Enabling NLoS LEO Satellite Communications with Reconfigurable Intelligent Surfaces

Xiao, Tian; Gonzalez-Prelcic, Nuria; Shioiri, Takayuki

doi:10.48550/arxiv.2205.15528

Cited by 1 publication

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“…Afterwards, the authors jointly optimized the active and passive beamforming on the LEO satellite and the ground nodes to maximize the channel capacity. On the other hand, the authors in [127] aim to improve the coverage of an IRS-assisted LEO SatCom network by changing the tilt of the IRS and by increasing the number of IRSs. Direct-tosatellite (DtS) channel estimation for different RIS configurations was studied in [128].…”

Section: Deployment Optimization Of Irss In Satellite Systemsmentioning

confidence: 99%

IRS-Empowered 6G Networks: Deployment Strategies, Performance Optimization, and Future Research Directions

et al. 2022

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The performance of the envisioned 6G network is fundamentally constrained by the uncontrollable and random wireless communication channel. Intelligent reflecting surfaces (IRSs) have emerged as one of the potential solutions to overcome this challenge by smartly controlling the incident signal to enhance the energy efficiency and spectrum efficiency of the 6G network. In addition, the future 6G network will incorporate several enabling technologies, including artificial intelligence and machine learning (AI/ML), integrated terrestrial and non-terrestrial (TNT) networks, multi-access edge computing (MEC), non-orthogonal multiple access (NOMA), and terahertz/millimeter wave (THz/mmWave) communication techniques. Therefore, this paper provides a contemporary and comprehensive overview of the envisioned IRS-empowered 6G networks from the perspective of its architecture, deployment strategy, integration of IRS technology with other 6G-enabling technologies, and physical layer security (PLS). Finally, we highlight design challenges and future research directions aimed at improving 6G network performance.INDEX TERMS Intelligent reflecting surfaces, Terahertz communication, Terrestrial and non-terrestrial (TNT) networks, Unmanned Aerial Vehicles, Reinforcement learning, Ultra-reliable and Low-latency communications.

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Section: Deployment Optimization Of Irss In Satellite Systemsmentioning

confidence: 99%