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

Park, Ki-Won; Kim, Hyeon Min; Shin, Oh‐Soon

doi:10.3390/en15145143

Cited by 13 publications

(5 citation statements)

References 116 publications

(165 reference statements)

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“…In addition, IRS can be combined with different technologies such as mMIMO, XL-MIMO, and CF-mMIMO, further improving their advantages and, consequently, meeting stringent requirements of several vertical applications of the use cases described in Section 5 . For instance, integrating IRS with UAV communications may be vital to reaching the requirements of different agribusiness applications [ 76 ].…”

Section: Use Cases and Key Performance Indicators (Kpis) Of 6g Networkmentioning

confidence: 99%

Emerging MIMO Technologies for 6G Networks

Souto

Dester

Silva

et al. 2023

Sensors

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The demand for wireless connectivity has grown exponentially over the last years. By 2030 there should be around 17 billion of mobile-connected devices, with monthly data traffic in the order of thousands of exabytes. Although the Fifth Generation (5G) communications systems present far more features than Fourth Generation (4G) systems, they will not be able to serve this growing demand and the requirements of innovative use cases. Therefore, Sixth Generation (6G) Networks are expected to support such massive connectivity and guarantee an increase in performance and quality of service for all users. To deal with such requirements, several technical issues need to be addressed, including novel multiple-antenna technologies. Then, this survey gives a concise review of the main emerging Multiple-Input Multiple-Output (MIMO) technologies for 6G Networks such as massive MIMO (mMIMO), extremely large MIMO (XL-MIMO), Intelligent Reflecting Surfaces (IRS), and Cell-Free mMIMO (CF-mMIMO). Moreover, we present a discussion on how some of the expected key performance indicators (KPIs) of some novel 6G Network use cases can be met with the development of each MIMO technology.

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Section: Use Cases and Key Performance Indicators (Kpis) Of 6g Networkmentioning

confidence: 99%

Emerging MIMO Technologies for 6G Networks

Souto

Dester

Silva

et al. 2023

Sensors

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show abstract

“…Furthermore, several surveys have been conducted to explore the potential benefits of integrating RIS into other emerging technologies [41], [87], [88], [89], [90], [91], [92], [93], [94], [95]. More precisely, the authors in [41] explored the promising potential of using RIS in THz communications, highlighting its application scenarios in wireless mobile communication, UAV, mobile edge computing (MEC), and THz localization.…”

Section: Related Surveys and Contributionsmentioning

confidence: 99%

“…The study also shed light on emerging technologies that have the potential to amplify the benefits of RISs, with a specific focus on both ground and airborne scenarios. The effects of RIS positioning and the roles played by UAVs in enhancing different performance aspects, including SE, EE, reliability, latency, and security, were investigated in a comprehensive survey conducted in [88]. In [89], the authors surveyed the optimization of UAV position and trajectory, as well as precoding and phase shift at the BS and RIS, respectively.…”

Section: Related Surveys and Contributionsmentioning

confidence: 99%

Joint Beamforming Optimization Design and Performance Evaluation of RIS-Aided Wireless Networks: A Comprehensive State-of-the-Art Review

Ibrahim,

Mahmud,

Salleh

et al. 2023

IEEE Access

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Reconfigurable intelligent surface (RIS) has emerged as a promising technology for supporting sixth-generation (6G) wireless communication systems. RIS intelligently manages signal reflection properties to enhance signal strength and quality at the receiver. RIS devices are inherently passive, requiring minimal power to perform signal manipulation. Through signal path optimization, interference and transmit power reduction, RIS advances energy efficiency. This aligns with the eco-friendly goals of 6G. However, efficient optimization in RIS-aided networks plays a crucial role in fully unlocking the potential of RIS. Additionally, performance evaluation of RIS-aided systems contributes to understanding optimal configurations and design guidelines for real-world RIS deployments. Despite the contributions from performance evaluation and optimization, RIS confronts various design constraints that demand innovative approaches to optimization and evaluation of their performances. Implementing RIS poses challenges in optimizing configurations for dynamic environments, handling computational complexity in large-scale systems, and adapting to changing wireless conditions. This work provides a comprehensive and in-depth survey of the state-of-the-art in joint optimization designs and performance evaluation for RIS-aided wireless systems. Furthermore, we identify areas that require further investigation to facilitate future research in addressing the existing gaps in knowledge. Finally, the survey discusses promising future research directions that include exploring optimization techniques ensuring global optima with computational efficiency, investigating analytical approaches for accurate network performance assessment under diverse conditions, advancing multiobjective joint optimization, developing application-specific integrated performance metrics, examining the joint impact of relevant RIS design parameters, investigating adaptive quantization schemes, and exploring reliable channel state estimation techniques that are resilient against dynamic environments, noise, interference, and delays.

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“…This technology is primarily driven by the increasing demand for 6G applications and future Internet of Things (IoT) networks [6]. RISs work by reflecting radio signals in a controlled manner, allowing them to reach their intended destination with higher quality and a longer range [7].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Link Quality Estimation for RIS-Assisted UAV-Enabled Wireless Communications System

Tesfaw,

Juang,

Tai

et al. 2023

Sensors

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In recent years, unmanned aerial vehicles (UAVs) have become a valuable platform for many applications, including communication networks. UAV-enabled wireless communication faces challenges in complex urban and dynamic environments. UAVs can suffer from power limitations and path losses caused by non-line-of-sight connections, which may hamper communication performance. To address these issues, reconfigurable intelligent surfaces (RIS) have been proposed as helpful technologies to enhance UAV communication networks. However, due to the high mobility of UAVs, complex channel environments, and dynamic RIS configurations, it is challenging to estimate the link quality of ground users. In this paper, we propose a link quality estimation model using a gated recurrent unit (GRU) to assess the link quality of ground users for a multi-user RIS-assisted UAV-enabled wireless communication system. Our proposed framework uses a time series of user channel data and RIS phase shift information to estimate the quality of the link for each ground user. The simulation results showed that the proposed GRU model can effectively and accurately estimate the link quality of ground users in the RIS-assisted UAV-enabled wireless communication network.

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

Cited by 13 publications

References 116 publications

Emerging MIMO Technologies for 6G Networks

Emerging MIMO Technologies for 6G Networks

Joint Beamforming Optimization Design and Performance Evaluation of RIS-Aided Wireless Networks: A Comprehensive State-of-the-Art Review

Deep Learning-Based Link Quality Estimation for RIS-Assisted UAV-Enabled Wireless Communications System

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