Source-linked AI summary
Joint Altitude and Beamwidth Optimization for UAV-Enabled Multiuser Communications
Haiyun He, Shuowen Zhang, Yong Zeng, Rui Zhang
TL;DR
The paper studies how to jointly select UAV altitude and adjustable directional-antenna beamwidth for multiuser communications. It proposes clustered fly-hover-and-communicate service and analyzes downlink multicasting, downlink broadcasting, and uplink multiple access. The optimal settings depend critically on the communication model.
Problem
The paper examines joint UAV altitude and adjustable antenna beamwidth optimization for UAV-enabled multiuser communication systems.
Method
The proposed protocol partitions ground terminals into disjoint clusters and sequentially serves them while the UAV hovers above each cluster center.
Results
Optimal altitude and beamwidth settings critically depend on the communication model considered.
Takeaways & Limitations
Altitude should be maximum for downlink MC, minimum for downlink BC, and any feasible value for uplink MAC; beamwidth has model-dependent effects.
Abstract
from arXiv · showhide
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.
I. INTRODUCTION
The paper addresses joint UAV altitude and adjustable antenna beamwidth optimization for multiuser communications, using a fly-hover-and-communicate protocol across clustered ground terminals. It shows that optimal altitude and beamwidth settings differ fundamentally among downlink multicasting, downlink broadcasting, and uplink multiple access.
- Existing studies mainly assume omnidirectional antennas or directional antennas with fixed beamwidth, leaving adjustable-beamwidth UAV communication less explored.
- Adjusting beamwidth and altitude creates a coverage-capacity trade-off: broader beams or higher altitude cover more ground terminals but reduce each link’s capacity.
- The paper jointly optimizes UAV altitude and antenna beamwidth for throughput in UAV-enabled multiuser communication systems.
- The proposed fly-hover-and-communicate protocol partitions ground terminals into disjoint clusters and sequentially serves each cluster while hovering above its center.
- The study considers downlink multicasting, downlink broadcasting via FDMA, and uplink multiple access via FDMA.
- For altitude, the optimum is maximum for downlink MC, minimum for downlink BC, and any feasible value for uplink MAC; for beamwidth, it is interior for MC, minimum for BC, and marginal for MAC.
II. SYSTEM MODEL
The system uses a rotary-wing UAV with an adjustable directional antenna to sequentially serve uniformly distributed ground terminals partitioned into regular hexagonal cells. The model assumes outdoor rural LoS channels, delay-tolerant communications, and negligible flying time relative to hovering time.
- System model: The UAV acts as a flying base station at altitude H and serves K ground terminals distributed over a large area.The ground terminals are uniformly distributed with density A GTs/m^2.
- System model: The directional antenna has equal azimuth and elevation half-power beamwidths 2Θ, with adjustable half-beamwidth Θ.Its gain is modeled as direction-dependent, with main-lobe gain G0 and sidelobe gain g satisfying 0 < g ≪ G0.
- Coverage and clustering: The antenna main lobe covers a ground disk of radius ¯r = H tan Θ.When the UAV hovers above a cell center, the cell's ground terminals lie within the UAV coverage area.
- Assumptions: The model assumes rural outdoor GTs with predominantly LoS channels, delay-tolerant traffic, and a feasible altitude range [Hmin, Hmax] plus beamwidth range [Θmin, Θmax].The UAV's flying speed is sufficiently large that total hovering time is much larger than flying time.
- Fly-hover-and-communicate protocol: Under the fly-hover-and-communicate protocol, the UAV sequentially flies over cell centers and hovers for Ti seconds to communicate with each cell's terminals.The visiting order may be obtained by algorithms solving the travelling salesman problem to minimize total flying distance L.
III. DOWNLINK MULTICASTING
For downlink multicasting, the UAV delivers a common file to all ground terminals in each cell and optimizes altitude and beamwidth by balancing coverage size against cell-edge rate. The optimal altitude reaches Hmax, while the optimal beamwidth generally requires a one-dimensional search.
- Problem formulation: Downlink multicasting delivers a common file of total size ¯D bits to all ground terminals in the service area while minimizing mission completion time.The mission completion time is minimized by maximizing the average multicast rate ˜RMC.
- Multicast rate: The multicast transmission time for a cell is governed by its cell-edge achievable rate RMC(¯r), because RMC(r) decreases with terminal distance r.The file is completely delivered when Ti W RMC(¯r) ≥ ¯D.
- Optimization trade-off: As H or Θ increases, the number of terminals Ks increases while the cell-edge multicast rate RMC(¯r) decreases.This creates the altitude-and-beamwidth trade-off addressed by the optimization.
- Optimal altitude: For any fixed Θ, ˜RMC(H, Θ) is non-decreasing for H > 0, so the optimal altitude is H⋆ = Hmax.The result follows because the increase in Ks with altitude is more significant than the decrease in RMC(¯r).
- Optimal beamwidth: The optimal multicast half-beamwidth generally lacks a closed-form expression and is obtained through a one-dimensional search over [Θmin, Θmax].The difficulty arises from the complicated derivative of ˜RMC(H, Θ) with respect to Θ.
IV. DOWNLINK BROADCASTING
The downlink broadcasting model maximizes the sum throughput of independently served ground terminals using FDMA and equal power allocation. For any fixed beamwidth, throughput decreases with altitude, making the minimum altitude optimal, while beamwidth selection is evaluated numerically.
- Downlink BC sends independent information to ground terminals and maximizes their sum throughput over a communication period.
- The UAV serves terminals simultaneously using FDMA, with equal bandwidth per terminal and equal allocation of total downlink power.
- Increasing altitude or beamwidth reduces individual terminal rates while increasing the number of served terminals, creating a throughput trade-off.
- For any fixed beamwidth Θ, ˜RBC(H, Θ) decreases with altitude H when H > 0.
- The optimal BC altitude is HBC = Hmin for every feasible beamwidth, contrasting with the downlink MC case.
- A closed-form optimal beamwidth is generally unavailable, so its effect on ˜RBC(H, Θ) is examined numerically.
V. UPLINK MULTIPLE ACCESS
The uplink MAC model maximizes the sum throughput of independently transmitting ground terminals through joint altitude and beamwidth optimization. Its total rate is independent of altitude, while beamwidth is selected numerically because the rate first rises and then falls with beamwidth.
- Uplink MAC considers independent terminal transmissions and maximizes their sum throughput over a given period by jointly optimizing altitude and beamwidth.
- The UAV serves terminals using FDMA with equal bandwidth allocation, so maximizing sum throughput reduces to maximizing the total communication rate.
- The individual uplink rate decreases as altitude or beamwidth increases.
- The total uplink rate ˜RMAC(H, Θ) is independent of altitude because the lower individual rates offset the larger number of served terminals.
- The optimal beamwidth is obtained numerically by maximizing ˜RMAC(Θ), regardless of altitude.
VI. NUMERICAL RESULTS
Numerical results validate the analytical expressions for downlink MC, downlink BC, and uplink MAC. They show increasing MC throughput with altitude, decreasing BC throughput with altitude and beamwidth, and a unimodal MAC dependence on beamwidth.
- Downlink MC simulations validate the analysis: for fixed beamwidth, ˜RMC increases with altitude.
- For fixed altitude in downlink MC, ˜RMC first increases and then decreases as beamwidth increases.
- Downlink BC analytical results closely match simulations averaged over 100 independent ground-terminal location realizations.
- Downlink BC throughput decreases with both altitude and beamwidth, indicating that smaller values are desirable for maximizing ˜RBC.
- For each tested terminal density, ˜RMAC first increases and then decreases with beamwidth.
- The beamwidth maximizing ˜RMAC is approximately 1.3195 radians, or 79.7271 degrees, when feasible.
VII. CONCLUSIONS
The letter studies joint altitude and beamwidth optimization for three multiuser communication models under a proposed fly-hover-and-communicate protocol. It finds that optimal settings differ substantially across models and offers design insights for practical UAV-enabled communication systems.
- VII. CONCLUSIONS: The study jointly optimizes UAV altitude and antenna beamwidth in three fundamental multiuser communication models.The models are examined using the proposed fly-hover-and-communicate protocol.
- VII. CONCLUSIONS: Optimal altitude and beamwidth follow drastically different rules across the multiuser communication models.
- VII. CONCLUSIONS: The results provide insights for designing practical UAV-enabled communication systems.
- VII. CONCLUSIONS: Extending the results to fading UAV-GT channels or multiple UAVs is identified as future work.