ETSI TR 103 952 V1.1.1 (2025-08)

Smart Body Area Network (SmartBAN); Brain Computer Interface (BCI)

DTR/SmartBAN-0022

General Information

• Status: Not Published
• Technical Committee: SmartBAN - Smart Body Area Network
• Current Stage: 12 - Citation in the OJ (auto-insert)
• Due Date: 06-Aug-2025
• Completion Date: 12-Aug-2025

Standards Content (Sample)

TECHNICAL REPORT
Smart Body Area Network (SmartBAN);
Brain Computer Interface (BCI)

2 ETSI TR 103 952 V1.1.1 (2025-08)

Reference
DTR/SmartBAN-0022
Keywords
device, implant, radio interface
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3 ETSI TR 103 952 V1.1.1 (2025-08)
Contents
Intellectual Property Rights . 5
Foreword . 5
Modal verbs terminology . 5
Executive summary . 6
1 Scope . 7
2 References . 7
2.1 Normative references . 7
2.2 Informative references . 7
3 Definition of terms, symbols, and abbreviations . 8
3.1 Terms . 8
3.2 Symbols . 8
3.3 Abbreviations . 8
4 BCI overview . 8
5 BCI system considerations . 11
5.1 Energy source . 11
5.1.0 Introduction. 11
5.1.1 Battery . 11
5.1.2 Energy harvesting . 12
5.1.3 Wireless power transfer . 12
5.2 Communication interface . 12
5.2.0 Introduction. 12
5.2.1 Backscatter communication in the near field . 13
5.2.2 ECoG wireless links. 13
5.3 Body Tera Hertz networks. 15
5.3.0 Introduction. 15
5.3.1 Enhancements to channel modeling . 16
5.3.2 Electronic and photonic technologies . 16
5.3.2.0 Introduction . 16
5.3.2.1 Electronic sources . 17
5.3.2.2 Photonic sources . 17
6 Design considerations. 17
6.0 General . 17
6.1 Selecting THz frequency bands . 18
6.1.1 General . 18
6.1.2 WRC-23 AI 1.14 . 18
6.1.3 WRC-27 AI 1.8 . 18
6.1.4 WRC-23 resolution 731 . 19
6.1.5 WRC-31 Potential New AI . 19
6.2 Photonic technology in THz transmission . 19
6.2.1 Overview . 19
6.2.2 Technical challenges . 21
7 Aspects of THz radio propagation . 23
7.1 General . 23
7.2 Frequency bands . 23
7.3 Channel modeling approaches . 24
7.3.1 General . 24
7.3.2 Extension to ETSI TR 138 901 Study on channel model for frequencies from 0,5 GHz to 100 GHz . 24
7.3.2.0 Introduction . 24
7.3.2.1 Frequency range up to 100 GHz . 25
7.3.2.2 Planar wave modeling . 25
7.3.2.3 Handling of large bandwidths . 26
7.3.2.4 Lack of sensing channel modeling . 26
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4 ETSI TR 103 952 V1.1.1 (2025-08)
7.3.3 Molecular absorption . 27
7.3.4 Human Blockage . 27
7.3.5 Effect of THz radiation on skin . 28
7.4 Propagation modelling . 29
7.4.1 Spherical wave model . 29
8 Aspects of THz hardware interfaces . 31
8.1 ADC and DAC . 31
8.2 Sub-THz transceivers based on photonics . 35
8.3 Radio interface impairments. 37
Annex A: Biological effects of THz radiation . 38
A.1 DNA damage . 38
Annex B: Bibliography . 40
Annex B: Change history . 41
History . 42

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5 ETSI TR 103 952 V1.1.1 (2025-08)
Intellectual Property Rights
Essential patents
IPRs essential or potentially essential to normative deliverables may have been declared to ETSI. The declarations
pertaining to these essential IPRs, if any, are publicly available for ETSI members and non-members, and can be
found in ETSI SR 000 314: "Intellectual Property Rights (IPRs); Essential, or potentially Essential, IPRs notified to
ETSI in respect of ETSI standards", which is available from the ETSI Secretariat. Latest updates are available on the
ETSI IPR online database.
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BLUETOOTH is a trademark registered and owned by Bluetooth SIG, Inc.
Foreword
This Technical Report (TR) has been produced by ETSI Technical Committee Smart Body Area Network (SmartBAN).
The contents of the present document are subject to continuing work within the SmartBAN TB and may change
following formal TB approval. Should the TB change the contents of the present document, it will be re-released by the
TB with an identifying change of release date and an increase in version number as follows:
Version x. y. z
where:
x the first digit:
0: presented to the TB for information.
1: presented to the TB for approval.
2: or greater shows the TB-approved document under change control.
y the second digit is incremented for technical changes, corrections, or updates.
z the third digit is incremented for editorial changes.
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.
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6 ETSI TR 103 952 V1.1.1 (2025-08)
Executive summary
The present document lays out an outlook for the Brain-Computer Interface (BCI) use case with an invasive ECoG
implant and an interface for Wireless Power Transfer (WPT) and data communications. Coping with the high
throughput required to capture large portions of the brain, THz technology is presented as a potential new healthcare
vertical for future wireless systems, such as 6G and an extension of SmartBAN networks.

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7 ETSI TR 103 952 V1.1.1 (2025-08)
1 Scope
The present document is limited to providing information for the brain computer interface use case.
The present document discusses proof of concept in the design of the wireless interface for the next-generation of
μECoG electrode arrays implanted in the human brain. This includes recording and stimulation of large regions of the
brain at a high spatial resolution, as well as energy harvesting, power management, and data communications
processing. In particular, the present document focuses on the wireless communication interface.
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 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.2] T. Nagatsuma, et al.: "Advances in terahertz communications accelerated by photonics", Nature
Photonics, vol. 10, pp. 371 to 379, 2016.
[i.3] R.B. Reilly: Neurology: central nervous system, in: J.G. Webster (Ed.), "The Physiological
Measurement Handbook", CRC Press, New York, 2014.
[i.4] R. Muller et.al.: "A minimally invasive 64-channel wireless μECoG implant", IEEE Journal of
Solid-State Circuits 50 (1) (2015).
[i.5] P.P. Mercier, A.P. Chandrakasan (Editors.): "Ultra-Low-Power Short-Range Radios", Springer,
2015.
[i.6] IEC/IEEE™ 62209-1528: "Measurement procedure for the assessment of specific absorption rate
of human exposure to radio frequency fields from hand-held and body-worn wireless
communication devices".
[i.7] R. Kankula: "Advances in hardware systems for implantable medical devices: challenges and
opportunities", International Research Journal of Modernization in Engineering Technology and
Science 7(3):2582-5208.
[i.8] Basabi, Inokawa, Roy (Editors): "Terahertz Biomedical and Healthcare Technologies", 2020,
Elsevier.
[i.9] Kürner, Mittleman, Nagatsuma (Editors): "THz Communications Paving the Way Towards
Wireless Tbps", 2022, Springer.
[i.10] World Radiocommunication Conference 2023 (WRC-23) Final Acts.
[i.11] IEEE Std 802.15.3™-2017: "IEEE Standard for High Data Rate Wireless Multi-Media Networks".
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3 Definition of terms, symbols, and abbreviations
3.1 Terms
For the purposes of the present document, the following terms apply:
craniotomy: surgical removal of a portion of the skull
energy scavenging: conversion of ambient energy present in the environment into electrical energy for use in powering
electronic devices or circuits
3.2 Symbols
Void.
3.3 Abbreviations
For the purposes of the present document, the following abbreviations apply:
AP Access Point
BCI Brain-Computer Interface
BER Bit Error Rate
EAP Extracellular Action Potentials
ECoG Electrocorticography
EEG ElectroEncephaloGraphy
MEG Magneto-Encephalon-Graphy
MRI Magnetic Resonance Imaging
NFC Near-Field Communication
PET Positron Emission Tomography
QCL Quantum Cascade Laser
RF Radio Frequency
RTD Resonant Tunneling Diodes
SAR Specific Absorption Rate
THz Tera Herz
UTC-PD Uni-Traveling-Carrier Photodiode
WPT Wireless Power Transfer
4 BCI overview
The use case of BCI targets the development and application of innovative neural technologies to advance the resolution
of neural recording and stimulation toward the dynamic mapping of brain activity and neural processing. These
advanced neuro-technologies will enable new studies and experiments to advance the current understanding of the
brain. Hence, enabling advances in diagnosis and treatment opportunities over a broad range of neurological diseases
and disorders, as well as commercial applications.
Studying the dynamics and connectivity of the brain requires a wide range of technologies to address temporal and
spatial resolutions. Figure 1 shows such spatial and temporal resolutions in the function of various brain monitoring
technologies that are currently available [i.3].
Noninvasive methods such as Magnetic Resonance Imaging (MRI), Functional Magnetic Resonance Imaging (FMRI),
Magneto-Encephalon-Graphy (MEG), and Positron Emission Tomography (PET) provide whole-brain spatial coverage:
• FMRI provides high spatial resolution (around 1 mm), but its temporal resolution is limited (1 sec to 10 sec)
for the system measuring neural activity.
• MEG provides higher temporal resolution (0,01 sec to 0,1 sec) at the expense of spatial resolution (1 cm).
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• PET offers molecular selectivity in functional imaging at the expense of lower spatial (1 cm) and temporal
(10 sec to 100 sec) resolutions. However, neither FMRI, MEG, nor PET is suitable for wearable or portable
applications, as they all require very large, expensive, and high-power equipment to support the sensors, as
well as extensively shielded environments.
In contrast, electrophysiology methods that directly measure electrical signals from the neurons' activity offer superior
temporal resolution. They have been extensively used to monitor brain activity due to their ability to capture wide
ranges of brain activities from the subcellular level to the whole brain oscillation level as shown in Figure 1.
EEG
Scalp
Epidural
Outer skull table
ECoG
Subdural
Skull
Diploe
EAP & LFP
ECoG
Inner skull table
Dura matter
Arachnoid
Cerebrospinal
fluid
Pia matter
Cortex
Figure 1: Illustration of electrophysiology methods
Due to recent advances in electrode and integrated circuit technologies, electrophysiological monitoring methods have
become portable with wearable or implantable configurations for BCI. In particular, Electro-Encephalography (EEG)
records the electrical activity on the scalp resulting from volume conduction of neural activity across the brain, as
shown in Figure 1. Moreover, EEG recording is noninvasive, but its spatiotemporal resolution is limited to about 1 cm
and 100 Hz due to the electrical properties of diverse layers of head and brain tissues, particularly the skull (between the
brain and the scalp).
In contrast, microelectrodes technology such as Extracellular Action Potentials (EAPs) and Local Field Potentials
(LFPs) enable recording from multiple neurons across multiple cortical areas and layers. Those can achieve much
higher resolution because of the closer proximity to individual neurons. Hence, EAP+LFP techniques are widely used
for brain research and BCI applications.
On the other hand, microelectrodes may suffer from tissue damage during insertion and be susceptible to signal
degradation due to electrode displacement over time and an immune response against the electrodes. Because of these
issues, penetrating microelectrodes in humans are not yet viable.
A practical alternative is electrocorticography (ECoG), or intracranial/intraoperative EEG (iEEG), which records
synchronized postsynaptic potentials at locations much closer to the cortical surface, as illustrated in Figure 1. Figure 2
illustrates the deployment of ECoG devices.
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Figure 2: Illustration of ECoG devices and deployment in the brain
ECoG has a higher spatial resolution than EEG, a higher signal-to-noise ratio, broader bandwidth, and much less
susceptibility to displacement. Furthermore, ECoG does not penetrate the cortex, does not scar, and can have superior
long-term signal stability recording. Furthermore, advances in integrated circuits that enable high channel count and
wireless operation, ECoG has become an important tool not only for more effective treatment of neurological disorders,
like epilepsy, but also for investigating other types of brain activity across the cortical surface, and its applications to
BCI systems.
ECoG recording provides stable brain activity recording at a mesoscopic spatiotemporal resolution with a large spatial
coverage, or at least a significant area of the brain.
Advanced and miniaturized electrode arrays have reached a spatial resolution of less than 1 mm, enabling monitoring of
large-scale brain activity with greater accuracy. Moreover, wireless implantable microsystems based on flexible
technology can record more closely to the cortical surface while enabling coverage along the natural curvature of the
cortex without penetration as shown in Figure 3.
μECoG
Pia matter
Figure 3: Implantable μECoG on flexible substrate
This ECoG technology, labeled as μECoG, enables even higher spatial resolution than conventional ECoG systems and
is beginning to enable next-generation brain mapping, therapeutic stimulation, and sophisticated BCI systems.
Therefore, recording with modern implementations of ECoG arrays falls into one of two categories:
1) Medium-size brain regions (about 80 mm × 80 mm) at a low spatial resolution of 10 mm electrode spacing for
conventional ECoG.
2) Small brain regions (10 mm × 10 mm) at high spatial resolution (0,5 mm to 1 mm electrode spacing): μECoG.
The present document discusses the design of the wireless interface for the next-generation of μECoG electrode arrays,
illustrated in Figure 4, including recording, stimulation of large regions of the brain at a high spatial resolution, as well
as energy harvesting, power management, and data communications processing. In particular, the present document
focuses on the wireless communication interface, including cybersecurity and privacy protection.
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11 ETSI TR 103 952 V1.1.1 (2025-08)
Energy harvesting & Power
management
Electrodes
Analog Communication
ADC
Frontend interface
Antenna
Stimulation
Figure 4: Schematic diagram of functional blocks for BCI node
Neural data acquisition with a high spatial resolution requires a high channel density of ECoG arrays and, consequently,
smaller electrode size. If the area overhead of the Application-Specific Integrated Circuits (ASICs) should be kept
small, then the area dedicated to the functions illustrated in Figure 4 (amplify and digitize each channel) should reduce
as well.
However, a denser array of amplifiers in the Analog Frontends (AFE) will dissipate more power and generate more
heat. Thus, the power of each AFE is reduced to meet thermal regulatory limits [i.6].
Unfortunately, as the signal power decreases, the Signal-to-Noise Ratio (SNR) also decreases, affecting the
transmission or reception performance requirements for wireless signals.
On the other hand, a higher channel count requires higher communication throughput, increasing the power
consumption and heat dissipation of the communication interface. All these requirements are interrelated and trade-off
with each other.
In addition, there are several circuit designs challenges, like high power Supply Rejection Ratio (PSRR), difficulty in
using external components such as inductors or capacitors. However, these are not addressed in the present document.
Another topic not addressed in the present document is interfaces for stimulation.
5 BCI system considerations
5.1 Energy source
5.1.0 Introduction
The constrained environment around the brain presents an energy source challenge. Indeed, one of the major challenges
on implantable μECoG arrays for BCI nodes is how to power such implantable devices.
Even logistically, it is an issue. For example, the electrode array is placed on the cortex, while the other components are
placed under the scalp, connected with lead wires or better mounted over a titanium plaque that replaced part of the
skull by a craniotomy, eliminating the risk of infection by the lead wires.
Regardless of placement, the constrained environment around the brain presents an energy source challenge. There are
three primary methods for powering an implanted device:
1) use a battery;
2) harvesting energy from the environment;
3) delivering power transcutaneous via a wireless power transmitter.
5.1.1 Battery
Another implantable application such as pacemakers has used batteries extensively. However, it makes sense to use a
battery in a pacemaker, because the required power is relatively small (microwatts) and there is a large physical area
available such that a battery can last 10 years or more.
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In contrast, the power consumption in high-density neural recording and stimulation applications is typically much
larger (milliwatts), and the physical volume available for a large battery is very small, making it unfit.
Another important aspect is that going through surgical re-implantation to replace a battery is unacceptable to most
patients. The medical risks of regular brain surgery and recovery disqualify batteries from being employed in
high-density neural applications.
5.1.2 Energy harvesting
Harvesting energy from ambient sources in local environments has been studied as a potential power source option.
Some scavenging methods include solar cells, biofuel cells, thermoelectric generators, piezoelectric generators, and
ambient RF.
While such approaches are theoretically attractive for implant neural devices, the limited area available near the brain
and the stochastic nature of many energy harvesting sources result in a power source that is too small and too variable to
operate multi-channel neural technologies.
5.1.3 Wireless power transfer
The most promising means to power an implanted device with higher power requirements than pacemakers is to deliver
energy wirelessly via a transcutaneous link, also known as Wireless Power Transfer (WPT).
A transcutaneous link may use light (typically near-infrared light), or acoustics (typically at ultrasound frequencies), or
electromagnetic waves (obviously not in the light range). Each method can deliver from μW to mW of energy power.
However, such delivered energy depends on the geometry, make-up, implant depth, and orientation of the receiving
transducer.
On the other hand, WPT via infrared light has a short penetration depth (around mm), limiting its utility to subcutaneous
implant applications. Ultrasound can penetrate deeper into tissues. However, it is known that ultrasonic energy does not
efficiently penetrate bone, limiting opportunities to directly power cortical implants from outside the skull. Therefore,
the most promising transcutaneous power delivery approach utilizes electromagnetic waves.
Electromagnetic waves in the near- or mid-field is generally considered the most efficient and practical WPT method
for such devices implanted a few cm. Therefore, most conventional designs for implant medical devices operate in the
near-field between 120 MHz and 20 MHz (conductivity and losses in tissue increase at higher frequencies). Moreover,
operating at higher frequencies is constrained by government regulations that limit the amount of dissipated power in
tissues for safety reasons. For example, the FCC sets a Specific Absorption Rate (SAR) of less than 1,6 W/kg in the
USA. For these reasons, conventional transcutaneous power transfer links operate in the low-MHz range.
However, recent advances in small coil antennas show that the antenna's quality factor and radiation resistance increase
with frequency. Thus, μECoG devices with small coils as transducers for WPT would perform better at higher
frequencies. Moreover, the trade-off between frequency of operation and tissue heat-up shows that it is possible to
deliver mW of power to small, implanted WPT antennas under regulatory limits [i.5], [i.6]. Thus, radio electromagnetic
approaches are the primary means to deliver power to implanted ECoG devices.
5.2 Communication interface
5.2.0 Introduction
ECoG devices convey the acquired data to an external controller or Access Point (AP) via a wireless link, where the
information can be processed and monitored for diverse applications from healthcare providers to scientific research.
In contrast to conventional star topologies, an ECoG network supports more traffic (aggregated throughput) from a
number of ECoG devices to the AP in the uplink (device to AP), than the downlink (AP to device). Moreover, the
uplink aggregated data rate may be relatively high (in the order of Mb/s), and subject to stringent power consumption
constraints, especially when the number of electrodes (channels) increase significantly.
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The radio waves for the uplink may be in the near-field or far-field, depending on the application. Assuming the AP is
mounted on goggles, the radio link is in the near-field, while if the AP is at a distance of more than 1 m, the radio link is
in the far-field. SmartBAN was designed to operate in the far field. However, it will not require much modification to
the MAC layer, but would require a new PHY to cope with near-field protocols for communication and WPT at a higher
frequency. ®
The current state-of-the-art of wearable radios, like Bluetooth Low Energy, require more than 1 nJ/bit [i.7], which is
larger than what a typical ECoG device uses. Hence, the design problem is divided into two categories: research
directions in THz spectrum, and a transition phase.
An intermediate transition phase assumes one fusion center mounted on a titanium plaque implanted on the skull. Such
fusion center can connect ECoG devices implanted on the brain without the radio interface via cables. Hence, the
aggregated throughput is centralized in one unit, which is not close to the brain tissue and consequently tolerate a bit
more heat-up.
A candidate is UWB technology. UWB enables low power consumption (around pJ/bit). However, due to government
regulatory constraints, the allocated UWB band varies from country to country, and it is not possible to operate a system
in the range 3,1 GHz to 10 GHz anymore. However, a UWB system design in the high band of UWB may be worth
studying.
5.2.1 Backscatter communication in the near field
Near-field communications operate at distances about one wavelength of the carrier frequency. Hence, it is suitable
when the AP is located on the head, for instance, on virtual reality goggles. In addition, WPT can be integrated easily.
Regarding the WPT for the downlink (AP to device), the backscattering method is one of the most popular.
Backscattering is a technique to transfer power wirelessly from a transmitter to a receiver by modulating the impedance
of the receiver's antenna such that the Electromagnetic Wave (EW) from the transmitter gets more absorbed at the
receiver's antenna or more reflected back to the transmitter. The principle is that the reflected EW from the receiver
modulates the information bits using a switch. In that manner, the power consumption on the ECoG's communication
block is minimal (around pJ/bit), as conventional modulation is not used.
However, the data reception of the reflected EW at the transmitter depends on the power of such backscattered signal,
which in turn depends on the system design and distance between transmitter and receiver. Backscattering is best suited
for applications where low to moderate power transfer is sufficient and energy efficiency and passive operation are
priorities.
Telemetry
WPT
Rx Tx
ECoG AP
Neural
data Carrier wave
RF Carrier
Backscatter
Switch source
modulator
Backscatter
modulated data
Figure 5: Schematic diagram of backscatter communication
5.2.2 ECoG wireless links
The processing, power, and size-constrained ECoG devices lead toward short-range wireless links. Moreover, ECoG
devices typically have a depth of a few cm and high-throughput neural recording. Hence, WPT is a natural choice as the
primary mode of power transfer due to its high efficiency and robustness in comparison to ultrasound and energy
harvesting.
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14 ETSI TR 103 952 V1.1.1 (2025-08)
Thus, over the years, inductive power transfer has been the focus of studies resulting in the development of many
efficient designs and methodologies. Moreover, Near-Field Communication (NFC) using inductive links offers a lower
cost of communication than far-field communication methods, and it has become the primary means of communication.
ECoG devices may be arranged with three configurations: an entire device placed on the cortex, an electrode array
placed on the cortex with an interface on the craniotomy, or placed under the scalp. In these configurations, the location
of such devices results in a challenge for WPT and data communication, besides the constrained power consumption
and asymmetric traffic requirements as illustrated in Figure 6.

Figure 6: Simplified illustration of an ECoG and requirements for WPT and data communication
To have an idea of the throughput requirements, it is assumed an ECoG recording with 1 024-channels with a sampling
rate of 600 samples/s per channel and a data resolution of 10 bits, requires 6,15 Mb/s. Similarly, 64-channels recording
with 10 000 samples/s rate and 10-bit resolution, requires 6,4 Mb/s.
State-of-the-art implant devices transmitting at these data rates typically consume several mW [i.7]. Moreover, the
position of the ECoG's antenna on the brain tissue has an impact on the WPT and communication link requirements.
Figure 7 shows options for implementation:
Power
Power
Implanted Implanted
Controller Controller
system system
Data
Data
b)
a)
Power
Implanted
Controller
system
Data
c)
Figure 7: Radio interfaces for WPT and data communication
• Inductive links for power and data communication are shown in Figure 7a). The links are optimized
independently. Hence, the configuration enables a high data rate while maintaining high power transfer
efficiency. However, this approach requires a more complicated antenna structure and suffers from crosstalk.
• Using different and distinct Radio Frequency (RF) bands as shown in Figure 7b). The scheme can achieve the
required data rate. However, it may require more energy for data communications and increased complexity.
• A simple approach uses a single inductive link to transfer both power and data, as illustrated in Figure 7c).
Typically, backscattering is used for passive data communication.
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5.3 Body Tera Hertz networks
5.3.0 Introduction
Covering significant portions of the brain with an adequate sampling resolution will require a high throughput to be
handled adequately for one central unit with significant processing and power constraints.
Therefore, researching the use of THz technology for WPT and data communication is due to the recent advances in
the field.
Figure 8 shows classifications of the THz band. From the RF spectrum perspective, THz frequencies start at 100 GHz
(0,1 THz), while from an optical communication perspective, the THz band is below 10 THz (the far-infrared
spectrum). Most publications are within this spectrum range.

Figure 8: THz frequency bands
Some medical applications already use the THz band, such as in oncology and medical imaging. Due to the short-range
connectivity, small form factor, and wide available bandwidth, the THz band enables connectivity of in-body wireless
networks. Moreover, THz radiation is relatively safe on biological tissues [i.8]. Hence, the THz spectrum can improve
the performance of existing Body Area Networks, enabling various medical applications. In particular, a THz-based
network can operate inside the human body in real-time for health monitoring and medical implant communication.
Therefore, THz technology is very attractive for the next generation of BCI.
NOTE: THz systems have been associated with the operation of nano-machines and interaction with so-called
molecular communications. However, the present document does not consider these applications, but
rather the potential use of radio interfaces for WPT and communication of high throughput data in a small
form factor and efficiency, which are closer to practical implementations.
Indeed, the proposed BCI use case and the use of THz bands may be seen as part of the key enablers for 6G next
generation of wireless communications, as it enables E-health, besides of fully merged virtual worlds, mixed reality and
immersive events, like sports, entertainment, gaming, work, social networks.

Figure 9: THz band from a 6G perspective
ETSI
16 ETSI TR 103 952 V1.1.1 (2025-08)
5.3.1 Enhancements to channel modeling
THz technologies still face various challenges. Among others, the propagation characteristics of THz channels.
Contributions describing THz channel measurements and modeling indicate [i.9]:
• Path loss and shadowing (large-scale) parameters in THz bands exhibit specific features compared to
frequencies below 100 GHz. THz waves suffer much higher free space path loss when compared to mm-wave
and lower frequencies. Moreover, its properties of penetration, diffraction, and scattering are different.
• Similarly, small-scale (fast-fading) parameters are also unique to the THz band [i.2].
• Furthermore, molecular absorption and the effect of changing ambient conditions, like humidity, cannot be
neglected in the case of THz channels [i.2].
THz wavelengths are small compared to mm-wave wavelengths, resulting in a reduction of the effective aperture
antenna. Hence, a THz antenna array would be attractive to implement in the uplink receiver:
• However, this means that the Rayleigh distance (the conventional boundary between the near field and far
field) may be larger than the communication range, and then spherical wave modeling is required [i.2].
• On another hand, the spatial non-stationarity (antenna elements at different spatial positions may capture
different multipath characteristics) may need to be modeled for the THz bands as the antenna array aperture
may be larger relative to the wavelength [i.2].
5.3.2 Electronic and photonic technologies
5.3.2.0 Introduction
THz bands are promising candidates for
...