Intelligent Reflecting Surfaces: Physics, Propagation, and Pathloss Modeling

By Özgecan Özdogan, Emil Björnson, Erik G. Larsson. IEEE Wireless Communications Letters, 2019

735 citations recorded by the source corpus.

Intelligent reflecting surfaces can improve the communication between a source and a destination. The surface contains metamaterial that is configured to “reflect” the incident wave from the source towards the destination. Two incompatible pathloss models have been used in prior work. In this letter, we derive the far-field pathloss using physical optics techniques and explain why the surface consists of many elements that individually act as diffuse scatterers but can jointly beamform the signal in a desired direction with a certain beamwidth. We disprove one of the previously conjectured pathloss models.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Electronic, Optical and Magnetic Materials

View Paper: https://www.semanticscholar.org/paper/e2723a8ac4d5b09f6d5c6fc15c22274a9fa236c3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

In Electrical and Electronic Engineering

In Electronic, Optical and Magnetic Materials

Citations in the corpus

6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities (2020, methodology): “In a similar line, a discussion on the implication of IRSs is presented in [147], where the implications of large-scale fading variability are characterized via first principles.”
Prospective Multiple Antenna Technologies for Beyond 5G (2019, background): “Normally, a ﬂat ﬁnite-sized surface reﬂects the incoming wave in the main direction determined by Snell’s law [158] but with a beamwidth that is inversely proportional to the size of the surface relative to the wavelength [159].”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, background): “In [79], the authors study the path-loss of RISs in the far-field regime by leveraging antenna theory.”
Reconfigurable Intelligent Surfaces: Three Myths and Two Critical Questions (2020, methodology): “distances to the RIS [6], rather than inversely proportional to the squared sum of the distances as with a mirror.”
A Joint Precoding Framework for Wideband Reconfigurable Intelligent Surface-Aided Cell-Free Network (2020, methodology): “The existing research works about RIS include antenna design [20], physical model [21], channel estimation [22], joint precoding/beamforming [23], and etc.”
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, result): “A similar result has been revealed in [87].”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, background): “In [79], the authors study the path-loss of RISs in the farfield regime by leveraging antenna theory.”
Rayleigh Fading Modeling and Channel Hardening for Reconfigurable Intelligent Surfaces (2020, background): “Since practical elements are sub-wavelength-sized A ∝ λ2 [3], [4], the number of elements N needed to achieve a given total area NA is inversely proportional to λ2.”
Physics-Based Modeling and Scalable Optimization of Large Intelligent Reflecting Surfaces (2020, background): “Moreover, as the physics-based models in [16]–[18] suggest, the path-loss of the end-to-end IRS-assisted links is signiﬁcant for far-ﬁeld scenarios and indeed a very large IRS is needed to overcome it in practice.”
Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-User Communications: Achievable Rates With Limited Discrete Phase Shifts (2019, methodology): “The channel h (k,n) l1,l2 between each BS antenna 1 ≤ n ≤ Nt and user k via RIS element (l1, l2) is given by [20]”
Intelligent Reflecting Surface Versus Decode-and-Forward: How Large Surfaces are Needed to Beat Relaying? (2019, methodology): “In general, it is the total size of the IRS (and not the number of elements or their individual size) that determines the pathloss, as explained in detail in [13].”
Active Reconfigurable Intelligent Surface-Aided Wireless Communications (2021, background): “Notice that the path loss of the RIS-aided link is proportional to df f d ηb b βfβb, where df , ηf , and βf are the distance between the transmitter and the RIS, the pathloss exponent and the pathloss measured at the reference distance for the transmitter-RIS sub-channel, respectively, while db, ηb,”
Modeling and Architecture Design of Reconfigurable Intelligent Surfaces Using Scattering Parameter Network Analysis (2020, methodology): “However, the limitation of [31], [32], [33], [34] is that they only focus on very speciﬁc physical and EM properties of RIS.”
Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications (2021, positive): “The elements are typically subwavelength in size (e.g., a square patch of size / / ) 5 5 # m m to behave as scatterers without strong intrinsic directivity [18].”
Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces (2020, background): “However, one can certainly use the mirror analogy to identify the approximately optimal phase-shifts when operating in the far-field [43].”
Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities (2020, background): “This has been analyzed theoretically in [26], [27], [29] and observed in empirical measurements conducted in [27].”
White Paper on Broadband Connectivity in 6G (2020, background): “The consequence is that an incoming waveform can be reﬂected in the shape of a beam whose direction is determined by the phase-shift pattern over the elements and thus can be controlled [29].”