Downlink Performance Analysis in MIMO UAV-Cellular Communication With LOS/NLOS Propagation Under 3D Beamforming

Alkama, Dina; Ouamri, Mohamed Amine; Alzaidi, Mohammed S.; Shaw, Rabindra Nath; Azni, Mohamed; Ghoneim, Sherif S. M.

doi:10.1109/access.2022.3142529

Cited by 28 publications

(15 citation statements)

References 28 publications

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“…Then, they proposed a heuristic algorithm weighted targets sweep coverage to find the optimal trajectory of UAV. Alkama et al [7] proposed an analytical framework to analyze the coverage probability and capacity by using stochastic geometry. Moreover, they further derived the downlink coverage expression based on signal-to-interference-plusnoise-ratio.…”

Section: Related Workmentioning

confidence: 99%

Joint Power and 3D Trajectory Optimization for UAV-Enabled Wireless Powered Communication Networks With Obstacles

Pan

Liu

Sun

et al. 2023

IEEE Trans. Commun.

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Unmanned aerial vehicle (UAV)-enabled wireless powered communication networks (WPCNs) are promising technologies in 5G/6G wireless communications, while there are several challenges about UAV power allocation and scheduling to enhance the energy utilization efficiency, considering the existence of obstacles. In this work, we consider a UAV-enabled WPCN scenario that a UAV needs to cover the ground wireless devices (WDs). During the coverage process, the UAV needs to collect data from the WDs and charge them simultaneously. To this end, we formulate a joint-UAV power and three-dimensional (3D) trajectory optimization problem (JUPTTOP) to simultaneously increase the total number of the covered WDs, increase the time efficiency, and reduce the total flying distance of UAV so as to improve the energy utilization efficiency in the network. Due to the difficulties and complexities, we decompose it into two sub optimization problems, which are the UAV power allocation optimization problem (UPAOP) and UAV 3D trajectory optimization problem (UTTOP), respectively. Then, we propose an improved non-dominated sorting genetic algorithm-II with K-means initialization operator and Variable dimension mechanism (NSGA-II-KV) for solving the UPAOP. For UTTOP, we first introduce a pretreatment method, and then use an improved particle swarm optimization with Normal distribution initialization, Genetic mechanism, Differential mechanism and Pursuit operator (PSO-NGDP) to deal with this sub optimization problem. Simulation results verify the effectiveness of the proposed strategies under different scales and settings of the networks.

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Section: Related Workmentioning

confidence: 99%

Joint Power and 3D Trajectory Optimization for UAV-Enabled Wireless Powered Communication Networks With Obstacles

Pan

Liu

Sun

et al. 2023

IEEE Trans. Commun.

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“…The fundamental principle of beamforming is to control the direction of a wavefront toward the UE. According to [42], UAV and SBS serve UE through beamforming technology. In this manner, the SINR of UE from UAV at time slot t can be written as…”

Section: Sinr and Path Loss Modelmentioning

confidence: 99%

Double Deep Q-Network Method for Energy Efficiency and Throughput in a UAV-Assisted Terrestrial Network

Ouamri¹,

Alkanhel²,

Singh³

et al. 2023

Computer Systems Science and Engineering

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Increasing the coverage and capacity of cellular networks by deploying additional base stations is one of the fundamental objectives of fifth-generation (5G) networks. However, it leads to performance degradation and huge spectral consumption due to the massive densification of connected devices and simultaneous access demand. To meet these access conditions and improve Quality of Service, resource allocation (RA) should be carefully optimized. Traditionally, RA problems are nonconvex optimizations, which are performed using heuristic methods, such as genetic algorithm, particle swarm optimization, and simulated annealing. However, the application of these approaches remains computationally expensive and unattractive for dense cellular networks. Therefore, artificial intelligence algorithms are used to improve traditional RA mechanisms. Deep learning is a promising tool for addressing resource management problems in wireless communication. In this study, we investigate a double deep Q-network-based RA framework that maximizes energy efficiency (EE) and total network throughput in unmanned aerial vehicle (UAV)-assisted terrestrial networks. Specifically, the system is studied under the constraints of interference. However, the optimization problem is formulated as a mixed integer nonlinear program. Within this framework, we evaluated the effect of height and the number of UAVs on EE and throughput. Then, in accordance with the experimental results, we compare the proposed algorithm with several artificial intelligence methods. Simulation results indicate that the proposed approach can increase EE with a considerable throughput.

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“…In [17], the optimal 3D deployment problem of UAVs was solved to maximize the downlink coverage performance with a minimum transmit power. In [18], a 3D beamforming was designed to increase the coverage of the wireless communication system, in which UAVs were distributed at different heights and equipped with Multiple-Input-Multiple-Output (MIMO). In [19], a scenario of UAVs with imperfect beam alignment was considered, and an analytical framework was proposed to analyze the coverage probability of UAV-assisted networks under cluster users.…”

Section: Related Workmentioning

confidence: 99%

A Robust Scheme for RIS-Assisted UAV Secure Communication in IoT

Qian

Zhang

Yan³

et al. 2023

Electronics

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Reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicles (UAV) have been extensively studied on the Internet of Things (IoT) systems to improve communication performance. In this paper, we aimed to counter simultaneous jamming and eavesdropping attacks by jointly designing an active beamforming vector at the base station (BS) and reflect phase shifts at the RIS. Specifically, considering imperfect angular channel state information (CSI), the sum secrecy rate maximization problem in the worst case could be formulated, which is NP-hard and non-convex. To address this problem, we improved the robust enhanced signal-to-leakage-and-noise ratio (E-SLNR) beamforming to reduce the computational complexity and mitigate the impact of interference, eavesdropping and jamming. Furthermore, a genetic algorithm with a tabu search (GA-TS) method was proposed to efficiently obtain an approximate optimal solution. The simulation results demonstrated that the proposed GA-TS method converged faster with better results than conventional GA, while the proposed robust scheme could achieve higher sum secrecy rates than the zero-forcing (ZF) and SLNR schemes.

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Downlink Performance Analysis in MIMO UAV-Cellular Communication With LOS/NLOS Propagation Under 3D Beamforming

Cited by 28 publications

References 28 publications

Joint Power and 3D Trajectory Optimization for UAV-Enabled Wireless Powered Communication Networks With Obstacles

Joint Power and 3D Trajectory Optimization for UAV-Enabled Wireless Powered Communication Networks With Obstacles

Double Deep Q-Network Method for Energy Efficiency and Throughput in a UAV-Assisted Terrestrial Network

A Robust Scheme for RIS-Assisted UAV Secure Communication in IoT

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