehicular Technology Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This research work is supported by the Nokia Foundation Visiting Professor Grant and the Visvesvaraya PhD Scheme of Ministry of Electronics & Information Technology (MeitY), Government of India, being implemented by Digital India Corporation (formerly Media Lab Asia), and in part by the Academy of Finland 6Genesis Flagship under Grant 318927.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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