ETSI GR RIS 003 V1.2.1 (2025-02)

Reconfigurable Intelligent Surfaces (RIS); Communication Models, Channel Models, Channel Estimation and Evaluation Methodology

RGR/RIS-003

General Information

• Status: Not Published
• Technical Committee: RIS - Reconfigurable Intelligent Surfaces
• Current Stage: 12 - Citation in the OJ (auto-insert)
• Due Date: 20-Feb-2025
• Completion Date: 07-Feb-2025

Standards Content (Sample)

GROUP REPORT
Reconfigurable Intelligent Surfaces (RIS);
Communication Models, Channel Models,
Channel Estimation and Evaluation Methodology
Disclaimer
The present document has been produced and approved by the Reconfigurable Intelligent Surfaces (RIS) ETSI Industry
Specification Group (ISG) and represents the views of those members who participated in this ISG.
It does not necessarily represent the views of the entire ETSI membership.

2 ETSI GR RIS 003 V1.2.1 (2025-02)

Reference
RGR/RIS-003
Keywords
methodology, RIS
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3 ETSI GR RIS 003 V1.2.1 (2025-02)
Contents
Intellectual Property Rights . 5
Foreword . 5
Modal verbs terminology . 5
1 Scope . 6
2 References . 6
2.1 Normative references . 6
2.2 Informative references . 6
3 Definition of terms, symbols and abbreviations . 7
3.1 Terms . 7
3.2 Symbols . 7
3.3 Abbreviations . 8
4 Introduction . 9
4.1 General Description . 9
4.2 Definition of RIS . 9
4.3 Types of RIS . 9
4.4 Deployment scenarios . 10
5 Models for RIS . 11
5.1 Models for communications . 11
5.1.1 General description . 11
5.1.2 Locally periodic discrete model . 11
5.1.3 Mutually-coupled antenna model . 11
5.1.4 Inhomogeneous sheets of surface impedance . 12
5.2 Models for radio localization and sensing . 13
5.2.1 Scenarios . 13
5.2.1.1 Localization scenarios . 13
5.2.1.2 SISO localization . 13
5.2.1.3 MISO localization . 13
5.2.1.4 SIMO localization . 14
5.2.1.5 MIMO localization . 14
5.2.1.6 RIS-aided and RIS-standalone . 14
5.2.2 Near-field . 15
5.2.2.1 Near-field regimes . 15
5.2.2.2 Near-field multiple paths . 16
5.2.2.3 Near-field single-path. 17
5.2.3 Far-field . 19
5.3 Continuous and discrete models . 20
6 Channel models . 20
6.1 Objectives of channel modeling and general principles . 20
6.2 Existing channel models . 21
6.3 Path-loss models . 21
6.3.1 Description of different cases . 21
6.3.1.1 General description . 21
6.3.1.2 General case . 22
6.3.1.3 Near-field case . 22
6.3.1.4 Far-field case . 23
6.4 Empirical channel model . 23
6.5 Multipath models . 24
6.5.1 Unstructured models for rich scattering (sub-6 GHz) environments . 24
6.5.2 Structured models for rich scattering (sub-6 GHz) environments . 25
6.5.3 Structured (geometric) models for high frequency bands . 25
6.6 Multi-mode reradiation models . 25
6.7 Interference and unwanted reradiation models . 26
6.7.1 Definition of interference and unwanted reradiation . 26
6.7.1.1 General description . 26
6.7.1.2 RIS contribution to the interference propagation channel (In-Band Reradiation) . 26
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4 ETSI GR RIS 003 V1.2.1 (2025-02)
6.7.1.3 Unwanted reradiations (Unexpected/Irregular/Discontinuously Time-Varying Out-Of-Band
Reradiation) . 28
6.7.2 Characterization of interference and unwanted reradiation . 28
6.7.2.0 General description . 28
6.7.2.1 Generated by the RIS itself . 29
6.7.2.2 Generated by other RIS . 29
6.7.2.3 Single and Multi/Inter-Operator Modeling . 29
6.7.2.4 Eavesdropping . 30
6.7.3 Destructive beamforming . 30
6.7.4 Modeling CSI mismatch due to interference and unwanted reradiation . 32
6.7.4.1 CSI mismatch due to interference (In-Band Reradiation) . 32
6.7.4.2 CSI mismatch due to Unwanted reradiations . 32
6.7.5 Spurious reradiation . 34
6.8 Polarized RIS element modeling . 35
7 Channel Estimation . 36
7.1 Reference scenarios . 36
7.1.1 General description . 36
7.1.2 RIS cannot perform on-board channel estimation . 36
7.1.3 RIS can perform on-board channel estimation . 36
7.1.4 Availability of direct link between gNB and UE . 37
7.2 Cascaded and separated channel estimation . 37
7.2.1 General description . 37
7.2.2 Methods to estimate the end-to-end cascaded channel . 37
7.2.2.0 General . 37
7.2.2.1 Element-wise RIS channel estimatio n . 38
7.2.2.1.0 General . 38
7.2.2.1.1 System model including one RIS element . 38
7.2.2.1.2 System model including all RIS elements . 39
7.2.2.1.3 Sub-surface based RIS channel estimation . 40
7.2.2.2 Configuration-wise RIS channel estimation . 40
7.2.2.3 Single RF chain enabled RIS channel estimation . 40
7.2.3 Methods to estimate the separated/individual RIS channels . 41
7.3 Estimation methods for unstructured channel models . 41
7.4 Methods for structured channel models. 42
7.5 Methods based on availability of channel state information . 42
7.6 Hybrid RIS-assisted channel estimation . 43
8 Key performance indicators and evaluation methodology . 43
8.1 Key performance indicators . 43
8.1.1 General . 43
8.1.2 Throughput . 44
8.1.3 Spectral Efficiency . 44
8.1.4 Coverage (User Percentiles) . 44
8.1.5 Energy Efficiency . 44
8.1.6 Security . 44
8.1.7 Latency . 44
8.1.8 Reliability . 45
8.1.9 Overhead . 45
8.2 Design Parameters . 45
8.2.1 RIS size . 45
8.2.2 Electromagnetic Field Exposure . 45
8.2.3 Carrier Frequency . 45
8.2.4 Bandwidth . 46
8.3 Reference scenarios for evaluation . 46
8.4 Evaluation methodology . 49
8.4.1 Link-level evaluation . 49
8.4.2 System-level evaluation . 49
8.4.3 Link budget evaluation . 51
9 Conclusions . 58
History . 59

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5 ETSI GR RIS 003 V1.2.1 (2025-02)
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Foreword
This Group Report (GR) has been produced by ETSI Industry Specification Group (ISG) Reconfigurable Intelligent
Surfaces (RIS).
Modal verbs terminology
In the present document "should", "should not", "may", "need not", "will", "will not", "can" and "cannot" are to be
interpreted as described in clause 3.2 of the ETSI Drafting Rules (Verbal forms for the expression of provisions).
"must" and "must not" are NOT allowed in ETSI deliverables except when used in direct citation.

ETSI
6 ETSI GR RIS 003 V1.2.1 (2025-02)
1 Scope
The present document is intended to study:
a) communication models that strike a suitable trade-off between electromagnetic accuracy and simplicity for
performance evaluation and optimization at different frequency bands;
b) channel models (deterministic and statistical) that include path-loss and multipath propagation effects, as well
as the impact of interference for application to different frequency bands;
c) channel estimation, including reference scenarios, estimation methods, and system designs; and
d) key performance indicators and the methodology for evaluating the performance of RIS for application to
wireless communications, including the coexistence between different network operators, and for fairly
comparing different transmission techniques, communication protocols, and network deployments.
2 References
2.1 Normative references
Normative references are not applicable in the present document.
2.2 Informative references
References are either specific (identified by date of publication and/or edition number or version number) or
non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the
referenced document (including any amendments) applies.
NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee
their long term validity.
The following referenced documents are not necessary for the application of the present document but they assist the
user with regard to a particular subject area.
[i.1] ETSI GR RIS 001 (V1.1.1): "Reconfigurable Intelligent Surfaces (RIS); Use Cases, Deployment
Scenarios and Requirements".
[i.2] ETSI TR 138 901 (V16.1.0): "5G; Study on channel model for frequencies from 0.5 to 100 GHz
(3GPP TR 38.901 version 16.1.0 Release 16)".
[i.3] Recommendation ITU-R SM.329: "Unwanted emissions in the spurious domain".
[i.4] M. Di Renzo, F. H. Danufane and S. Tretyakov: "Communication Models for Reconfigurable
Intelligent Surfaces: From Surface Electromagnetics to Wireless Networks Optimization", in
™
Proceedings of the IEEE , 2022, doi: 10.1109/JPROC.2022.3195536.
[i.5] G. Gradoni and M. Di Renzo: "End-to-End Mutual Coupling Aware Communication Model for
Reconfigurable Intelligent Surfaces: An Electromagnetic-Compliant Approach Based on Mutual
™
Impedances", in IEEE Wireless Communications Letters, vol. 10, no. 5, pp. 938-942, May 2021,
doi: 10.1109/LWC.2021.3050826.
[i.6] W. Tang et al.: "Wireless communications with reconfigurable intelligent surface: Path loss
™
modeling and experimental measurement", IEEE Trans. Wireless Commun., vol. 20, no. 1,
pp. 421-439, January 2021.
[i.7] W. Tang et al.: "Path loss modeling and measurements for reconfigurable intelligent surfaces in
™
the millimeter-wave frequency band", IEEE Transactions on Communications 70, no. 9 (2022),
pp. 6259-6276.
ETSI
7 ETSI GR RIS 003 V1.2.1 (2025-02)
™
[i.8] S. W. Ellingson: "Path loss in reconfigurable intelligent surface-enabled channels", 2021 IEEE
nd
32 Annual International Symposium on Personal, Indoor and Mobile Radio Communications
(PIMRC).
[i.9] F. H. Danufane et al.: "On the Path-Loss of Reconfigurable Intelligent Surfaces: An Approach
™
Based on Green's Theorem Applied to Vector Fields," in IEEE Transactions on Communications,
vol. 69, no. 8, pp. 5573-5592, August 2021.
[i.10] Emil Björnson and Luca Sanguinetti: "Rayleigh fading modeling and channel hardening for
™
reconfigurable intelligent surfaces", IEEE Wireless Communications Letters 10, no. 4 (2020):
pp. 830-834.
[i.11] N. S. Perović et al.: "Achievable Rate Optimization for MIMO Systems With Reconfigurable
™
Intelligent Surfaces", in IEEE Transactions on Wireless Communications, vol. 20, no. 6,
pp. 3865-3882, June 2021.
[i.12] A. Abrardo et al.: "MIMO Interference Channels Assisted by Reconfigurable Intelligent Surfaces:
Mutual Coupling Aware Sum-Rate Optimization Based on a Mutual Impedance Channel Model",
in IEEE™ Wireless Communications Letters, vol. 10, no. 12, pp. 2624-2628, December 2021.
[i.13] Ibrahim Yildirim and Ertugrul Basar: "Channel Modeling in RIS‐Empowered Wireless
Communications", in Intelligent Reconfigurable Surfaces (IRS) for Prospective 6G Wireless
™
, 2023, pp.123-148, doi: 10.1002/9781119875284.ch7.
Networks, IEEE
™
[i.14] A. Saleh and R. Valenzuela: "A statistical model for indoor multipath propagation", in IEEE
Journal of Selected Areas in Communications, vol. 5, no. 2, pp. 128-137, February 1987.
[i.15] C. Pan et al.: "An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless
™
Systems", in IEEE Journal of Selected Topics in Signal Processing, vol. 16, no. 5, pp. 883-917,
August 2022.
[i.16] A. Díaz-Rubio and S. A. Tretyakov: "Macroscopic Modeling of Anomalously Reflecting
™
Metasurfaces: Angular Response and Far-Field Scattering", in IEEE Transactions on Antennas
and Propagation, vol. 69, no. 10, pp. 6560-6571, October 2021.
[i.17] V. Degli-Esposti et al.: "Reradiation and Scattering from a Reconfigurable Intelligent Surface: A
General Macroscopic Model", in IEEE™ Transactions on Antennas and Propagation, 2022.
[i.18] B. Sihlbom, et al.: "Reconfigurable Intelligent Surfaces: Performance Assessment Through a
™
Wireless Communications, 2022.
System-Level Simulator", in IEEE
[i.19] 3GPP TR 37.885: "Study on evaluation methodology of new Vehicle-to-Everything (V2X) use
cases for LTE and NR".
[i.20] ETSI TR 137 910: "5G; Study on self evaluation towards IMT-2020 submission (3GPP
TR 37.910)".
3 Definition of terms, symbols and abbreviations
3.1 Terms
For the purposes of the present document, the terms given in ETSI GR RIS 001 [i.1] apply.
3.2 Symbols
Void.
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8 ETSI GR RIS 003 V1.2.1 (2025-02)
3.3 Abbreviations
For the purposes of the present document, the following abbreviations apply:
2D 2 Dimensional
3D 3 Dimensional
AoA Angle of Arrival
AoD Angle of Departure
AWGN Additive White Gaussian Noise
BLER BLock Error Rate
BS Base Station
CDL Clustered Delay Line
CDS Coherent Demodulation Scheme
CSI Channel State Information
DFT Discrete Fourier Transform
DFT-S Discrete Fourier Transform Spread
DL DownLink
DMRS DeModulation Reference Signal
DoA Direction of Arrival
EIRP Effective Isotropic Radiated Power
EM ElectroMagnetic
EMC ElectroMagnetic Compatibility
EMF ElectroMagnetic Field
gNB g Node B
HARQ Hybrid Automatic Repeat Request
HITRAN High resolution Transmission
HMIMOS Holographic Multiple Input Multiple Output Surface
LLS Link-Level Simulator
LOS Line Of Sight
LS Least Square
MAC Medium Access Control
MCL Minimum Coupling Loss
MCS Modulation and Coding Scheme
MIL Hardware link budget
MIMO Multiple-Input Multiple-Output
MISO Multiple-Input Single-Output
MPL Mechanically Pumped fluid Loop
MU Multi User
NB Node B
NCDS Non Coherent Demodulation Scheme
NLOS Non Line Of Sight
NR New Radio
nRB number of Resource Block
nSC number of Sub-Carriers per resource block
NW Network
O2I Outdoor-to-Indoor
O2O Outdoor-to-Outdoor
OFDM Orthogonal Frequency-Division Multiplexing
PDSCH Physical Downlink Shared Channel
PHY Physical layer
PUSCH Physical Uplink Shared CHannel
RB Resource Block
RF Radio Frequency
RIS Reconfigurable Intelligent Surfaces
RSE Radiated Spurious Emission
RTT Round-Trip Time
RX Receiver
SAR Specific Absorption Rate
SDU Service Data Unit
SIMO Single-Input Multiple-Output
SINR Signal-to-Interference-Noise Ratio
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9 ETSI GR RIS 003 V1.2.1 (2025-02)
SISO Single-Input Single-Output
SM Spatial Modulation
SNR Signal-to-Noise Ratio
SV Saleh-Valenzuela
TBA To Be Added
TdoA Time difference of Arrival
ToA Time of Arrival
TRP Total Radiated Power
TRxP Transmission and Reception Point
TxRU Transmit Radio Unit
UE User Equipment
UL Uplink
ULA Uniform Linear Array
UMa Urban Macro
UMi Urban Micro
US United States
WB Wide-Band
4 Introduction
4.1 General Description
In this clause, the definition of RIS and relevant scenarios are described.
NOTE: The descriptions provided in the present document are aligned with those in ETSI GR RIS 001 [i.1].
4.2 Definition of RIS
Broadly an RIS is defined as follows:
• It is a surface, i.e. it is not a volumetric material, in order to reduce the implementation complexity, the losses,
etc. while still being able to fully control the electromagnetic waves.
• It is an engineered (or intelligent) surface, i.e. it can realize functions that a non-engineered surface (i.e. a
metal plate) cannot realize.
• It is reconfigurable, i.e. its response can be adapted over time based on the network conditions. The
reconfigurability encompasses multiple functions including controlled reflection, refraction, scattering,
modulation, etc.
4.3 Types of RIS
An RIS can be defined in terms of the single or multiple functions that it can realize:
• Reflecting surfaces: This is an RIS that is capable of modifying the angle of reflection of an incident wave.
• Refracting surfaces: This is an RIS that is capable of modifying the angle of refraction (transmission) of an
incident wave.
• Joint reflecting and refracting surfaces: This is an RIS that is capable of simultaneously modifying the
angle of reflection and refraction of an incident wave.
• Transmitting or information surfaces: This is an RIS that is capable of encoding data and to realize
single-RF (single-stream or multi-stream) transmitters. Examples include RIS that encode data onto the
activations patterns of the unit cells or the synthetized radiation patterns.
• Surface for ambient backscattering: This is an RIS that can simultaneously reflect or refract the incident
waves and simultaneously modulate data onto the reflected or refracted wave.
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10 ETSI GR RIS 003 V1.2.1 (2025-02)
• Surfaced for tuned randomness: This is an RIS that is configured in order to increase the scattering in a
given area.
• Absorbing surfaces: This is an RIS that is configured to minimize the scattered field.
• Communication and sensing surfaces: This is an RIS with integrated communication and sensing
capabilities, i.e. a surface that can simultaneously reflect a wave and detect the presence of objects.
4.4 Deployment scenarios
RIS can be utilized in different scenarios, including the following:
Enhanced connectivity and reliability
• Connectivity and reliability boosted by a single RIS.
• Connectivity and reliability boosted by individually controlled multiple RIS.
• Connectivity and reliability enabled by multiple RIS.
• Connectivity and reliability boosted by a single multitenant RIS.
• RIS-aided mobile edge computing.
Enhanced localization and sensing
• Unambiguous localization under favourable problem geometry with a minimal number of base stations.
• Non Line Of Sight (LOS) mitigation for better service coverage and continuity in far-field conditions.
• Non LOS mitigation for better service coverage and continuity in near-field conditions.
• On-demand multi-user and multi-accuracy service provision.
• Opportunistic detection/sensing of passive objects through multi-link radio activity monitoring.
• RIS-assisted search-and-rescue operations in emergency scenarios.
• Localization without BSs using a single or multiple RIS.
• RIS-aided radio environment mapping for fingerprinting localization.
• Radar localization/detection of passive target(s) with hybrid RIS.
Enhanced sustainability and security
• Deployments of RIS to increase the energy efficiency and reduce the power consumption.
• Deployments of RIS to increase security.
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11 ETSI GR RIS 003 V1.2.1 (2025-02)
5 Models for RIS
5.1 Models for communications
5.1.1 General description
Three main communication models for RIS can be adopted [i.4]:
• Locally periodic discrete model.
• Mutually-coupled antenna model.
• Inhomogeneous sheets of surface impedance model.
5.1.2 Locally periodic discrete model
A widely used model for RIS is based on a locally periodic design, in which periodic boundary conditions are applied at
the unit cell level. Accordingly, each RIS reconfigurable element is associated with a set of complex-valued coefficients
(the RIS alphabet). Each element of the alphabet is obtained by appropriately configuring the electronic circuits of the
RIS reconfigurable element. For ease of description, it is assumed that the RIS operates as a reflecting surface. From the
physical standpoint, therefore, the complex-valued coefficient has the meaning of a reflection coefficient, i.e. the ratio
between the reflected electric field and the incident electric field, of an infinite RIS whose elements are all configured to
the same state. Therefore, the corresponding equivalent structure is a homogeneous surface that realizes specular
reflection. According to this definition, each RIS reconfigurable element is characterized by means of locally periodic
boundary conditions, and, since an RIS is not endowed with power amplifiers, the reflection coefficients have an
amplitude that is, by definition, less than one. However, this neither necessarily implies that the amplitude is a constant
independent of the phase nor that the amplitude and the phase can be optimized independently of one another.
5.1.3 Mutually-coupled antenna model
To account for the mutual coupling among closely-spaced RIS elements, a model based on loaded RIS elements
illustrated in Figure 1 can be used.

Figure 1: Mutually coupled antenna model
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12 ETSI GR RIS 003 V1.2.1 (2025-02)
The model resembles a conventional single transmitter-receiver pair Multiple-Input Multiple-Output (MIMO)
communication link in the presence of an RIS. The transmitter and the receiver are equipped with multiple-antenna
elements. For ease of representation, the antenna elements are assumed to be thin wire dipoles. The model can be
utilized for application to radiating elements different from thin wire dipoles. Each antenna element at the transmitter is
driven by a voltage generator that models the transmit feed line, and each antenna element at the receiver is connected
to a load impedance that mimics the receive electronic circuit. The transmission between the transmitter and the
receiver is assisted by an RIS, which comprises several scattering elements that are independently configurable (by an
external controller) through tuneable impedances. The end-to-end transfer function that accounts for the scattering from
the RIS can be formulated as follows [i.5]:
�� ��
�� �� ��
�=(� +� � −� �� +� � � � ) � �� +� �
�� �,� � �,� �,� � �,� � �,� �,� �
where:
��
� =� −� �� +� � �
�,� �,� �,� �,� ��� �,�
��
� = � −� �� +� � �
�,� �,� �,� �,� ��� �,�
��
� = � −� �� +� � �
�,� �,� �,� �,� ��� �,�
��
� =� −� �� +� � �
�,� �,� �,� �,� ��� �,�
Each term of the equations can be computed either numerically or in closed-form [i.5]. The proposed model is
conveniently formulated in a MIMO-like form, which enables one to use optimization methods for optimizing the
tenable loads connected to each scattering element.
In the far-field of each scattering element of the transmitter, receiver, and RIS, the following simplified model can be
used [i.5]:
�� ��
�� ��
� ≈(� +� � ) �� +� � (� −� �� +� � � )
�,� �� �,� � �,� � �,� �,� �,� ��� �,�
This simplified model has wide applicability in wireless communications because it is expected to operate in the
far-field of each scattering element, but not in the far-field of the entire surface.
5.1.4 Inhomogeneous sheets of surface impedance
More precisely, an RIS whose unit cells have sizes and inter-distances much smaller than the wavelength is
homogenizable and can be modeled as a continuous surface sheet through appropriate surface functions, i.e. surface
impedances. This modeling approach is not dissimilar from the characterization of bulk (three-dimensional)
metamaterials, which are usually represented through effective permittivity and permeability functions that determine
the wave phenomena based on Maxwell's equations. The only difference is that a metasurface is better modeled by
effective surface parameters, which manifest themselves in electromagnetic problems that are formulated as effective
boundary conditions. These boundary conditions can be expressed in terms of surface polarizabilities, surface
susceptibilities, or surface impedances (or admittances). Under these assumptions, an RIS can be modeled as an
inhomogeneous sheet of polarizable particles (the unit cells) that is characterized by an electric surface impedance and a
magnetic surface admittance, which, for general wave transformations, are dyadic tensors. These two dyadic tensors
constitute the macroscopic homogenized model of an RIS. Once the homogenized and continuous electric surface
impedance and magnetic surface admittance are obtained based on the desired wave transformations, the microscopic
structure and physical implementation of the RIS in terms of unit cells are obtained. Generally speaking, once the
macroscopic surface impedance and admittance are determined, appropriate geometric arrangements of sub-wavelength
unit cells and the associated tuning circuits that exhibit the corresponding electric and magnetic response are
characterized by, typically, using full-wave electromagnetic simulations.
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13 ETSI GR RIS 003 V1.2.1 (2025-02)
5.2 Models for radio localization and sensing
5.2.1 Scenarios
5.2.1.1 Localization scenarios
With cellular localization, the User Equipment (UE) location can be estimated based on a variety of measurements from
the received signal, including the signal strength, Time of Arrival (ToA), Round-Trip Time (RTT), Angle of
Arrival (AoA) and Angle of Departure (AoD). The scenarios can be categorized as SISO localization, MISO
�, ф, and � indicate
localization, SIMO localization, and MIMO localization as shown in Figure 2, where the symbols
ToAs, AoDs, and AoAs, respectively.

Figure 2: Localization scenarios
5.2.1.2 SISO localization
In this scenario, the Base Station (BS) and UE are both equipped with a single antenna.
In the SISO system with 1 RIS and 1 BS, Wide-Band (WB) pilots should be used to measure the ToAs for the direct
(i.e. the path BS-UE) and the reflected (i.e. the path BS-RIS-UE) paths, from which the resulting TdoA can be can
calculated and so the corresponding hyperboloid in 3D space. By using different RIS phase profiles at different
transmission times, the AoD from the RIS to the UE can be estimated, which geometrically translates to a half-line.
Therefore, the UE position can be calculated via the intersection between such half-line and the abovementioned
hyperboloid.
In the SISO system with 2 (more than 1) RIS and 1 BS, UE positioning even with NB signalling can be performed,
which does not allow ToA estimation. Indeed, the UE position can be estimated via the intersection of the two half-lines
corresponding to the AoDs from the RIS. The direct BS-UE path does not carry any position information, thus
localization can be performed even when the direct path is blocked.
In the SISO system with 1 RIS in the absence of a BS, the RTT and the AoD from the RIS to the UE can be measured.
Geometrically, they respectively correspond to a sphere centred in the RIS and a half-line originated in the RIS, whose
intersection returns the UE position estimate.
5.2.1.3 MISO localization
In this scenario, the BS is equipped with multiple antennas while the UE is with a single antenna. The UE position can
be estimated by intersecting the two half-lines corresponding to the two AoDs from the BS and the RIS.
ETSI
14 ETSI GR RIS 003 V1.2.1 (2025-02)
5.2.1.4 SIMO localization
In this scenario, the UE is equipped with multiple antennas while the BS is with a single antenna. Two AoAs and one
AoD from the RIS can be measured. Using the two AoAs, the user on (part of) a spindle Torus can be located, whose
intersection with the line corresponding the AoD locates the UE. Then the UE orientation can be estimated via the two
AoAs.
5.2.1.5 MIMO localization
In this scenario, both the BS and the UE are e
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