Joint Optimization of Location, Beam, and Radio Resource for an Aerial Base Station With Controllable Directional Antennas | IEEE Journals & Magazine | IEEE Xplore

Joint Optimization of Location, Beam, and Radio Resource for an Aerial Base Station With Controllable Directional Antennas


Abstract:

Recent advancements in an unmanned aerial vehicle (UAV)-enabled network have demonstrated potential of a directional antenna to enhance network performance by utilizing l...Show More

Abstract:

Recent advancements in an unmanned aerial vehicle (UAV)-enabled network have demonstrated potential of a directional antenna to enhance network performance by utilizing limited resources more efficiently. In the UAV-enabled network where a directional antenna is utilized, controlling both its beam direction and beamwidth appropriately is an important issue in order to maximize its efficiency. Existing studies on the UAV-enabled network with a directional antenna, however, have primarily concentrated on adjusting antenna’s beamwidth with a fixed beam direction for simplicity. In this article, we explore joint optimization of both beam direction and beamwidth of a UAV equipped with controllable directional antennas. To this end, we consider a UAV-enabled network where the UAV functions as an aerial base station (ABS), relaying data from a ground base station (GBS) to multiple ground users (GUs), aiming at maximizing the sum rate for all GUs by controlling the location, beam direction, and beamwidth of the UAV and resource allocation. To address this complex problem, we develop an algorithm called Joint optimization of location, beam direction, beamwidth, and resource allocation (Joint-LDWR). Through comprehensive simulations, we show the outstanding performance of Joint-LDWR, focusing on its efficiency for enhancing network performance. The results highlight a significant benefit of simultaneously controlling beam direction and beamwidth of the ABS together with its location in the UAV-enabled network.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 16, 15 August 2024)
Page(s): 27571 - 27583
Date of Publication: 10 May 2024

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