This document summarizes a seminar presentation on electromagnetic models of intelligent reflecting surfaces. It discusses the working principle, architecture, advantages, applications, limitations, and future research directions of intelligent reflecting surfaces. The presentation was submitted to fulfill requirements for a Bachelor of Technology degree. It was authored by Shreyansh Patni and guided by Ms. Jyotsna Joshi of the Electronics and Communication Engineering department at Poornima College of Engineering, Jaipur.

1. A
Seminar
ON
“Electromagnetic Model of Reflective Intelligent Surfaces”
Submitted in partial fulfilment for the award of Degree of Bachelor of Technology
Session: 2022-23
SUBMITTED TO:
Dr. Garima Mathur
(Head & Professor)
Guided By:
Ms. Jyotsna Joshi
SUBMITTED BY:
Shreyansh Patni
(PCE19EC064)
Department Of
Electronics and Communication Engineering
Poornima College of Engineering, Jaipur

2. CONTENT LIST
 Intelligent Reflecting Surfaces (IRS)
 Working Principle of IRS
 Architecture of IRS
 Applications of Speech Recognition
 Advantages and Applications
 Limitations/Disadvantages
 Challenging Issues
 Research Directions
 Future Scope
 Conclusion
 Thank You

3. Intelligent Reflecting Surface
IRS is a new and revolutionizing technology that is able to significantly improve the performance of wireless
communication networks, by smartly reconfiguring the wireless propagation environment with the use of massive
low-cost passive reflecting elements integrated on a planar surface

4. Intelligent Reflecting Surface
An IRS comprises an array of sub-wavelength IRS unit cells, each of which can independently incur some
change to the incident signal. The change in general may be about the phase, amplitude, frequency, or even
polarization.

5. Working Principle of IRS
The working principle of IRS is as per variation to Snell’s law. The input to IRS is plane waves whereas
the output is scattered waves whose phase shifts are controlled to meet desired reflection.

6. Working Principle of IRS
The EM (Electromagnetic) waves transmitted from BS are impinged on IRS which produces induction current in the
IRS. IRS reflects these signals toward the users. During reflection, IRS changes response by controlling phase and
amplitude. Phase shifts are controlled by PIN diodes used in IRS.

7. Architecture of IRS
The hardware implementation of IRS is based on the concept of “metasurface”, which is made of two-dimensional (2D)
meta-material that is digitally controllable. The metasurface is a planar array consisting of a large number of elements or
so-called meta-atoms with electrical thickness in the order of the subwavelength of the operating frequency of interest.
By properly designing the elements, including geometry shape (e.g., square or split-ring), size/dimension, orientation,
arrangement, etc., their individual signal response (reflection amplitude and phase shift) can be modified accordingly.

8. Architecture of IRS
As shown in the figure, a typical architecture of IRS may consist of three layers and a smart controller. In the outer layer,
a large number of metallic patches (elements) are printed on a dielectric substrate to directly interact with incident
signals. Behind this layer, a copper plate is used to avoid the signal energy leakage. Lastly, the inner layer is a control
circuit board that is responsible for adjusting the reflection amplitude/phase shift of each element, triggered by a smart
controller attached to the IRS.

9. Advantages of IRS
 They are nearly passive, and, ideally, they do not need any dedicated energy source.
 They are viewed as a contiguous surface, and, ideally, any point can shape the wave impinging upon it (soft
programming).
 They can be easily deployed, e.g., on the facades of buildings, ceilings of factories and indoor spaces, human
clothing, etc.
 They have full-band response, since, ideally, they can work at any operating frequency.
 They are not affected by receiver noise, since, ideally, they do not need analog-to-digital/digital-to-analog
converters (ADCs and DACs), and power amplifiers. As a result, they do not amplify nor introduce noise when
reflecting the signals and provide an inherently full duplex transmission.
 Overcoming Localized Coverage Holes
 It reduces the EM Pollution

10. Advantages of IRS
Two scenarios of IRS-assisted wireless communications.
(a) IRS-assisted beamforming.
(b) IRS-assisted broadcasting.

11. Advantages of IRS
A smart radio environment with multiple IRSs. User A is far away from the AP and suffers from low received
signal strength, while user B has amble received power but a low-rank ill-conditioned channel. The IRSs can be
optimized to help in both scenarios.

12. Applications of IRS

13. Limitations/Disadvantages of IRS
 Once the metasurface is fabricated with a specific physical structure, it will have fixed EM properties and
therefore can be used for a specific purpose, e.g., a perfect absorber operating at a certain frequency.
 However, it becomes very inflexible as a new metasurface has to be redesigned and fabricated to serve another
purpose or operate at a different frequency.
 n particular, based on the application requirements, the structural parameters of the scattering elements
constituting the metasurface have to be recalculated by a synthesis approach, which is in general computational
demanding.
 It does not outperform relay. To make performance similar to relay, requires metasurface with higher number of
elements (~200).
 RIS elements do not support digital processing capability as it is designed based on concept of analog
beamforming.

14. Challenging Issues
 Experimentally-validated channel models and path loss scaling
 Energy-efficient channel sensing, estimation and feedback overhead
 Spatial models for system-level analysis and optimization
 Integration of IRSs with emerging technologies
 Practical protocols for information exchange
 Agile and light-weight phase reconfiguration
 Data-driven optimization

15. Research Directions
 Experimentally-validated channel models and path loss model
 An IRS’s behavior depends on its physical materials and manufacturing processes. Models taking these issues into
account can more accurately guide the optimization of IRSs for aiding wireless communications.
 Scaling laws need to be established for a fundamental understanding of the performance limits in IRS-aided
communications.
 Artificial neural network, Deep learning-based design can be employed in IRS-aided communications to see the
performance.
 RF Sensing and Localization issues need to be examined.

16. PAPER-1
Jie Yuan , Ying-Chang Liang , Intelligent Reflecting Surface-Assisted Cognitive Radio System, pp.
153227 ,2021
• This paper presents that Cognitive radio (CR) is an effective solution to improve the spectral efficiency
(SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary
users (PUs)
• This paper first proposes to improve both SE and Energy efficiency (EE), in this paper, we introduce
multiple IRSs to a downlink multiple-input single-output (MISO) CR system.
• The design objective is to maximize the achievable rate of SU subject to a total transmit power
constraint on the SU transmitter.
• To achieve interference temperature constraints on the PU-RXs, They do jointly optimizing the
beamforming at SU-TX and the reflecting coefficients at each IRS

17. PAPER-2
S. Fatemeh Zamanian , Vertical Beamforming in Intelligent Reflecting Surface-Aided Cognitive
Radio Networks ,2021
• This paper presents to investigate joint application of intelligent reflecting surface (IRS) and vertical
beamforming in cognitive radio networks (CRN)
• This paper proposes phase shifts at the IRS with the objective of maximizing spectral efficiency of the
secondary network.
• An IRS aided network comprises a programmable meta-surface with massive reflecting elements that
their phases are optimized in a way to improve some metrics such as interference reduction, security
enhancement, and energy efficiency

18. PAPER-3
Tao , Junwei , Zhong , Performance Analysis of Intelligent Reflecting Surface Aided Communication
System, 2020.
• This letter presents a detailed performance analysis of the intelligent reflecting surface (IRS) aided
single-input singleoutput communication systems, taking into account of the direct link between the
transmitter and receiver.
• This paper tells that the works on IRS focus on the design of the phase shift matrix and the transmit
beamformer
• The intelligent reflecting surface (IRS), can manipulate the propagation channel into a favorable shape,
has been regarded as a promising technology for the next generation wireless communication systems.

19. PAPER-4
Limeng Dong , Haitao Xiao , Double Intelligent Reflecting Surface for Secure Transmission
With Inter-Surface Signal Reflection, 2021
• This paper tells that we use double intelligent reflecting surface (IRS) assisted design to enhance the
secrecy performance of wireless transmission.
• This paper propose a product Riemmanian manifold (PRM) based alternating optimization (AO)
algorithm to jointly optimize the beamformer at transmitter as well as phase shift coefficients at double
IRS
• By using the PRM method it optimize the phase shift coefficients at both IRSs simultaneously
• The PRM method algorithm greatly enhance the SR compared with the existing benchmark schemes.

20. PAPER-5
Matthiesen, Bho , Intelligent Reflecting Surface Operation under Predictable Receiver Mobility:
A Continuous Time Propagation Model., 2020
• This paper presents intelligent reflecting surface (IRS) under predictable receiver mobility is
investigated and develop a continuous time system model for multipath channels
• It is shown that the received power can be maximized without adding Doppler spread to the system.
• It also adds that almost equivalently strong, communication can improves the link reliability
• Also , this paper considers multipath propagation with predictive receiver mobility and evaluates the
implications of adding an IRS to a line-of-sight (LOS) communication scenario.

21. Conclusion of Research Papers
Paper 1 Paper 2 Paper 3 Paper 4
Work Done Cognitive radio (CR)
is an effective
solution to improve
the spectral
efficiency
Study of joint
application of
intelligent reflecting
surface (IRS)
performance
analysis of the
intelligent reflecting
surface (IRS)
Study of double intelligent
reflecting surface (IRS)
Technology /
Algorithm
Used
multiple IRSs to a
downlink multiple-
input single-output
(MISO)
phase shifts at the IRS phase shift matrix
and the transmit
beamformer
product Riemmanian
manifold (PRM)
Outcome achieve interference
temperature
constraints
• improve some
metrics such as
interference
reduction, security,
& energy efficiency
can manipulate the
propagation channel
into a favorable
shape
PRM method algorithm
greatly enhance the SR

22. Future Scope
• We can create smart radio environment with multiple IRSs.
• We can reduces the EM Pollution
• We can easily deployed, e.g., on the facades of buildings, ceilings of factories and indoor
spaces, human clothing, etc.
• We can Integrate emerging technologies with IRS
• Overcome Localized Coverage Holes

23. Conclusion
• This paper the Electromagnetic Model of Reflective Intelligent Surfaces presents and it is
important to consider the environment in which the Reflective Intelligent Surfaces has to work .
• Intelligent Reflecting Surface (IRS) is a revolutionary technology which is able to improve the
performance of wireless data transmission system. Specially, large numbers of small reflecting
unit are jointly adjusted to reconfigure the wireless signal transmitting environment.

24. THANK YOU