Multi-Agent Reinforcement Learning Trajectory Design and Two-Stage Resource Management in CoMP UAV VLC Networks

Mili, Mohammad Robat; Javan, Mohammad Reza; Mokari, Nader; Jorswieck, Eduard A.

doi:10.1109/tcomm.2022.3211083

Cited by 20 publications

(7 citation statements)

References 46 publications

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“…Similarly, various UAVs in a VLC network are considered to further enhance optimization [53]. Multiagent reinforcement learning method is used to minimize the transmit power and maximize the sum rate of the UAVenabled VLC network [54]. Coverage probability has been increased to improve the single UAV-based VLC network [55].…”

Section: A Related Workmentioning

confidence: 99%

6G: Technology Evolution in Future Wireless Networks

Shafi,

Jha,

Jain

2024

IEEE Access

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The Sixth Generation (6G) Wireless Communication Network (WCN) is the successive provision to ameliorate the gain with ultra-low latency, and e xtremely high energy efficiency. The 6G WCN enables the specifications of artificial intelligence to optimize the services and capabilities. The vision of the 6G era is expected to address a seamless fusion of communication between the human, physical world, and digital world. The latest 6G WCN standard is a fundamental foundation and requires immense attention in the field of research. This paper presents the framework of 6G WCN with an illustration of its key technologies. The different technologies involved in 6G are well explained with the demonstration of the communication scenario such that the key performance indicators are improved with major differences. The primary contribution of this paper is the explanation of the 6G with the technologies that have a drastic impact on the characteristic aspects of a wireless communication network such as data rate, spectrum efficiency, energy efficiency, connection density, and reliability. All these technologies have the capability to revolutionize the subsequent WCN.

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Section: A Related Workmentioning

confidence: 99%

6G: Technology Evolution in Future Wireless Networks

Shafi,

Jha,

Jain

2024

IEEE Access

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“…Assuming the data rate threshold for the user to establish a successful communication link is C th , according to (13), the minimum optical power to meet the communication requirement at the j-th user position can be obtained by…”

Section: Energy Efficiencymentioning

confidence: 99%

“…In recent years, VLC has been considered for many emerging applications such as underwater communication [ 5 , 6 ], the Internet of things [ 7 ], wireless human–machine interactions [ 8 ], infrastructure-to-vehicle communication [ 9 ] and emergency communication [ 10 ]. Particularly, unmanned aerial vehicle-aided VLC (UAV-VLC) has been considered as promising candidate for joint emergency illumination and communication [ 11 , 12 , 13 ].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Unmanned Aerial Vehicle-Aided Visible Light Communication with an Angle Diversity Transmitter for Joint Emergency Illumination and Communication

Huang,

Wen,

Liu

et al. 2023

Sensors

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Unmanned aerial vehicle-aided visible light communication (UAV-VLC) can be used to realize joint emergency illumination and communication, but the endurance of UAV is a key limiting factor. In order to overcome this limitation, this paper proposes the use of an angle diversity transmitter (ADT) to enhance the energy efficiency of the UAV-VLC system. The ADT is designed with one bottom LED and several evenly distributed inclined side LEDs. By jointly optimizing the inclination angle of the side LEDs in the ADT and the height of the hovering UAV, the study aims to minimize the power consumption of the UAV-VLC system while satisfying the requirements of both illumination and communication. Simulation results show that the energy efficiency of the UAV-VLC system can be greatly enhanced by applying the optimized ADT. Moreover, the energy efficiency enhancement is much more significant when the LEDs in the ADT have a smaller divergence angle, or more side LEDs are configured in the ADT. More specifically, a 50.9% energy efficiency improvement can be achieved by using the optimized ADT in comparison to the conventional non-angle diversity transmitter (NADT).

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“…Also, to further reduce the transmit power of the UAVs, reconfigurable intelligent surfaces (RISs) were employed in [13], and the number of employed UAVs was considered as an additional optimization variable in [15]. The authors of [16] used multi-agent reinforcement learning to jointly maximize the network sum-rate and minimize the UAVs transmit power, whereas the authors of [17] considered a different objective, which sought to increase the coverage probability and decrease the data rate disparity among the users in single-UAV networks.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Deployment of VLC-Enabled UAV Using Particle Swarm Optimization

Ibraiwish,

Eltokhey,

Alouini

2024

IEEE Open J. Commun. Soc.

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Aerial base stations can be realized using unmanned aerial vehicles (UAVs)-mounted access points, which offer flexible and rapid network access in scenarios where terrestrial cellular networks are challenged by high traffic loads or insufficient coverage. Visible light communication (VLC) is an emerging technology that can be integrated with UAVs to offer simultaneous communication and illumination services while having low interference, high energy efficiency, and high data rates.To achieve an efficient operation of VLC-enabled UAVs, the power consumption of the UAVs due to their mobility should be considered, as it constitutes a significant portion of the total power consumption of the UAVs, especially when compared to that of the communication needs. This paper proposes a framework to optimize the trajectories of VLC-enabled UAVs, considering a multi-objective optimization problem that jointly maximizes the sum-rate and rate fairness of the users and minimizes the power consumption of the UAVs using particle swarm optimization (PSO) algorithm. The results show that the proposed optimization can effectively improve the performance of the system under various user mobility scenarios and UAV deployment altitudes.

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Multi-Agent Reinforcement Learning Trajectory Design and Two-Stage Resource Management in CoMP UAV VLC Networks

Cited by 20 publications

References 46 publications

6G: Technology Evolution in Future Wireless Networks

6G: Technology Evolution in Future Wireless Networks

Energy-Efficient Unmanned Aerial Vehicle-Aided Visible Light Communication with an Angle Diversity Transmitter for Joint Emergency Illumination and Communication

Energy Efficient Deployment of VLC-Enabled UAV Using Particle Swarm Optimization

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