Power-Efficient Communication in UAV-Aided Wireless Sensor Networks

Hua, Meng; Wang, Yi; Zhang, Zhengming; Li, Chunguo; Huang, Yongming; Yang, Liu

doi:10.1109/lcomm.2018.2822700

Cited by 137 publications

(84 citation statements)

References 11 publications

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“…By discretizing the whole flight period T into N equal-time slots with each slot length δ [5], the time-varying horizontal coordinate of the UAV at the nth time slot can be denoted as q[n] ∈ R 2×1 . As this paper focuses on the algorithm design, we adopt the same air-ground channel as in [5]- [8], [11], [14], i.e., the LoS model, which is also shown to be a good approximation for a UAV beyond a certain altitude. Additionally, it is assumed that the Doppler effect due to the UAV mobility can be well compensated at the user side.…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…The conventional way to solve problem (2) is to directly optimize p and q via AO [5]- [8], [11]. However, the resulting subproblem related to q is non-convex, and thus a globally optimal solution is not guaranteed by the SCA framework.…”

Section: System Model and Problem Formulationmentioning

confidence: 99%

“…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]. To guarantee a certain transmission rate, the authors in [8] minimize the UAV's total power consumption. Reference [9] and [10] investigate the communication in security systems by jointly optimizing the UAV trajectory and transmit power.…”

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.

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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.

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Section: System Model and Problem Formulationmentioning

confidence: 99%

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.

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“…UAVs are capable of supporting a wide range of civilian and military applications as a result of their flexible movements and ease of configurations [1,2]. UAVs can further be deployed to form collaborative networks with the ground nodes.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

Sayeed

Kumar

2018

Drones

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Multi-Unmanned Aerial Vehicle (UAV) enabled Wireless Sensor Networks (WSNs) provide a wide range of applications, covering civilian and military expeditions along with geographical navigation, control, and reconnaissance. The coordinated networks formed between the UAVs and the WSNs help in enhancing the issues related to quality as well as coverage. The overall coverage issues result in starvation as an effect of long waiting time for the nodes, while forwarding the traffic. The coverage problem can be resolved by an intelligent choice of UAV way-points. Therefore, a specialized UAV mobility model is required which takes into account the topological structure as well as the importance of strategic locations to fix UAV way-points and decide the data transmission paradigm. To resolve this problem, a novel mobility model is proposed, which takes into account the attraction factor for setting up the way-points for UAV movements. The model is capable of deciding between the locations which result in more coverage, increased throughput with lesser number of UAVs employed, as justified by the simulation results and comparative evaluations.

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Multiple input single output aerial base station‐assisted networks: Joint 3D beam‐forming, aerial base station assignment, 3D placement, and radio resource allocation

Azizi

Mokari

2020

Trans Emerging Tel Tech

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In this article, we propose a novel method according to which joint aerial base station (ABS) assignment, three‐dimensional placement (3DP), three‐dimensional beam‐forming (3DB), and radio resource allocation are considered for multiple input single output (MISO) ABS‐based networks with orthogonal frequency division multiple access (OFDMA) technology. We aim to maximize the instantaneous data rate subject to some practical constraints. In light of the fact that our optimization problem is mixed‐integer nonlinear programming (MINLP) with high computational complexity, we propose a low complex and practical approach. Therefore, we resort to an alternate method by which the main optimization problem decomposes into three subproblems. Then we solve the resulting subproblems via linear approximation method, matching theory, and mesh adaptive direct search (MADS) algorithm. In order to shed light on our proposed approach, we decompose the proposed scenario into some cases with fewer optimization variables and compare them with our main problem. Our proposed approach boosts the instantaneous data rate compared to the decomposed cases with fewer optimization variables. Via simulation, we study the effect of various parameters like numbers of users, ABSs, and maximum transmission powers on the network performance. Finally, we analyze the network performance for suburban and urban environments considering various number of ABSs.

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Power-Efficient Communication in UAV-Aided Wireless Sensor Networks

Cited by 137 publications

References 11 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

An Efficient Mobility Model for Improving Transmissions in Multi-UAVs Enabled WSNs

Multiple input single output aerial base station‐assisted networks: Joint 3D beam‐forming, aerial base station assignment, 3D placement, and radio resource allocation

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