NOMA-Based Full-Duplex UAV Network with K-Means Clustering for Disaster Scenarios
2022 (English)In: IEEE Vehicular Technology Conference proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2022Conference paper, Published paper (Refereed)
Abstract [en]
In this paper, we propose and assess the performance of a downlink non-orthogonal multiple access (NOMA)based full-duplex (FD) unmanned aerial vehicle (UAV) network for disaster scenarios. The K-means algorithm is used to partition the user equipments (UEs) residing in the disaster region into a number of clusters. The UAVs are located at the cluster centers and act as decode-and-forward relays to secure coverage from an operational base station (BS) into the disaster region. The power-domain NOMA used at the BS and the UAVs operating in FD mode improve the system performance in terms of outage probability and sum rate compared to orthogonal multiple access and half-duplex mode. In particular, analytical expressions for the outage probability and sum rate are derived. Numerical results are provided to reveal the impact of system parameters on the performance of the NOMA-based FD UAV network over Nakagami-m fading which in turn illustrate design options for applications in disaster scenarios. © 2022 IEEE.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022.
Series
IEEE Vehicular Technology Conference, ISSN 1090-3038, E-ISSN 2577-2465
Keywords [en]
disaster scenarios, full-duplex relay, K-means algorithm, NOMA, outage probability, sum rate, UAV, Antennas, Disasters, Finite difference method, Unmanned aerial vehicles (UAV), Aerial vehicle, Disaster scenario, Duplex relay, Full-duplex, K-mean algorithms, Multiple access, Non-orthogonal, Non-orthogonal multiple access, Sum-rate, Unmanned aerial vehicle, K-means clustering
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:bth-24275DOI: 10.1109/VTC2022-Fall57202.2022.10012723ISI: 000927580600031Scopus ID: 2-s2.0-85147023723ISBN: 9781665454681 OAI: oai:DiVA.org:bth-24275DiVA, id: diva2:1735873
Conference
96th IEEE Vehicular Technology Conference, VTC 2022-Fall 2022, London, 26 September through 29 September 2022
2023-02-102023-02-102023-09-21Bibliographically approved