Joint Trajectory-Task-Cache Optimization With Phase-Shift Design of RIS-Assisted UAV for MEC

Mei, Haibo; Yang, Kun; Shen, Jun; Liu, Qiang

doi:10.1109/lwc.2021.3074990

Cited by 51 publications

(23 citation statements)

References 11 publications

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“…Also, the increase in the number of the elements at RIS has not only enhanced the performance of the proposed system with the developed algorithm but also proved to be one of the great energy-saving schemas. In [59], the UAV acts as a MEC server to provide computational services to the ground users (GTs). This UAV was considered to be integrated with RIS to achieve improved performance on mobile computing.…”

Section: Table 2 Contributions Of Recent Survey Articles On Uav and Rismentioning

confidence: 99%

UAV-Assisted RIS for Future Wireless Communications: A Survey on Optimization and Performance Analysis

Pogaku

Lee

et al. 2022

IEEE Access

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Reconfigurable intelligent surfaces (RIS) have the immense ability to enhance the data transmission from the sender to the receiver. RIS is made of low-cost meta-surfaces that can reflect or refract the signals in the desired manner. The concept of RIS is inspired by a smart radio environment or programmable radio environment. Though the device was introduced a couple of years back, it has gained immense attention from researchers because of its applications in 5G and 6G wireless communications. The introduction of this device in wireless communications aids in reducing the hardware requirements, energy consumption, and signal processing complexity. The integration of this device with various emerging technologies such as multiple-input multiple-output (MIMO) systems, non-orthogonal multiple access (NOMA) technique, physical layer security, etc., has increased its potentiality in terms of performance enhancement. One such integration could be studied, i.e. RIS-assisted unmanned aerial vehicles (UAVs). The UAVs exhibit aiding capability in various services to our society such as real-time data collection, traffic monitoring, military operations & surveillance, medical assistance, and goods delivery. Despite the positive appeal, the UAV has its limitations such as fuel efficacy, environment disturbances, limited network capability, etc. Considering these scenarios, the RIS can provide assistance to UAVs to enhance their performance when integrated. There is a limited number of articles and researches that consider UAV-assisted RIS systems. This article provides a detailed survey on RIS-assisted UAV systems considering multiple contexts such as optimization, communication techniques, deep reinforcement learning, secrecy performance, efficiency enhancement, and the internet of things. Finally, we draw attention to the open challenges and possible future directions of UAV-assisted RIS systems in phase shifting, channel modeling, energy efficacy, and federated learning.

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Section: Table 2 Contributions Of Recent Survey Articles On Uav and Rismentioning

confidence: 99%

UAV-Assisted RIS for Future Wireless Communications: A Survey on Optimization and Performance Analysis

Pogaku

Lee

et al. 2022

IEEE Access

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“…Nowadays, there has been few work studying the RISassisted aerial MEC yet. In [135], one rotary-wing UAV is deployed to work as a MEC server, and a RIS is deployed on the the building surface to reflect the signals from users to the UAV during the task offloading. In order to minimize the energy consumption of the UAV while satisfying the QoS requirement of tasks, the UAV trajectory, task offloading and cache, as well as the phase-shift design of the RIS are jointly optimized by SCA.…”

Section: Rismentioning

confidence: 99%

A comprehensive survey on aerial mobile edge computing: Challenges, state-of-the-art, and future directions

Song

Qin

Hao

et al. 2022

Computer Communications

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“…Similarly, Refs. [70][71][72] aimed to maximize the energy efficiency of the IRS-assisted UAV communications systems. The system proposed in [71] provides communication and computing services to the ground terminals by operating UAVs as mobile edge computing (MEC) servers in the air.…”

Section: Improvement Of Energy Efficiencymentioning

confidence: 99%

“…[70][71][72] aimed to maximize the energy efficiency of the IRS-assisted UAV communications systems. The system proposed in [71] provides communication and computing services to the ground terminals by operating UAVs as mobile edge computing (MEC) servers in the air. However, UAVs should operate in an adverse environment where UAV-to-ground links are frequently blocked by ground obstacles, which may result in the long latency of tasks.…”

Section: Improvement Of Energy Efficiencymentioning

confidence: 99%

“…To address this issue, it is essential to configure the IRS so that the propagation channels between the UAV and ground terminals are improved. As a result, Reference [71] showed that IRS-assisted UAVs have great potential for improving the performance of MEC, as well as pure wireless communications. To improve the secrecy energy efficiency in an IRS-assisted UAV system with eavesdroppers, the authors of [72] argued for the need for the optimization of the IRS phase shift, UAV trajectory, user association, and transmit power.…”

Section: Improvement Of Energy Efficiencymentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Intelligent-Reflecting-Surface-Assisted UAV Communications

2022

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Both the unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) are attracting growing attention as enabling technologies for future wireless networks. In particular, IRS-assisted UAV communication, which incorporates IRSs into UAV communications, is emerging to overcome the limitations and problems of UAV communications and improve the system performance. This article aims to provide a comprehensive survey on IRS-assisted UAV communications. We first present six representative scenarios that integrate IRSs and UAVs according to the installation point of IRSs and the role of UAVs. Then, we introduce and discuss the technical features of the state-of-the-art relevant works on IRS-assisted UAV communications systems from the perspective of the main performance criteria, i.e., spectral efficiency, energy efficiency, security, etc. We also introduce machine learning algorithms adopted in the previous works. Finally, we highlight technical issues and research challenges that need to be addressed to realize IRS-assisted UAV communications systems.

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Joint Trajectory-Task-Cache Optimization With Phase-Shift Design of RIS-Assisted UAV for MEC

Cited by 51 publications

References 11 publications

UAV-Assisted RIS for Future Wireless Communications: A Survey on Optimization and Performance Analysis

UAV-Assisted RIS for Future Wireless Communications: A Survey on Optimization and Performance Analysis

A comprehensive survey on aerial mobile edge computing: Challenges, state-of-the-art, and future directions

A Survey on Intelligent-Reflecting-Surface-Assisted UAV Communications

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