Trajectory Design for Throughput Maximization in UAV-Assisted Communication System

Gupta, Nishant; Agarwal, Suneeta; Mishra, Deepak

doi:10.1109/tgcn.2021.3085867

Cited by 30 publications

(9 citation statements)

References 37 publications

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“…Regarding access techniques, we found that 31.53% of the analyzed papers have modeled various techniques, including FDMA, OFDMA, TDMA, and NOMA. Specifically, 12.3% of the papers have focused on FDMA (i.e., ( [63], [72], [77], [88], [92], [107], [112], [120], [134], [135], [149], [165], [173], [182], [189], [190]) as depicted in Figure 10. For example, studies such as You et al [182] and Hayanjneh et al [149] employed FDMA, where UAVs divide the available bandwidth into sub-bands, with each frequency sub-band transmitting data independently to a ground user.…”

Section: B: Access and Interference Techniquementioning

confidence: 99%

“…Citation information: DOI 10.1109/OJVT.2024.3379751 a sequence of simpler problems, sometimes even incorporating non-convex constraints. Also, some studies like [63], [69], [92], [118], [119], [152] use Bisections research or their variant Golden section search or line search in polynomial time to resolve the MINLP. Additionally, certain studies, such as [63], [69], [92], [118], [119], [152], utilize Bisection research or their variants, like the Golden Section Search or Line Search.…”

Section: Volume 29mentioning

confidence: 99%

“…Also, some studies like [63], [69], [92], [118], [119], [152] use Bisections research or their variant Golden section search or line search in polynomial time to resolve the MINLP. Additionally, certain studies, such as [63], [69], [92], [118], [119], [152], utilize Bisection research or their variants, like the Golden Section Search or Line Search. These techniques resolve MINLP problems efficiently within polynomial time.…”

Section: Volume 29mentioning

confidence: 99%

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3D Placement Optimization in UAV-Enabled Communications: A Systematic Mapping Study

Carvajal-Rodríguez,

Guamán,

Tipantuña

et al. 2024

IEEE Open J. Veh. Technol.

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Unmanned aerial vehicles (UAVs) have seen remarkable improvements in their flight capabilities and computational power. Their applications span various domains, such as agriculture, military, and communications. To improve communication quality and coverage in UAV-enabled systems, understanding effective placement techniques is crucial. While research has explored optimal UAV placement in two dimensions, there is a need for a comprehensive three-dimensional (3D) analysis, particularly for resource optimization. This article presents a systematic mapping study on 3D placement in UAV-enabled communication systems, incorporating a threat analysis for the reliability of the results. It provides valuable insights for future research on 3D placement optimization techniques, specifically examining optimization objectives, model system features, problem types, and solution strategies. Our research reveals, on one hand, an emphasis on optimizing data rate throughput, power transmission, and ground coverage, and a predominant use of large-scale fading in the air-to-ground channel model; on the other hand, heuristic algorithms prevail as the solution strategy. Moreover, we identify gaps in achieving critical objectives such as the probability of outage, deployment costs, quality of experience, and spectrum optimization. This highlights the need for further exploration in the formulation aspects of the system, which includes small-scale fading, access techniques, and interference management.

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Section: B: Access and Interference Techniquementioning

confidence: 99%

Section: Volume 29mentioning

confidence: 99%

Section: Volume 29mentioning

confidence: 99%

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3D Placement Optimization in UAV-Enabled Communications: A Systematic Mapping Study

Carvajal-Rodríguez,

Guamán,

Tipantuña

et al. 2024

IEEE Open J. Veh. Technol.

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“…But it considered the online decision mode and neglected UAV's flight energy consumption. The authors in [44] proposed an iterative solution for obtaining optimal UAV trajectory in online mode, which took into account the same propulsion energy consumption as in [16]. However, the optimization of transmission power was neglected in this paper.…”

Section: A Related Workmentioning

confidence: 99%

Energy-Efficient UAV-Relaying 5G/6G Spectrum Sharing Networks: Interference Coordination With Power Management and Trajectory Design

Wang

Jia

et al. 2022

IEEE Open J. Commun. Soc.

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As massive ground users access wireless networks with limited available spectrum, coexisting users that share the same spectrum band severely interfere with each other. Moreover, communication pairs without direct communication links may suffer from severe outage issues. In this paper, unmanned aerial vehicle (UAV) relaying-assisted interference coordination is proposed to enhance data transmission reliability by 1) relaying transmission, and 2) alleviating mutual interference among ground users. To efficiently utilize confined UAV energy such that the UAV relaying service life can be significantly prolonged, the full-duplex (FD) technique is exploited. An exact energy efficiency (EE) maximization problem is formulated, which jointly optimizes throughput and UAV energy consumption. Different from the traditional offline method, online power management and trajectory designs are performed under the information causality and rate constraints. Considering that power management and trajectory are coupled, we design a block coordinate descent method to efficiently solve the optimization problem. Numerical results demonstrate that the proposed scheme outperforms existing schemes, and the EE is about 30% and 46% higher than those of the genetic algorithm and half-duplex scheme, respectively. Moreover, impacts of different positions and the maximum power of ground users on the EE have been demonstrated.

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“…Similarly, outage probability, as well as throughput, is optimized in Reference 21 for multiple UAV‐assisted cooperative communication networks to enhance the performance of the UAV‐aided relay network. In Reference 22, the trajectory optimization for a UAV‐assisted communication network has been discussed to maximize the average sum rate of all the users.…”

Section: Introductionmentioning

confidence: 99%

A novel multi‐hop routing structure for throughput maximization in unmanned aerial vehicle assisted flying ad‐hoc networks

Mittal

Shah

Agarwal

2022

Trans Emerging Tel Tech

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Unmanned aerial vehicle (UAV) aided wireless communication has many potential uses to improve connectivity in the harsh environments due to its high mobility and flexible deployment. To extend the coverage, multi‐hop communication with multiple UAVs as relays has become the prominent scheme in today's wireless network. In this article, we investigate the problem of generating a multi‐hop routing structure for data transmission to maximize the overall network throughput of a flying ad‐hoc network using UAVs. Specifically, we propose an optimization problem to jointly select a communication link and its transmission power so that the overall network throughput for a given total power budget is maximized. The problem is nonconvex over selected metrics, thus making it an NP‐hard problem. Without loss of generality, we consider the Dijkstra‐based shortest‐path tree as a routing structure, thereby converting the original problem into a solvable convex problem over the transmission link metric. We observe Dijkstra‐based routing is not optimal in our scenario, thus we propose a low complexity link swap approach to further improve the network throughput by exchanging appropriate child‐parent links of UAVs. Results are numerically validated, and optimal design insights are provided.

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Trajectory Design for Throughput Maximization in UAV-Assisted Communication System

Cited by 30 publications

References 37 publications

3D Placement Optimization in UAV-Enabled Communications: A Systematic Mapping Study

3D Placement Optimization in UAV-Enabled Communications: A Systematic Mapping Study

Energy-Efficient UAV-Relaying 5G/6G Spectrum Sharing Networks: Interference Coordination With Power Management and Trajectory Design

A novel multi‐hop routing structure for throughput maximization in unmanned aerial vehicle assisted flying ad‐hoc networks

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