Throughput Maximization in Multi-UAV Enabled Communication Systems With Difference Consideration

Xu, Yu; Xiao, Lin; Yang, Dingcheng; Wu, Qingqing; Cuthbert, Laurie

doi:10.1109/access.2018.2872736

Cited by 38 publications

(16 citation statements)

References 23 publications

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“…The works of Chen et al 34 and Sohail et al, 35 find the efficient radio resource allocation of a single ABS in order to maximize the throughput. In the work of Xiao et al, 36 the efficient radio resource allocation of ABSs is optimized in order to maximize the throughput. Xue et al 37 find efficient radio resource allocation for a single ABS to maximize data dissemination.…”

Section: Related Workmentioning

confidence: 99%

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Azizi

Mokari

2019

Trans Emerging Tel Tech

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In this paper, a novel method for joint resource allocation, three-dimensional placement, and user association as a predominant problem in the internet of things (IoTs) networks is proposed. We consider two kinds of channel models for the links between users and aerial base stations (ABSs), namely (a) line of sight (LoS) model and (b) generalized model. In the LoS case, all the ABSs should establish LoS communications path toward IoT users. In the generalized case, the ABSs channels toward the IoT users could be LoS or nonline of sight. We propose four different scenarios, namely interference-free (IF)-LoS, IF-Generalized, interference-included (II)-LoS, and II-Generalized. The IF-LoS and IF-Generalized cases consider subcarrier and modulation order as the resources while the II-LoS and II-Generalized cases consider transmit power, subcarrier, and modulation order as the resources. Our objective function is minimizing the overall transmit power of the IoT users while satisfying some quality of service constraints in the uplink. To solve the resulting nonconvex optimization problem, we convert the main problem with high complexity into the subproblems with low complexities. We compare the performance of our joint proposed scenario with other joint and disjoint cases for the IF-LoS, IF-Generalized, II-LoS, and II-Generalized cases. Moreover, we evaluate the performance of the proposed schemes for different numbers of ABSs, environment types, target areas, and numbers of IoT users.Trans Emerging Tel Tech. 2019;30:e3632.wileyonlinelibrary.com/journal/ett

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Section: Related Workmentioning

confidence: 99%

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Azizi

Mokari

2019

Trans Emerging Tel Tech

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“…Aiming at this problem, a local convex approximation method is adopted, which ensures the convergence to the local optimal solution. Thus, a k,m [n] u k,m [n] , m ∈ {S, D} can be reformulated as [22]:…”

Section: Sub-problem 1: Optimizing Relay Selection and Uav Power Contmentioning

confidence: 99%

Joint Trajectory and Communication Design for Buffer-Aided Multi-UAV Relaying Networks

Cao

Yang

Xu³

2019

Applied Sciences

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With the rapid development and evolvement of unmanned aerial vehicle (UAV) technology, UAV aided wireless communication technology has been widely studied recently. In this paper, a buffer aided multi-UAV relaying network is investigated to assist blocked ground communication. According to the mobility and implementation flexibility of UAV relays, it is assumed that the communication link between air-to-ground is the Rician fading channel. On the basis of information causality, we derive the state change of the information in the buffer of UAV relays and maximize the end-to-end average throughput by join the relay selection, UAV transmit power, and UAV trajectory optimization. However, the considered problem is a mixed integer non-convex optimization problem, and therefore, it is difficult to solve directly with general optimization methods. In order to make the problem tractable, an efficient iterative algorithm based on the block coordinate descent and the successive convex optimization techniques is proposed. The convergence of the proposed algorithm will be verified analytically at the end of this paper. The simulation results show that by alternately optimizing the relay selection, UAV transmit power, and UAV trajectory, the proposed algorithm is able to achieve convergence quickly and significantly improve the average throughput, as compared to other benchmark schemes.

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“…The emergence of the concept of UAV-based communication provides a new direction for the WPCN strategy in remote areas [26]. Furthermore, methods for extending UAV communication systems to a wider range of applications, such as aquatic vehicle networks, have been discussed in [27] and [28].…”

Section: Introductionmentioning

confidence: 99%

UAV Hovering Strategy Based on a Wirelessly Powered Communication Network

Chen

Yin

2019

IEEE Access

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With the development of wireless power transfer technology, wirelessly powered communication networks (WPCNs), which can provide a sustainable energy supply for the user equipment, have received extensive attention from researchers. An unmanned aerial vehicle (UAV)-based WPCN (U-WPCN) can effectively solve the problems of energy shortage and weak signal strength for ground terminals in remote areas. To establish a highly efficient U-WPCN, the service area for each UAV platform should be determined such that each UAV platform will hover at the optimal position according to the locations of the ground terminals in its group. Through hovering position optimization, this paper proposes two networking strategies for improving networking efficiency and maximizing communication performance. A greedy algorithm is used to find the optimal hovering point for each area; thus, the hovering points of all UAVs in the U-WPCN are finally obtained. Simulation results show that the UAV utilization efficiency can be significantly increased through the economical mode, and the terminal transmission rates can be improved for a given number of drones in the performance mode. INDEX TERMS Unmanned aerial vehicle, optimal placement, wirelessly powered communication network, sustainable communication.

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Throughput Maximization in Multi-UAV Enabled Communication Systems With Difference Consideration

Cited by 38 publications

References 23 publications

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Joint resource allocation, 3D placement, and user association in ABS‐supported IoT networks considering adaptive modulation technique

Joint Trajectory and Communication Design for Buffer-Aided Multi-UAV Relaying Networks

UAV Hovering Strategy Based on a Wirelessly Powered Communication Network

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