Open AccessPosted Content
Reconfigurable Intelligent Surfaces: Principles and Opportunities
Yuanwei Liu,Xiao Liu,Xidong Mu,Tianwei Hou,Jiaqi Xu,Zhijin Qin,Marco Di Renzo,Naofal Al-Dhahir +7 more
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TLDR
A comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies is provided in this article.Abstract:
Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), have received significant attention for their potential to enhance the capacity and coverage of wireless networks by smartly reconfiguring the wireless propagation environment. Therefore, RISs are considered a promising technology for the sixth-generation (6G) communication networks. In this context, we provide a comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies. We describe the basic principles of RISs both from physics and communications perspectives, based on which we present performance evaluation of multi-antenna assisted RIS systems. In addition, we systematically survey existing designs for RIS-enhanced wireless networks encompassing performance analysis, information theory, and performance optimization perspectives. Furthermore, we survey existing research contributions that apply machine learning for tackling challenges in dynamic scenarios, such as random fluctuations of wireless channels and user mobility in RIS-enhanced wireless networks. Last but not least, we identify major issues and research opportunities associated with the integration of RISs and other emerging technologies for application to next-generation networks.read more
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Journal ArticleDOI
STAR-RISs: Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surfaces
TL;DR: Compared with the conventional reflecting-only RISs, the coverage of STAR-RISs is extended to 360 degrees via simultaneous transmission and reflection and channel models are proposed for the near-field and the far-field scenarios, base on which the diversity gain is analyzed and compared with that of the conventional RISs.
Journal ArticleDOI
RIS-Assisted Coverage Enhancement in Millimeter-Wave Cellular Networks
TL;DR: In this paper, the authors study the coverage of an RIS-assisted large-scale mmWave cellular network using stochastic geometry, and derive the peak reflection power expression of RIS and the downlink signal-to-interference ratio (SIR) coverage expression in closed forms.
Journal ArticleDOI
Intelligent Reflecting Surface Enhanced Multi-UAV NOMA Networks
TL;DR: To tackle the formulated mixed-integer non-convex optimization problem with coupled variables, a block coordinate descent (BCD)-based iterative algorithm is developed and is demonstrated to be able to obtain a stationary point of the original problem with polynomial time complexity.
Posted Content
Seven Defining Features of Terahertz (THz) Wireless Systems: A Fellowship of Communication and Sensing.
Christina Chaccour,Mehdi Naderi Soorki,Walid Saad,Mehdi Bennis,Petar Popovski,Merouane Debbah +5 more
TL;DR: In this article, the authors characterize seven unique defining features of the terahertz (THz) wireless systems: 1) Quasi-opticality of the band, 2) THz-tailored wireless architectures, 3) Synergy with lower frequency bands, 4) Joint sensing and communication systems, 5) PHY-layer procedures, 6) Spectrum access techniques, and 7) Real-time network optimization.
Journal ArticleDOI
Beamforming Design for Multiuser Transmission Through Reconfigurable Intelligent Surface
TL;DR: In this paper, the sum transmit power of the network is minimized by controlling the phase beamforming of the RIS and the BS transmit power under signal-to-interference-plus-noise ratio constraints.
References
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