Unmanned Aerial Vehicle-Aided Communications: Joint Transmit Power and Trajectory Optimization

Wang, Haichao; Ren, Guochun; Jin, Chen; Ding, Guoru; Yang, Yijun

doi:10.1109/lwc.2018.2792435

Cited by 96 publications

(54 citation statements)

References 14 publications

(25 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Assume the existence of another solution of problem (4), i.e., β ′ with associated objective value τ ′ > τ . Then one can always find a constant c = τ τ ′ < 1 to scale down β ′ without violating the constraint of problem (6). The resulting solution cβ ′ has smaller power than P max , which contradicts optimality of β ⋆ .…”

Section: Efficient Alternative Optimization a Proposed Methodsmentioning

confidence: 98%

“…Denote the downlink transmit power of UAV allocated to user k in time slot n by p k [n] ≥ 0. It is assumed that the whole transmission bandwidth B in Hertz(Hz) is equally assigned to every user as in [6]. Thus the instantaneous transmission rate to user k in time slot n, denoted by R k [n] in bits/second (bps), can be expressed as…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…A more general trajectory design, by taking into account the practical constraints on the UAV's maximum speed, is studied in a UAV-enabled relaying system for serving single ground user [5]. With equallyallocated spectrum bandwidth, the authors in [6] investigate the throughput maximization problem by jointly designing transmit power and trajectory via a frequency-division multiple access (FDMA). Considering a minimum user rate ratio, an iterative optimization framework is proposed to maximize the system max-min average throughput by jointly optimizing the power and trajectory design [7].…”

Section: Introductionmentioning

confidence: 99%

“…In this letter, we investigate a UAV-enabled multiuser system, where the UAV communicates with ground users via FDMA, with the aim to attain the optimal max-min average throughput, under the maximum speed control as well as the total transmit power constraint, similar to [6]- [8]. The conventional methods (such as [7] and [11]) to tackle this problem are based on the AO method by iteratively updating power and trajectory until convergence, resulting in a nonconvex trajectory subproblem.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Novel Alternative Optimization Method for Joint Power and Trajectory Design in UAV-Enabled Wireless Network

Tang

et al. 2019

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

This letter aims to maximize the average throughput via the joint design of the transmit power and trajectory for unmanned aerial vehicle (UAV)-enabled network. The conventional way to tackle this problem is based on the alternating optimization (AO) method by iteratively updating power and trajectory until convergence, resulting in a non-convex trajectory subproblem which is difficult to deal with. To develop more efficient methods, we propose a novel AO method by incorporating both power and trajectory into an intermediate variable, and then iteratively updating power and the newly introduced variable. This novel variable transformation makes it easier to decompose the original problem into two convex subproblems, namely a throughput maximization subproblem and a feasibility subproblem. Consequently, both of these subproblems can be solved in a globally optimal fashion. We further propose a lowcomplexity algorithm for the feasibility subproblem by exploiting the alternating directional method of multipliers (ADMM), whose updating step is performed in closed-form solutions. Simulation results demonstrate that our proposed method reduces the computation time by orders of magnitude, while achieving higher performance than the conventional methods.Index Terms-Alternative Optimization, ADMM, joint power and trajectory design, unmanned aerial vehicle, throughput maximization.

show abstract

Section: Efficient Alternative Optimization a Proposed Methodsmentioning

confidence: 98%

Section: System Model and Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Alternative Optimization Method for Joint Power and Trajectory Design in UAV-Enabled Wireless Network

Tang

et al. 2019

IEEE Trans. Veh. Technol.

View full text Add to dashboard Cite

show abstract

“…Moreover, it achieves the highest average payoff and energy efficiency among the benchmark greedy path and circular path schemes. throughput within a given time length in [14]. Furthermore, the authors in [15] proposed a new cyclical multiple access scheme that the UAV flies cyclically above the ground, and characterized the max-min throughput by optimally allocating the transmission time to ground terminals based on the UAV position.…”

mentioning

confidence: 99%

Trajectory Design for UAV Assisted Wireless Networks

Tang

Cheung

Lok

2019

2019 IEEE Global Communications Conference (GLOBECOM)

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) can enhance the performance of cellular networks, due to their high mobility and efficient deployment. In this paper, we present a first study on how the user mobility affects the UAVs' trajectories of a multiple-UAV assisted wireless communication system. Specifically, we consider the UAVs are deployed as aerial base stations to serve ground users who move between different regions. We maximize the throughput of ground users in the downlink communication by optimizing the UAVs' trajectories, while taking into account the impact of the user mobility, propulsion energy consumption, and UAVs' mutual interference. We formulate the problem as a route selection problem in an acyclic directed graph. Each vertex represents a task associated with a reward on the average user throughput in a region-time point, while each edge is associated with a cost on the energy propulsion consumption during flying and hovering. For the centralized trajectory design, we first propose the shortest path scheme that determines the optimal trajectory for the single UAV case. We also propose the centralized route selection (CRS) scheme to systematically compute the optimal trajectories for the more general multiple-UAV case. Due to the NP-hardness of the centralized problem, we consider the distributed trajectory design that each UAV selects its trajectory autonomously. We formulate the UAVs' interactions as a route selection game. We prove that it is a potential game with the finite improvement property, which guarantees our proposed distributed route selection (DRS) scheme will converge to a pure strategy Nash equilibrium within a finite number of iterations. Simulation results show that our DRS scheme results in a near-optimal performance that achieves 95% of the maximal total payoff. Moreover, it achieves the highest average payoff and energy efficiency among the benchmark greedy path and circular path schemes. throughput within a given time length in [14]. Furthermore, the authors in [15] proposed a new cyclical multiple access scheme that the UAV flies cyclically above the ground, and characterized the max-min throughput by optimally allocating the transmission time to ground terminals based on the UAV position. In [16], a UAV was dispatched to disseminate a common file to a set of ground terminals (GTs) and the authors aimed to design the UAV trajectory to minimize its mission completion time, and [17] optimized the trajectory design to maximize the amount of energy transferred to all energy receivers during a finite charging period. The above studies mainly focus on communication performance improvement and the technical challenges that exist in trajectory design are energy limitation, interference mitigation, and user mobility. Since UAVs consume a significant amount of energy to support their mobility, it motivated the design of the energy-efficient UAV communication via trajectory design in [19]-[22]. The authors of [19] focused on the energy efficient maximization of a fixed-wing UAV enabled commu...

show abstract

Optimal 3D trajectory design for UAV‐assisted cellular communications in the post‐disaster scenarios

Deepak

Politis

2023

Internet Technology Letters

View full text Add to dashboard Cite

Unmanned aerial vehicle (UAV) assisted wireless communication has been recently proposed as an effective solution to provide wireless connectivity to ground users which can improve the network coverage area and spectral efficiency. In this paper, we consider the post-disaster network scenario where users are isolated from the network infrastructure. We investigate the best positioning of the UAV in terms of the optimal trajectory as well as UAV vertical location to cover as many ground users as possible to improve the spectral efficiency. When the trajectory is optimized, the optimal transmit power within the available power budget is then obtained. The simulation results demonstrate that the proposed UAV-enabled wireless communication technique improves the overall spectral and energy efficiency.

show abstract

Unmanned Aerial Vehicle-Aided Communications: Joint Transmit Power and Trajectory Optimization

Cited by 96 publications

References 14 publications

A Novel Alternative Optimization Method for Joint Power and Trajectory Design in UAV-Enabled Wireless Network

A Novel Alternative Optimization Method for Joint Power and Trajectory Design in UAV-Enabled Wireless Network

Trajectory Design for UAV Assisted Wireless Networks

Optimal 3D trajectory design for UAV‐assisted cellular communications in the post‐disaster scenarios

Contact Info

Product

Resources

About