Joint Altitude and Beamwidth Optimization for UAV-Enabled Multiuser Communications (1711.02343v1)

Abstract: In this letter, we study multiuser communication systems enabled by an unmanned aerial vehicle (UAV) that is equipped with a directional antenna of adjustable beamwidth. We propose a fly-hover-and-communicate protocol where the ground terminals (GTs) are partitioned into disjoint clusters that are sequentially served by the UAV as it hovers above the corresponding cluster centers. We jointly optimize the UAV's flying altitude and antenna beamwidth for throughput optimization in three fundamental multiuser communication models, namely UAV-enabled downlink multicasting (MC), downlink broadcasting (BC), and uplink multiple access (MAC). Our results show that the optimal UAV altitude and antenna beamwidth critically depend on the communication model considered.

• The paper introduces a fly-hover-and-communicate protocol that jointly optimizes UAV altitude and beamwidth to enhance throughput in multiuser communications.
• Numerical analysis reveals that optimal altitude and beamwidth settings differ by communication model, favoring high altitude for multicasting and low altitude for broadcasting.
• The study offers actionable guidelines for UAV deployment in practical scenarios, such as temporary hotspot coverage and emergency communications.

Joint Altitude and Beamwidth Optimization for UAV-Enabled Multiuser Communications

This paper discusses the optimization of altitude and beamwidth for unmanned aerial vehicles (UAVs) engaged in multiuser communication, specifically addressing the UAV's role in enhancing throughput in three pertinent communication models: downlink multicasting (MC), downlink broadcasting (BC), and uplink multiple access (MAC). The research is premised on the impressive versatility of UAVs in wireless systems, offering on-demand deployment and superior line-of-sight (LoS) communication links, setting them apart from traditional terrestrial and satellite-based systems.

The proposed methodology introduces a "fly-hover-and-communicate" protocol wherein UAVs partition ground terminals (GTs) into clusters and serve each cluster sequentially when hovering above their respective centers. The research focuses on jointly optimizing the UAV's altitude and the beamwidth of its adaptive directional antenna to amplify communication throughput across the aforementioned models.

Numerical Results and Claims

The paper is distinguished by its detailed numerical analysis, which reveals notable variations in the optimal settings of UAV altitude and beamwidth contingent on the communication model. The findings indicate:

1. Downlink Multicasting (MC):
   • The optimal altitude for the UAV is the maximum feasible altitude, as the throughput, defined by the number of clustered GTs and their achieved communication rate, increases with altitude.
   • An optimal beamwidth exists that maximizes throughput, though it generally leans towards narrower beamwidths as altitude increases.
2. Downlink Broadcasting (BC):
   • The optimal operation involves the UAV flying at its minimum altitude. This is due to the partitioning of bandwidth across multiple GTs, where higher altitudes yield significant attenuation in individual GT rates.
   • The beamwidth should be as narrow as possible to maximize the sum rate across all GTs served via frequency division multiple access (FDMA).
3. Uplink Multiple Access (MAC):
   • Interestingly, the UAV altitude does not impact throughput, as the balance between GT rate and the number of GTs served neutralizes any variations due to altitude changes.
   • An optimal beamwidth maximizes throughput, balancing the trade-off between more GTs being served and higher achievable rates per GT.

Implications and Future Works

The insights derived from this paper have substantial implications for the design and deployment of UAV-enabled communication networks. With distinct optimal strategies for altitude and beamwidth per communication model, operators can tailor UAV operations more precisely to specific mission needs, thereby enhancing system efficiency and service quality.

Practically, these results could influence how UAVs are deployed in scenarios like temporary hotspot coverage, IoT data collection, or emergency communications. Acknowledging trade-offs between system complexity and performance gains, the optimization framework presented opens avenues for integrating real-world constraints such as channel fading and multi-UAV coordination, thereby enriching future research directions.

Overall, this paper furnishes a comprehensive analytical framework and practical guideline for UAV communication system design, encouraging further exploration of UAV mobility in three-dimensional space to fully harness its potential in emerging wireless networks.