ETSI GR RIS 006 V1.1.1 (2025-06)

Reconfigurable Intelligent Surfaces (RIS); Multi-functional Reconfigurable Intelligent Surfaces (RIS): Modelling, Optimization, and Operation

DGR/RIS-006

General Information

• Status: Not Published
• Technical Committee: RIS - Reconfigurable Intelligent Surfaces
• Current Stage: 12 - Citation in the OJ (auto-insert)
• Due Date: 16-Jun-2025
• Completion Date: 04-Jun-2025

Standards Content (Sample)

GROUP REPORT
Reconfigurable Intelligent Surfaces (RIS);
Multi-functional Reconfigurable Intelligent Surfaces (RIS):
Modelling, Optimization, and Operation
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 006 V1.1.1 (2025-06)

Reference
DGR/RIS-006
Keywords
model, radio, RIS
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ETSI
3 ETSI GR RIS 006 V1.1.1 (2025-06)
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 . 7
4 General aspects of MF-RIS . 8
4.0 General Introduction of MF-RIS . 8
5 Simultaneously transmitting and reflecting RIS. 8
5.0 General Introduction. 8
5.1 Signal and Channel Model . 9
5.1.1 Signal Models for STAR RIS . 9
5.1.2 Channel Models for STAR RIS . 10
5.2 Operating Protocols . 10
5.3 Reconfigurable Coefficient Design . 11
5.3.0 General . 11
5.3.1 Joint Optimization Based STAR Beamforming for the Independent Phase-Shift Model . 12
5.3.2 Element-Wise Based STAR Beamforming for the Coupled Phase-Shift Model . 12
5.3.3 Tile-based STAR Beamforming Design . 13
5.4 Deployment Considerations . 14
5.5 Resource Allocation Schemes . 15
5.5.1 STAR RIS aided transmission-reflection NOMA. 15
5.5.2 STAR RIS aided NCJT . 16
5.6 Performance Analysis . 17
5.6.1 Diversity Analysis . 17
5.6.2 STAR Beamforming Optimization for Power Minimization . 18
6 RIS with sensing capabilities . 19
6.0 General Introduction. 19
6.1 Signal and Channel Model . 19
6.2 Operating Protocols . 20
6.2.0 General . 20
6.2.1 Sensing at the BS and RIS . 20
6.2.2 STAR RIS Protocols for Integrated Sensing and Communications . 21
6.3 Reconfigurable Coefficient Design . 22
6.3.0 General . 22
6.3.1 Beampattern-based Design . 22
6.3.2 Theoretical-boundary-based Design . 22
6.3.2.0 General . 22
6.3.2.1 Optimization Based RIS Beamforming Design . 23
6.3.2.2 Codebook Based RIS Beamforming Design . 23
6.4 Deployment Considerations . 24
6.4.1 Target-mounted RIS . 24
6.5 Resource Allocation Schemes . 24
6.5.1 Joint Offline-Online Scheme . 24
6.6 Performance Analysis . 25
6.6.1 Analysis Framework . 25
7 RIS with Other Capabilities . 26
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4 ETSI GR RIS 006 V1.1.1 (2025-06)
7.0 General Introduction. 26
7.1 RIS with Computing Capabilities . 26
7.1.0 General . 26
7.1.1 Multi-Layer RIS Architecture with Computing Capabilities . 26
7.1.2 STAR RIS Architecture with Computing Capabilities . 27
7.2 RIS with Caching Capabilities . 28
8 Conclusion . 29
History . 30

ETSI
5 ETSI GR RIS 006 V1.1.1 (2025-06)
Intellectual Property Rights
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pertaining to these essential IPRs, if any, are publicly available for ETSI members and non-members, and can be
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ETSI in respect of ETSI standards", which is available from the ETSI Secretariat. Latest updates are available on the
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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 006 V1.1.1 (2025-06)
1 Scope
The present document is to:
a) identify technological challenges and summarize technical solutions for MF-RIS incorporating transmission,
reflection, sensing, computation, and other potential functions;
b) study channel modelling, coefficient optimization, deployment design, resource allocation and other technical
aspects of MF-RIS;
c) suggest possible ways of deploying MF-RIS in real-world scenarios and the expected performance
enhancement in different scenarios.
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 may be useful in implementing an ETSI deliverable or add to the reader's
understanding, but are not required for conformance to the present document.
[i.1] ETSI GR RIS 001: "Reconfigurable Intelligent Surfaces (RIS); Use Cases, Deployment Scenarios
and Requirements".
[i.2] ETSI GR RIS 003: "Reconfigurable Intelligent Surfaces (RIS); Communication Models, Channel
Models, Channel Estimation and Evaluation Methodology".
[i.3] X. Mu, et al.: "Simultaneously Transmitting and Reflecting (STAR) RIS Aided Wireless
Communications", in IEEE™ Transactions on Wireless Communications, vol. 21, no. 5,
pp. 3083-3098, May 2022.
[i.4] Y. Liu, et al.: "Simultaneously Transmitting and Reflecting (STAR)-RISs: A Coupled Phase-Shift
Model", ICC 2022 - IEEE™ International Conference on Communications, Seoul, Korea,
Republic of, 2022, pp. 2840-2845.
[i.5] R. Liu, J. Dou, P. Li, J. Wu and Y. Cui: "Simulation and Field Trial Results of Reconfigurable
Intelligent Surfaces in 5G Networks", in IEEE™ Access, vol. 10, pp. 122786-122795, 2022.
[i.6] R. Zhong, et al.: "STAR-RISs Assisted NOMA Networks: A Distributed Learning Approach", in
IEEE™ Journal of Selected Topics in Signal Processing, vol. 17, no. 1, pp. 264-278, January 2023.
[i.7] Q. Wu, et al.: "Intelligent surfaces empowered wireless network: Recent advances and the road to
6G", in Proceedings of the IEEE™, vol. 112, no. 7, pp. 724-763, July 2024.
[i.8] X. Shao, et al.: "Target Sensing With Intelligent Reflecting Surface: Architecture and
Performance", in IEEE™ Journal on Selected Areas in Communications, vol. 40, no. 7,
pp. 2070-2084, July 2022.
[i.9] ETSI GR RIS 002: "Reconfigurable Intelligent Surfaces (RIS); Technological challenges,
architecture and impact on standardization".
ETSI
7 ETSI GR RIS 006 V1.1.1 (2025-06)
[i.10] Z. Wang, et al.: "STARS Enabled Integrated Sensing and Communications", in IEEE™
Transactions on Wireless Communications, vol. 22, no. 10, pp. 6750-6765, October 2023.
[i.11] Q. Peng, et al.: "Semi-passive intelligent reflecting surface enabled sensing systems", in IEEE™
Transactions on Communications, vol. 72, no. 12, pp. 7674-7688, Dec. 2024.
[i.12] M. Hua, et al.: "Intelligent reflecting surface assisted localization: Performance analysis and
algorithm design", in IEEE™ Wireless Communications Letters, vol. 13, no. 1, pp. 84-88,
January 2024.
[i.13] K. Meng, et al.:"Sensing-Assisted Communication in Vehicular Networks with Intelligent
Surface", in IEEE™ Transactions on Vehicular Technology, vol. 73, no. 1, pp. 876-893,
January 2024.
[i.14] E. Björnson, et al.: "Reconfigurable Intelligent Surfaces: A signal processing perspective with
wireless applications", in IEEE™ Signal Processing Magazine, vol. 39, no. 2, pp. 135-158,
March 2022.
[i.15] C. Ouyang, et al.: "Integrated Sensing and Communications: A Mutual Information-Based
Framework", in IEEE™ Communications Magazine, vol. 61, no. 5, pp. 26-32, May 2023.
[i.16] J. An, et al.: "Stacked Intelligent Metasurface-Aided MIMO Transceiver Design", in IEEE™
Wireless Communications, vol. 31, no. 4, pp. 123-131, August 2024.
[i.17] Z. Hu, et al.: "Caching-at-STARS: the Next Generation Edge Caching", in IEEE™ Transactions
on Wireless Communications, vol. 23, no. 8, pp. 8372-8387, August 2024.
3 Definition of terms, symbols and abbreviations
3.1 Terms
Void.
3.2 Symbols
Void.
3.3 Abbreviations
For the purposes of the present document, the following abbreviations apply:
AoA Angles of Arrival
AP Acces Point
BS Base Station
CRLB Cramér-Rao Lower Bound
CSI Channel State Information
DFT Discrete Fourier Transform
DoA Direction of Angle
DoF Degrees of Freedom
EM ElectroMagnetic
ES Energy Splitting
IMT International Mobile Telecommunication
ISAC Integrated Sensing And Communication
JO Joint Optimization
LoS Line of Sight
MF-RIS Multi-Functional Reconfigurable Intelligent Surfaces
MIMO Multiple-Input Multiple-Output
NCJT Non-Coherent Joint Transmission
NOMA Non-Orthogonal Multiple Access
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8 ETSI GR RIS 006 V1.1.1 (2025-06)
O2I Outdoor-to-Indoor
RF Radio Frequencies
RIS Reconfigurable Intelligent Surfaces
RoI Region of Interest
S&C Sensing and Communication
SIM Stacked Intelligent Metasurfaces
SINR Signal-to-Interference-plus-Noise Ratio
SNR Signal-to-Noise Ratio
SS Surface Splitting
SSB Synchronization Signal Block
STAR Simultaneously Transmitting And Reflecting
TDM Time Division Mode
ToA Time of Arrival
TS Time Switching
UE Use Equipment
4 General aspects of MF-RIS
4.0 General Introduction of MF-RIS
Following the general definition of RIS in clause 4 of ETSI GR RIS 001 [i.1], RIS integrated with multiple
functionalities (e.g. transmission (refraction)), reflection, sensing, computing, and caching), namely MF-RIS, is
discussed in the present document with their signal modelling, operating protocols, possible deployment considerations,
RIS coefficients design, and performance analysis. Here, the different types of MF-RIS to be discussed are listed as
below:
• STAR RIS: This is an RIS that integrate the two fundamental transmission (refraction) and reflection
functions into one single surface, which can forward the incident wireless signals into both sides of the RIS,
i.e. achieving a full-space coverage.
• RIS with sensing capabilities: This is an RIS that integrates active sensors to detect the surrounding targets
and/or feedback the sensing results to the base stations or users.
• RIS with computing capabilities: This is an RIS that achieves dedicated signal processing tasks
(e.g. precoding and signal detection) during the wireless signal passing through the surface.
• RIS with caching capabilities: This is an RIS that is installed with caching memory to provide content
delivery service to end users.
5 Simultaneously transmitting and reflecting RIS
5.0 General Introduction
STAR RIS is a tunable surface that integrates the transmission (refraction) and reflection functions. As depicted in
Figure 5.0-1, the wireless signal incident upon the STAR RIS can be simultaneously transmitted and reflected into the
two sides with modified angles. There are various tunable surface designs that are potential candidates for realizing
STAR RIS. In terms of periodic structure, STAR RIS hardware implementations can be loosely divided into two
categories, namely, patch-array-based implementations and metasurface-based implementations. Patch-array-based
implementations consist of periodic cells with sizes on the order of a few centimetres. Because of their relatively large
sizes, each cell (patch) can be made tunable by incorporating positive-intrinsic-negative diodes or delay lines. By
contrast, metasurface-based implementations have periodic cells on the order of a few millimetres, possibly
micrometres, and even molecular sizes. Hence, they require more sophisticated controls of their EM properties, such as
conductivity and permittivity. The candidate materials include but not limited to smart glass, graphene, etc.
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9 ETSI GR RIS 006 V1.1.1 (2025-06)

Figure 5.0-1: Illustration of the STAR RIS concept
5.1 Signal and Channel Model
5.1.1 Signal Models for STAR RIS
By exploiting the field equivalence principle, each STAR RIS element is excited by the incident signal, the transmitted
and reflected signals can be equivalently treated as waves radiated from the time-varying surface equivalent electric
currents � and equivalent magnetic currents � , as shown in Figure 5.1-1. For the m-th element, the strengths and
� �
distribution of these surface equivalent currents are determined by the incident narrowband signal � as well as the
�
local surface averaged electric and magnetic impedances � and � . Let � denote the signal incident upon the m-th
� � �
� and � , with the same
element. Assume that the STAR RIS produces both transmitted and reflected signals, namely
� �
polarization, these signals can be expressed as:
� �� � ,   � �� � ,
� � � � � �
where � and � are the transmission and reflection coefficients of the m-th element, respectively. According to the
� �
law of energy conservation, for passive STAR RIS elements, the following constraint on the local transmission and
reflection coefficients are satisfied:
� �
|� | �|� | �1.
� �
According to electromagnetic theory, the phase delays of both the transmitted and reflected field are related to � and
�
� . In Figure 5.1-1, the reconfigurability of the element is reflected in the change of the surface impedances, since the
�
transmission and reflection coefficients of the m-th element is related to the surface impedances as follows:
��� �
� �
� � �� ,
� �
��� �
� �
�
��� � �� �
� �
�
� �� ,
�
� �� �
��� � �� ��
� � � �
where � is the impedance of free space. To facilitate the design of STAR RIS in wireless communication systems, the
�
transmission and reflection coefficients of the m-th element can be further rewritten in the form of their amplitudes and
phase shifts as follows:
� �
�� ��
� �
� �
� � �� � ,  � ��� � ,
� � � �
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10 ETSI GR RIS 006 V1.1.1 (2025-06)
� � �
� � � � � �
where � ∈ 0,1 and � ∈ 0,1 are real-valued amplitude coefficients for transmission and reflection. � ∈ 0, 2�
� � �
�
� �
and � ∈ 0, 2� are the phase shifts introduced by the m-th element for the transmitted and reflected signals. Here, due
�
� �
to the law of energy conservation, � +� ≤1.
� �
Figure 5.1-1: Schematic illustration of STAR RIS
The value of transmission and reflection coefficients (� and � ) are determined by the two complex-valued
� �
impedances, � and � , i.e. tuning surface electric and magnetic impedances. In terms of the phase-shift adjustment
� �
capabilities, there are two main categories of phase-shift models for STAR RIS:
�
• Independent phase-shift model: For this STAR RIS, the transmission phase shift (� ) and the reflection
�
�
� ) can be adjusted independently with each other. The independent phase-shift model has the
phase shift (
�
maximum DoF for communication design. However, the independent phase-shift model is challenging to
realize in practice, especially for passive STAR RIS. This is because if STAR RIS is made of passive
materials, the corresponding electric impedance (� ) and magnetic impedance (� ) cannot be arbitrary values.
� �
• Coupled phase-shift model: For STAR RIS using passive lossless materials, the corresponding electric
impedance and magnetic impedances should be purely imaginary numbers. Under this constraint, the
� �
transmission phase shift (� ) and the reflection phase shift (� ) are coupled subject to specific values of
� �
phase-shift differences as follows:
� �
� �
|� −� | = � �� �.
� �
� �
5.1.2 Channel Models for STAR RIS
For channels associated with STAR RIS, they follow the channel models presented in clause 7 of ETSI
GR RIS 003 [i.2].
5.2 Operating Protocols
By adjusting the amplitude coefficients used for both transmission and reflection, each STAR RIS element can operate
in full transmission mode (referred to as the T mode), full reflection mode (referred to as the R mode), or simultaneous
transmission and reflection mode (referred to as the T&R mode). As shown in Figure 5.2-1, by exploiting such
adjustment capabilities, at least three operating protocols can be used to deploy the STAR RIS:
• Energy Splitting (ES): For ES, all elements of the STAR RIS are assumed to operate in T&R mode, as shown
in Figure 5.2-1(1). For given transmission and reflection amplitude coefficients, the signals incident upon each
element are split into transmitted and reflected signals having different energy. In a practical implementation,
� � � �
� ,� ) and phase-shift coefficients (� ,� ) of each element for transmission and reflection
the amplitude (
� � � �
can be optimized jointly for achieving diverse design objectives in wireless networks.
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11 ETSI GR RIS 006 V1.1.1 (2025-06)
• Surface Splitting (SS): In SS, all elements of the STAR RIS are partitioned into two or more groups.
Specifically, one group contains the elements that operate in T mode, while the other group contains the
elements operating in R mode. It is possible to have another group, comprising of elements without any phase
shift. The surface can be split into many groups, potentially serving different user devices. As shown in
Figure 5.2-1(2), a SS STAR RIS can be viewed as being composed of a conventional reflecting-only RIS and a
transmitting-only RIS of reduced sizes. Under this protocol, the element-wise mode selection and the
corresponding transmission and reflection phase shift coefficients can be optimized jointly. The drawback is
that under this mode, the transmission and reflection gain is reduced since only a subset of the elements are
selected for transmission and reflection.
• Time Switching (TS): The STAR RIS employing the TS protocol periodically switches all elements between
T mode and R mode in orthogonal time slots (referred to as T period and R period), as illustrated in
Figure 5.2-1(3). The fraction of time allocated to fully transmitting and fully reflecting signals can be
optimized to achieve a balance between the communication qualities of the front and back sides. Compared to
ES and SS, the advantage of TS is that, for a given time allocation, the transmission and reflection coefficients
are not coupled; hence, they can be optimized independently. Nevertheless, periodically switching the
elements imposes stringent time synchronization requirements, thus increasing the implementation complexity
compared to the ES and SS, as well as potential power consumption.

Figure 5.2-1: Illustration of three possible protocols for operating STAR RIS
5.3 Reconfigurable Coefficient Design
5.3.0 General
Reconfigurable coefficient design, also known as passive beamforming design, is important to unlock the full benefits
of STAR RIS in wireless communications. Note that depending on the near-field or far-field channel models
considered, the beamforming can exhibit either beamfocusing or beamsteering characteristic. For a pre-configured
communication system, where the BS is connected with the STAR RIS via a controller, a general STAR beamforming
design problem can be expressed as follows:
��������
� � � �
��� ,� ,� ,� ,��
� � � �
�������
� � � �
�� ,� ,� ,� �
� � � �
� � � �
�.�. � +� ≤1,� ∈�0, 2��,� ∈�0, 2��,
� � � �
� �
� �
| |
� −� = � �� �,�� �ℎ� ������� �ℎ��� −�ℎ��� ����� �� ����������,
� �
� �
��ℎ�� �����������.
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12 ETSI GR RIS 006 V1.1.1 (2025-06)
Here, � represents the set of other optimization variables that are not relevant to STAR RIS, such as user power
allocation and BS active beamforming vectors. Despite different operating protocols impose different constraints on the
STAR beamforming design problem, the beamforming design in ES STAR RIS is much more challenging than that in
SS STAR RIS and TS STAR RIS. The case becomes even worse when considering the coupled phase-shift model.
Therefore, tailored passive beamforming algorithms are required. Note that the accurate CSI is essential for the passive
beamforming design. For STAR RIS, the CSI can be subsequently obtained by exploiting the TS protocol and CSI
estimation methods in clause 8 of ETSI GR RIS 003 [i.2]. In the following, the passive beamforming design is
discussed assuming perfect CSI.
5.3.1 Joint Optimization Based STAR Beamforming for the Independent
Phase-Shift Model
For ES STAR RIS-assisted communication systems with the independent phase-shift model. the main challenge lies in
the coupling between the newly introduced STAR beamforming and the existing variables (e.g. BS active beamforming
and power allocation). One existing way is to decompose the original joint BS and RIS beamforming problem into two
subproblems and alternatingly optimizes one beamforming with the other fixed. Alternatively, an efficient JO-based
beamforming approach is developed for minimizing the BS power consumption in a STAR RIS-assisted multiple-input
single-output multi-user communication system [i.3]. As shown in Figure 5.3-1, the BS beamforming and STAR
beamforming in the JO-based approach can be simultaneously optimized in each iteration.

Figure 5.3-1: Joint optimization based STAR beamforming design
5.3.2 Element-Wise Based STAR Beamforming for the Coupled
Phase-Shift Model
For ES STAR RIS assisted communication systems with the coupled phase-shift model, the STAR beamforming design
becomes quite challenging. This is because, for each STAR element, the transmission and reflection phase shifts are
coupled. To facilitate the corresponding STAR beamforming design, an efficient element-wise based STAR
beamforming approach is developed for minimizing the BS power consumption in a STAR RIS assisted single-input
single-output two-user communication system [i.4]. As shown in Figure 5.3-2, the salient feature is that the phase-shift
and amplitude coefficients of each STAR element are optimized one by one, i.e. in an element-wise manner. Therefore,
the computational complexity only linearly scales with the number of STAR elements, which renders it promising to be
used in practice since the size of STAR RIS is usually large.
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13 ETSI GR RIS 006 V1.1.1 (2025-06)

Figure 5.3-2: Element-wise based STAR beamforming design
5.3.3 Tile-based STAR Beamforming Design
The complexity of the passive beamforming design is a critical challenge for STAR RIS. Since the reconfigurable
elements are not likely to have a power amplification function and the incident signal has experienced fading before
arriving at the STAR RIS, the transmitted or reflected signal from each single element has limited energy. Hence, in
order to ensure sufficient strength of the reflected signal, a large STAR RIS panel having a massive number of elements
is necessary. Once an enormous number of elements are employed in the STAR RIS, the optimization complexity of
their transmission and reflection coefficients will increase significantly, which leads to challenges on complexity of the
beamforming.
A tile-based low-complexity beamforming approach can be employed to empower the STAR RIS, where the elements
on STAR RIS are partitioned into several tiles [i.6]. The elements in the same tile, also as known as subsurface, have
the same transmission and reflection coefficients. The tile-based beamforming approach no longer requires the STAR
RIS controller to calculate reconfigurable coefficients for each element. The STAR RIS controller only needs to plan
reconfigurable coefficients for each tile, thereby reducing the complexity of signalling, control circuitry, and computing
required by STAR RIS beamforming.
STAR Controller: tile
partition, reconfigurable
coeffici ents
BS
STAR RIS
Figure 5.3-3: Tile based STAR RIS beamforming design
Specifically, the tile-based beamforming for two STAR RIS operating protocols, ES and SS are shown as below. As
shown in Figure 5.3-4(a), for ES protocol, each tile has transmission and reflection capabilities. The size, shape, and
element partitioning of the tile can be flexible or fixed depending on the specific case. In contrast, in the SS protocol,
each tile can selectively work in transmission or reflective modes.
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14 ETSI GR RIS 006 V1.1.1 (2025-06)
Incident Signal
T mode R mode
T&R mode
Reflected Signal
Transmitted Signal
(a) (b)
Figure 5.3-4: Tile based STAR RIS beamforming design (a) ES protocol. (b) SS protocol
5.4 Deployment Considerations
Considering STAR RIS as more advanced type of RIS, they can be primarily considered for deployment scenarios
where typical reflecting-only or transmit (refract)-only RIS cannot fully serve the intended coverage region. Compared
to reflecting-only or transmit (refract)-only RIS, the key benefit of STAR RIS is that they can be leveraged to provide
close to 360-degree coverage, i.e. both the front region and back region of the RIS surface can be served with STAR
RIS.
One of the important deployment scenarios for STAR RIS could be to extend both outdoor coverage and
outdoor-to-indoor coverage using the same RIS, as illustrated in Figure 5.4-1. In the deployment scenario illustrated in
Figure 5.4-1, the RIS could either be deployed on a window or it could be integrated on the wall of the building. In the
case where the RIS is deployed on a window, depending on the implementation, it may allow light to pass through, or
not.
O2I coverage with refraction via STAR RIS
Outdoor coverage with reflection via STAR RIS

Figure 5.4-1: Illustration of STAR RIS deployment for outdoor and O2I coverage with same RIS
Furthermore, STAR RIS could possibly operate in different modes, e.g. energy-split mode, where transmit (refract) and
reflect happen simultaneously; or time-split mode, where transmit (refract) and reflect happen at different time
instances. One mode maybe more suited than the other mode depending on the use-cases. Energy-split mode with
simultaneous transmission and reflection would be beneficial for channels/signals that need to be transmitted to multiple
users, such as broadcast, multicast, and group-common channels/signals. For example, it could be beneficial to have
STAR RIS operating either in ES mode for transmission of synchronization signal blocks, i.e. the same SSB beam
transmitted from the base station is transmitted (refracted) and reflected at the same time via STAR RIS or beam
sweeping of SSB via STAR RIS in TDM manner.
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One of the most promising applications of STAR RIS is to enlarge the coverage area and improve the quality of
wireless transmissions, especially when the links between the BSs or access points and users are severely blocked
(e.g. by trees along roads, buildings, and metallic shells of vehicles). As shown in Figure 5.4-2, the deployment of
STAR RIS can be divided into three scenarios, namely outdoor, outdoor-to-indoor, and indoor, as these are identified as
three important scenarios for RIS deployment and testing [i.5]:
• Outdoor: In outdoor scenarios, similar to conventional reflecting-only RISs, STAR-RISs can be mounted on
building facades and roadside billboards to create additional communication links. More innovatively, STAR
RIS can also be accommodated by the windows of vehicles (e.g. cars, aircraft, and cruise ships) to enhance the
signal strength received inside by exploiting their transmission capability, thus extending the coverage
area/quality of BSs and satellites.
• Outdoor-to-Indoor: It is usually challenging to serve indoor users with outdoor BSs since the severe
penetration loss caused by building walls gravely restricts the coverage provided by outdoor BSs, especially in
mmWave bands. In fact, STAR RIS constitutes an efficient technique for creating an outdoor-to-indoor bridge
as illustrated in the middle of Figure 5.4-2. STAR RIS can serve users both indoors and outdoors by
simultaneously reflecting and transmitting signals to both directions.
• Indoor: For indoor communications, STAR RIS is more appealing than conventional reflecting-only RISs. As
conventional reflecting-only RISs merely achieve half-space coverage, the signals emerging from the AP may
require multi-hop bounces for reaching the target user. However, by exploiting both transmission and
reflection, the resultant full-space coverage may reduce the propagation distance, thus increasing the received
signal power.
Figure 5.4-2: Illustration of deploying STAR RIS for wireless coverage extension
5.5 Resource Allocation Schemes
5.5.1 STAR RIS aided transmission-reflection NOMA
As recommended by IMT-2030, NOMA and RIS are important technique for mobile services in the years 2030 and
beyond. For NOMA to achieve a high performance gain over orthogonal multiple access, it is important to pair users
having different channel conditions. However, for conventional reflecting-only RISs, the benefits of NOMA may not be
fully reaped since the channel conditions of users in the local reflected space are generally similar. Exploiting STAR
RIS facilitates a more beneficial communication framework, namely transmission-reflection NOMA, where a pair of
users at the transmission- and reflection-oriented side can be grouped together for supporting NOMA, as shown in
Figure 5.5-1. For example, the reflected and transmitted signals can pertain to a high-date rate video streaming user and
a low-date rate Internet-of-Things user, respectively. By optimizing the transmission and reflection coefficients of
STAR RIS, sufficiently different transmitted and reflected channel conditions can be achieved, thus enhancing the
NOMA gain. As a result, the STAR RIS aided transmission-reflection NOMA resource allocation framework is well
suited to support the heterogenous quality-of-service requirements of the two types of users.
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Figure 5.5-1: STAR RIS aided transmission-reflection NOMA
5.5.2 STAR RIS aided NCJT
For realistic multi-cell communication networks, the performance of cell-edge users cannot be guaranteed due to the
strong inter-cell interference. NCJT can be exploited to enhance the quality of experience of cell-edge users. In
Figure 5.5-2, a beneficial STAR RIS-aided NCJT resource allocation scenario is presented. In particular, several
multiple-antenna BSs are coordinated to serve a cell-edge user. Additionally, each BS can also individually serve an
additional cell-centre user. A STAR RIS is deployed in each cell where the cell-edge user is located in the transmission
half space, while the cell-centre user is located in the reflection half-space. The advantages of this resource allocation
scheme are that on one hand, the received SINR of the cell-edge user can be enhanced through NCJT and the design of
the transmission coefficients of all STAR RISs, while on the other hand, the reflection coefficients of each STAR RIS
can be optimized for enhancing the performance of the cell-edge user.

Figure 5.5-2: STAR RIS aided NCJT
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5.6 Performance Analysis
5.6.1 Diversity Analysis
Consider a frequency-flat narrowband communication system with a single-antenna Tx, two single-antenna Rxs, and a
STAR RIS consisting of � elements. One Rx is located at the transmission region of STAR RIS, and the other Rx is
located at the reflection region of STAR RIS. Perfect CSI is assumed, and the independent phase-shift model is
�� ��
considered for STAR RIS. Let ℎ ∈ denote the channel coefficient of Tx-to-Rx channel, ! ∈ denote the
�
��
channel vector from Tx to STAR RIS, " ∈  denote the channel vector from STAR RIS to Rx, and
�
� �
�
� �� �� � ��
�
� � �
# =diag$%� � ,.,&� � ,.,%� � ’ denote the reconfigurable coefficient matrix of STAR RIS. Here,
� �
� �
� ∈(�,�) indicates the transmitted or reflected Rx. The end-to-end channel gain of Rx � is given by:
� � �
| | | |
* = ℎ +" # ! .
� � � �
Under the target SNR for Rx � (+̅), the outage probability can be expressed as:
�
�
�� �
�
� �
� � | |
- +̅=Pr. * < /,
���,� � �
�
�
�
where � is the signal power allocated for Rx � and 0 is the received noise power. The diversity order of Rx � defined
� �
through the outage probability is gi
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