# Demonstration of Safe Electromagnetic Radiation Emitted by 5G Active Antenna
Systems

Sumit Kumar, Chandan Kumar Sheemar, Abdelrahman Astro, Jorge Querol, Symeon
Chatzinotas

Email:{sumit.kumar, chandankumar.sheemar
<EMAIL_ADDRESS>Interdisciplinary Centre for
Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg

###### Abstract

The careful planning and safe deployment of 5G technologies will bring
enormous benefits to society and economy. Higher frequency, beamforming and
small-cells are key technologies that will provide unmatched throughput and
seamless connectivity to the 5G users. Superficial knowledge of these
technologies has raised concerns among the general public about the harmful
effects of radiation. Several standardization bodies are active to put limits
on the emissions which are based on a defined set of radiation measurement
methodologies. However, due to the peculiarity of 5G such as dynamicity of the
beams, network densification, Time Division Duplexing mode of operation, etc,
using existing EMF measurement methods may provide inaccurate results. In this
context, we discuss our experimental studies aimed towards the measurement of
radiation caused by beam-based transmissions from 5G base-station equipped
with an Active Antenna System(AAS). We elaborate on the shortcomings of
current measurement methodologies and address several open questions. Next, we
demonstrate that using user-specific downlink beamforming, not only better
performance is achieved compared to non-beamformed downlink, but also the
radiation in the vicinity of the intended user is significantly decreased.
Further, we show that under weak reception conditions, an uplink transmission
can cause significantly high radiation in the vicinity of the user-equipment.
We believe that our work will help in clearing several misleading concepts
about the 5G EMF radiation effects. We conclude the work by providing
guidelines to improve the methodology of EMF measurement by considering the
spatio-temporal dynamicity of the 5G transmission.

###### Index Terms:

Electromagnetic Radiation, 5G-NR, Active Antenna Systems (AAS)

##  I Introduction

Fifth-generation (5G) New-Radio (NR) mobile networks have become the
foundation for industrial transformation in terms of digitalization and
advanced communication systems [1]. Thanks to the technologies such as Massive
MIMO, Millimeter Wave (mmWave), Beamforming, D2D, and Ultra-Dense Networks,
5G-NR can support higher data rates (upto $10~{}$Gbps) and significantly lower
latency(maximum $10~{}$ms) than the previous generation 4G Long Term Evolution
(LTE)[2, 3]. The dense deployment of the 5G base stations is crucial for
achieving the ”everywhere/anytime” connectivity promised by 5G. This
deployment will be on top of the existing 2G/3G/4G deployments, which are
already operational. Thus, foreseeing such an increased number of active
radiating nodes, a large part of the population is concerned about the
potential health impacts due to increased electromagnetic field (EMF) exposure
[4, 5].

One of the particular features of 5G-NR is the application of Active Antenna
Systems (AASs) which creates and manages user-specific beams. This feature
helps to overcome the path loss for synchronization signals and data channels.
AAS is the key enabler for the technologies such as massive MIMO, mmWave,
beamforming, beam-steering [3]. In AAS, active components from the Remote
Radio Unit (RRU) are integrated with the passive antenna[6]. This allows AAS
to both amplify and convert radio frequency waves in addition to signal
radiation and reception. Moreover, an integrated RRU facilitates focusing the
power in a certain direction and creates Field Strength Hotspots in the main
lobes of the beams, resulting in increased SNR in the intended direction.
However, such Field Strength Hotspots has created concern among the general
public over increased radiation.

Some of the concerns from the general public include the risk of cancer,
increased sensitivity to radiation, and oxidative stress in the cells[7, 8,
9]. Such doubts and concerns can delay the deployment of 5G in some countries,
leading to unfavorable economic impacts[10]. Standardization bodies such as
International Commission on Non-Ionizing Radiation Protection (ICNIRP),
International Electrotechnical Commission (IEC), and International
Telecommunication Union (ITU), based on various measurement campaigns,
studies, and scientific efforts, define the limits of EMF radiation. They
impose that the highest possible power and gain values are used when
calculating the RF-EMF exposure to ensure conservative results. Additionally,
countries can follow the guidelines or even set stricter (more conservative)
limits on radiation. However, such approaches can have a direct impact on the
system capacity, and coverage [11]. A conservative limit imposed by the
countries can restrict the buildout of 5G network capacity. Besides, the
current EMF measurement methodologies could be challenging due to the spatial
and temporal dynamics of the beams as the methodologies were developed for
channels and signals consisting of always-on pilots and non-beamformed
signals.

In a typical operation of 5G, the signals and channels are beam-formed and the
beams could be dynamic in nature, i.e., the beamwidth can vary and the beams
may move to focus on the mobile UE, for example. Therefore, it is crucial to
analyze the limitations of the current EMF assessment methodologies, study the
peculiarities of 5G-NR, which pose a challenge to the current methods and
identify the gaps and propose appropriate adaptations.

###  I-A Previous Works

The research for EMF exposure assessment in 5G cellular networks is ongoing,
and several new methods are proposed [12, 13, 14, 15, 16, 17, 18]. In [14],
the authors conducted a study to investigate the maximum transmitted power and
maximum Effective Isotropic Radiated Power (EIRP) to comply with all major RF-
EMF exposure standards. The power density was evaluated, and the spatial peak
power density was assessed using a minimum spatial sampling density of four
samples per wavelength. In [15], the impact of the maximum radiated power from
a device used near the human body is investigated. Assessments were made using
numerical simulations with the commercial electromagnetic solver FEKO. In
[16], the transmitted power of the uplink slots and the synchronization signal
reference signal received power (SS-RSRP) from user equipment (UE) were
measured in Seoul, Korea, to evaluate the EMF exposure. The power samples were
averaged over a $1$s duration, and the measurement results showed that the
time-average level, when exposed to a beam sweep of the base stations, was
less than $5~{}\mu W/m^{2}$. In [17], EMF exposure for several 5G base
stations was measured in Australia. The base stations used the massive MIMO
antennas with beamforming to optimize the signal strength at the user’s
device, and the maximum time-averaged power per beam direction was found to be
well below the theoretical maximum. In [18], a method for power reduction
estimation in realistic scenarios with 5G AAS to enable a preliminary fast
estimation of the EMF exposure in 5G cells is proposed.

###  I-B Main Contributions

In this context of EMF measurement and concerns from the general public, we
discuss the studies and experimentation conducted with the aim to showcase the
benefits of 5G from a scientific point of view and to expose some of the
misconceptions related to AAS technology. In particular, our work focuses on
demonstrating that by using beamforming in an AAS, the SNR at the intended
user is improved and at the same time EMF level in the vicinity of the
intended user reduces significantly. Our main contributions to this work are
summarized as follows:

  * •

We have studied the peculiarities of 5G AAS, on both the Radio Access Network
and Network layer, which makes the conventional EMF measurement methods less
efficient. We have identified the issues with conventional EMF measurement
methodology while measuring EMF from a 5G AAS.

  * •

Further, we conducted field experiments to validate the fact that a 5G AAS is
capable of not only improving the SNR at the intended user but can also
reducing the EMF radiation in the vicinity of the intended user. Moreover, we
also studied the uplink traffic, which has gained lesser attention compared to
downlink traffic, however, from an EMF radiation point of view, it is more
critical to analyze.

  * •

Finally, we discuss the limitation of the exiting EMF assessment methods and
why they cannot be used for the higher frequency bands. To overcome the
drawbacks, we discuss a novel research direction which is particularly suited
for mmWave and beyond.

_Paper Organization:_ The rest of this paper is organized as follows. Section-
II discusses the features of 5G-NR which are creating concerns over EMF
radiation. Section-III discusses the measurement challenges of conventional
EMF measurement methodologies and identifies the gaps. Section-IV details the
field experiments conducted to validate some of the methods discussed in
Section-III for downlink and uplink. Next, in Section-V, we discuss open
challenges in 5G EMF measurement especially due to the spatio-temporal
dynamicity of 5G transmissions and provide guidelines for the development of
EMF measurement methodology. Finally, Section-VI summarizes the paper with
concluding remarks on future works.

##  II 5G-NR EMF Concerns

Although 5G-NR still uses OFDM for uplink and downlink, it has gone through
significant changes on Radio Access Network (RAN); especially how the
waveforms are transmitted/received from the gNBs. Apart from different
frequency bands (FR1 and FR2), wider bandwidths ($100$ MHz for FR1 and $400$
MHz for FR2) and Time Division Duplexing (TDD) are some of the peculiarities
in 5G which are in contrast to the RAN of 4G LTE. Discussion on such
differences between 4G and 5G is critical from an EMF radiation and assessment
point of view. In this section, we focus on the specific features of 5G-NR,
which are creating concern among the general public.

###  II-A Massive MIMO

Massive MIMO is one of the most important 5G technologies [19]. It contains a
large number of antenna elements on the base-station side. Through digital
and/or analog control of the RF chains, one or many user-centric sharp beams
can be created and the beams can be further adapted dynamically based on the
user movement and requirements. A controller is required for such operation.
The controller can be either collocated with the antenna units or connected
via Common Public Radio Interface (CPRI). The former constitutes an Active
Antenna System (AAS) which has become the dominant configuration in the
ongoing deployment of 5G base stations.

Superficially, one can correspond a large number of antenna elements to an
increased amount of radiated power which in turn can strengthen the myth about
higher radiation from a 5G base station. In fact, the maximum transmitted
power by a 5G BS can reach up to $200$Watts which is almost double the
corresponding value for a 4G BS[12]. This increase in power triggers the
population’s concern about potential health risks. However, scientifically
this is not the fact. A Massive MIMO system aims to project focused power
towards user locations and in this process, compared to a sectoral antenna,
less power per antenna element is required in order to achieve the same SNR a
sectoral-antenna would have provided [19]. This is possible because the
antenna array can concentrate the input energy in the desired direction and
minimizes the radiation in the undesired direction, thus less input energy is
required per antenna element.

###  II-B Beamformed Channels and Signals

5G inherently uses beamforming using AAS as discussed in section-II-A. Not
only the user-centric data(payload and control) is beamformed, but the
synchronization signals, which are used to set up the time-frequency
alignment, are also transmitted as beams. The former is called User-Specific
Beamforming and is done for PDSCH and PDCCH while the latter is called
Synchronization Signal Blocks (SSBs) Beam-Sweeping which is done for PSS, SSS,
and PBCH. User-specific beams could be narrower than the beams used for SSBs.
Besides, the beams can be parsed in both azimuth and elevation with the
application of an AAS.

Such beam-based operations are also one of the causes of public concerns
regarding radiation from the 5G base station. A crude perception of the beam,
among the general public is seen as a focussed beam of energy towards them,
and hence beams are visualized as a cause of concern. However, the reality is
different. For a desired SNR at the intended user, the transmit power from a
sectoral antenna is higher compared to an antenna array with high gain and
directivity. Besides, the radiation from the sectoral antenna not only reaches
the intended user but also gets spread in the vicinity unnecessarily. In
contrast, the antenna array elements inside the AAS, require less input power
per antenna element for a given target SNR at the intended user and at the
same time minimize the spill of radiation in the vicinity of the intended
user.

###  II-C mmWave and network densification

Millimeter-wave (mmWave) frequency bands contain large signal bandwidth and
are very promising for 5G to reach a data rate as high as $10$Gb/s. Mm-Wave
provides a much larger bandwidth, higher throughput, faster data rate, and
capacity compared with, 3G, and 4G. Hence, 5G networks are also planned to be
deployed in FR2 (for higher bandwidth use-cases) apart from FR1 ( more
favorable for coverage). However, the benefits of mmWave come at the cost of
reduced coverage. mmWave cannot travel as far as the frequencies used in
2G/3G/4G can travel. To cope-up with this, either beamforming is done on the
mmWave carrier (discussed in section-II-A) and/or the base stations have to be
placed densely. The latter is called network densification and this has raised
concern among the general public where network densification is being
perceived as radiation densification.

###  II-D small-cells

Among one of the promises of 5G is a reliable and ultra-low latency
connection. For this purpose it is planned to densify the deployment of 5G
base-stations which is in contrast to 3G and 4G where the distance between the
towers was in order of KMs. As the distance between the users and the nearest
cell shrinks this has increased the general public’s perception of potential
health impacts. However, in reality, and unlikely the common perception,
network densification can significantly reduce the average EMF exposure for a
given required rate [20, 21]. In fact, in a small cell, the cell coverage area
is smaller for networks with higher BS density, requiring lower transmitted
power. In fact, 3G and 4G with distant base-stations, radiate more power in
order to cover a large chunk of area. This also leads to higher exposure of
radiation at the cell egde. In contrast, in a small-cell there is a
homogeneous distribution of power over the coverage area leading to uniform
distribution of EMF. Densifying the network with small-cells in fact reduces
the average EMF exposure over the coverage area compared to the sparsely
deployed legacy networks as reported in [20, 22].

###  II-E High Uplink Traffic

Traffic patterns are changing. Applications such as online gaming, cloud
storage, personal broadcasting are dominated by uplink traffic. TDD based
operations are more flexible compared to FDD in terms of spectrum usage. That
is why TDD has become the dominant deployment mode in 5G. TDD uses the same
frequency, though different time slots for uplink and downlink traffic. These
time slots are configurable due to which the bandwidth demand of uplink or
downlink can be catered dynamically.

A rise in such uplink traffic is a genuine concern from the EMF point of view,
especially when the RSSI at the UE is poor [23].

##  III 5G-NR EMF Measurement Challenges

5G is definitely more challenging when it comes to measuring the EMF
radiation. For classic base station antennas with static antenna radiation
patterns, the RF EMF evaluations are relatively straightforward. This is
completely in contrast to how 5G is designed and operated. Besides, the
measurement methodologies and the maximum level set for EMF radiation vary
from country to country. Regulations typically require that the highest
possible power and gain values are used when calculating the RF-EMF exposure
to ensure conservative results. In this section, we will discuss the peculiar
features of 5G which can make the measurement of EMF difficult in comparison
to 2G/3G/4G. Such features not only include the significantly different frame
structure, Massive MIMO, and beam-based operations in 5G-NR but also the way
in which 5G is operated on a network level. A majority of the challenges come
because some of the transmitter parameters are not known apriori.

###  III-A No Always-On Signal

The basic principle of assessing the EMF is to measure the power received from
a constant radio frequency source, which is typically a pilot signal coming
from the base station and to apply a proper extrapolation factor. This kind of
approach is standardized for 2G, 3G, and 4G where always-on reference signals
were used as reference signals for precise channel estimation and cell-
specific synchronization. However, this is not straightforward for 5G, because
there is not always-on signal in 5G. Besides, 5G NR is a completely new
approach regarding cell-specific signals [23]. Unlike LTE, the reference
signals in 5G (DMRS, PTRS, SRS, and CSI-RS) are transmitted only when
necessary and not spread over the entire spectrum. In 5G NR only a minimum
amount of cell-specific signals are broadcasted that can be measured by a
calibrated measurement receiver. Rest of the signals are specific to UE and
their appearance in the frequency and time domain depends on the data traffic.
The only always-on signal is the synchronization signal block (SSB) which is
sparse in both time and frequency. Thus it becomes difficult to extrapolate
the power measured from SSB to the traffic region of the resource gird.
Further, the power gain offset between SSS and PDSCH is required for
extrapolation which can only be obtained with an active connection between the
gNB and the scanner [24, 25]. Besides, since the SSB beams are narrower,
several such beams (with a unique directional index) are transmitted
periodically to cover the entire sector. It is difficult to get enough dwell
time to measure, especially in the case of mmWave where the number of such
beams could be very high.

Figure 1: 5G-NR Synchronization Signal Block (PSS¡ SSS and PBCH) and PDSCH.
SSB is restricted only to 240 subcarriersin frequency domain and only 4 OFDM
symbols in the time domain.

###  III-B Traffic load distribution

Since SSB is used for EMF measurement, it is important to be aware of the
traffic load distribution in the resource grid. It is not straightforward to
access the traffic load distribution and hence the power from the traffic
channel. The reason being 5G is packet-switched, thus traffic channel power is
only measurable when there is active traffic. Without the knowledge of such
distribution, the linear spectral extrapolation from SSB to total channel
bandwidth power does not work correctly. There could be the following three
cases (a pictorial representation is shown in Figure-2):

  1. (a)

Cell is fully loaded, i.e., traffic channel power = SSB power : In this case,
a linear spectral extrapolation from SSB will work correctly, EMF value
derived from SS-RSRP will correctly represent the real power.

  2. (b)

Cell is partially loaded or traffic channel power ¡ SSB power :  A linear
spectral extrapolation from SSB will result in an EMF that is higher than the
real value.

  3. (c)

Cell is fully loaded and/or traffic channel power ¿ SSB power :  A linear
spectral extrapolation from SSB will result in lower than the real value.

Figure 2: (a) A fully loaded cell where traffic channel power is the same as
SSB power; (b) A partially loaded cell where traffic channel power is less
than SSB power (c) A fully loaded cell where traffic channel power is more
than SSB power

###  III-C Apriori Knowledge of Antenna Beam Pattern

Once the process of beam sweeping is completed and traffic flow is started
between the gNB and UE, a UE-specific beam is created by the gNB towards the
UE. The width of this beam is narrower and the power content of this beam is
higher compared to the SSB beam. To measure the EMF content in this traffic
beam, it is important to have apriori information about the antenna pattern
and maximum transmit power. Such information helps for the proper placement of
the isotropic EMF measurement antenna during EMF measurement from the user-
specific beam. Ideally, the isotropic should be placed at the center of the
beam. Such information could be difficult to obtain in practice. A pictorial
description of the same is shown in Figure-3.

Figure 3: Beam sweeping of SSBs in a gNB and user-specific beamforming. It is
important to have apriori information about the gNB antenna pattern for
placing the isotropic antenna at an appropriate location in order to minimize
the EMF measurement error. While measuring the EMF caused by traffic channel
(user-specific beam) Position-B is desirable to get the accurate EMF.

Another challenge that can be encountered in practice is the directional and
power mismatch between the beam used for SSB and the beam used for traffic
channel(PDSCH and PDCCH). Dynamicity of the UE-specific beam (when the
environment is changing, UE is moving, etc) makes the measurement further
complicated in this situation. Three different cases may arise (a pictorial
representation is shown in Figure-4).

  1. (a)

Traffic beam has the same power and same direction as SSB beam:  In this case
the linear extrapolation of the EMF measured from SSB provides a realistic EMF
value of the traffic beam.

  2. (b)

Traffic beam has less power and direction not aligned with the SSB beam:  In
this case the linear extrapolation of the EMF measured from SSB will result in
a higher than actual EMF value of traffic beam.

  3. (c)

Traffic beam has more power and direction not aligned with the SSB beam:  In
this case the linear extrapolation of the EMF measured from SSB will result in
a lower than actual EMF value of traffic beam.

Figure 4: (a)Power and direction of traffic and SSB beam are same – linear
extrapolation on the power of SSB beam provides correct result (b),(c) Power
and direction of traffic beam are different than SSB beam – linear
extrapolation on the power of SSB beam may provide incorrect result.

###  III-D Uplink-Downlink Relation Factor

TDD mode of operation is dominant in the current 5G deployment. The
configuration of Downlink (DL) and Uplink (UL) slots could be different
depending on which configuration has been agreed on by the operators. While
measuring the EMF from the transmission coming from gNB, it is important to
know the periodicity of DL and UL slots. Without such knowledge, the probe may
log the cumulative EMF of both the DL and UL transmissions. A gated
measurement could be required which triggers to measure of the power only when
there is DL transmission. A pictorial depiction is shown in Figure-5. This is
different from FDD where the probe can be simply tuned to the DL frequency for
DL EMF measurement.

Figure 5: In the TDD mode of operation, it is important to perform a gated
measurement to measure DL specific EMF.

##  IV Field Experiments and Observations

###  IV-A Field Experiments

Concerning the radiation caused by gNB, we are interested in the radiated far-
field region of the active antenna and for that either the measurement of
electric field strength (E, unit V/m2) or magnetic field strength (H, unit
A/m) is sufficient. Optionally power density (unit W/m2) is also used to
quantify the radiation. We have chosen to work with electric field strength
due to simplicity in measurement with the instruments we have, nonetheless,
power density can also be used. To measure the EMF values, we have used Wave
control SMP2 which is a broadband EMF measurement meter. This comprised an
electric field isotropic probe, connected to the main control unit which
records the electric field values for the band encompassing DC to 60 GHz.

In this section, we will discuss the EMF measurement experiments which we
performed to validate some of the discussions which we did in section-II and
section-III. We did several experiments to measure the EMF at various
distances from the UE during both DL and UL transmission. In all the
experiments we perform a 10-second moving average for the entire duration of
the measurement (for ruling out the outliers) and log the maximum and RMS
value of the EMF in V/m2.

###  IV-B Downlink EMF Measurement at UE from beamformed traffic

####  IV-B1 Experiment Objective

In this experiment our objective is to measure and analyze the worst case (a)
EMF observed at the UE and (b) EMF observed in the vicinity of the UE caused
by DL waveform transmitted from a gNB which is equipped with an AAS. For both
the EMF measurements (a) and (b) we compare two scenarios where in the first
one, the gNB is equipped with an AAS, i.e., capable of beamforming, while in
the second case, the gNB will not use an AAS. In both scenarios, the UE is not
capable of performing any beamforming. Next, we detail the experimental setup.

####  IV-B2 Experiment Set-up

For these experiments, we have used emulated gNB and emulated UE. This is a
unidirectional connection where only the gNB makes a transmission beam towards
the UE while the UE simply decodes the transmission from UE. To emulate the
gNB we have used a commercial 5G vector signal generator from Rhode & Schwartz
(SMBV100B) which is capable of generating standard-compliant 5G-NR TDD
waveforms. Our emulated gNB using a commercial 5G signal generator cannot
perform beam sweeping, i.e., multiple SSB in different directions. Hence, to
emulate an active-antenna gNB system that creates a dedicated beam towards the
UE for traffic and data channels, we used a high directive horn antenna at the
NBA. This is not an accurate representation, however, it closely emulates the
situation of beam correspondence. Beam-correspondence is the step where a
user-specific traffic beam is created from the gNB and the actual downlink
traffic proceeds. To compare, we also used a low directive antenna at gNB
which emulates conventional wide-angled transmission from the gNB. Next, to
emulate the UE, we have used a commercial 5G signal analyzer from Rhode &
Schwartz (FSV3000) capable of decoding the test waveforms from the gNB. On the
UE side, we are simply using an antenna with low directivity which is a valid
assumption. The transmission frequency for our experiment is $3.775$ GHz for
which we have the license from Institut Luxembourgeois de Régulation(ILR) for
experimental work. To measure the EMF, we have used a broadband-EMF meter and
an isotropic probe. Our measurement was dedicated to a single transmitter
(gNB) which was under our control, hence, we decided to use broadband
measurement. The probe was mounted on a wooden tripod at a height of $1.5$m
and recordings were time-averaged for 6 minutes. Although the latest ICNIRP
guideline has a stated duration of 30 minutes for the measurement of EMF[26],
in our case (a) the gNB is fully under our control (b) there is only one UE
that is served by the gNB (c) the environment is static and no other 5G
transmitters nearby. Hence, we decided to use 6 minutes of dwell time for our
measurements. A pictorial representation of the emulated gNB and UE is shown
in 6 and Table-I. Next, we will discuss the experimental methodology.

####  IV-B3 Experiment Methodology

  * •

Step-1: We connect the gNB with a low-directive antenna and connect the UE
with a similar low-directive antenna

  * •

Step-2: A known waveform is transmitted with a fixed power TxP from the gNB
towards UE and the PDSCH Error Vector Magnitude(EVM) is recorded for that TxP.
We start with a transmission bandwidth of 5 MHz.

  * •

Step-3: For the known TxP and EVM, the EMF is measured (Maximum and RMS value)
at three different locations:

    1. (a)

$10$cm near to the UE: This represents the EMF observed by a user which is
very near to the human body (for example head).

    2. (b)

$150$cm away from UE: This represents the EMF observed by a user who is in the
vicinity of the human body (for example a person talking on speakerphone).

    3. (c)

$400$cm away from the UE: This represents the EMF observed by a UE which is
far away from the human body (for example a person using a smartphone as a
wifi hotspot).

  * •

Step-4: We connect the high-directive horn antenna to the gNB and keep the
rest of the set-up intact.

  * •

Step-5: Now we perform the again steps-2 and step-3 and log the EMF values at
different locations as mentioned in step-4.

  * •

Step-6: We repeat step-2, 3, 4 and 5 for $10$, $20$ and $50$ MHz of
transmission bandwidth.

TABLE I:  Details of equipment and experiment set-up as discussed in section-IV-B3 Parameters |  Values
---|---
gNB |  R&S SMBV100b
nrUE |  R&S FSV3000
Frequency |  3775 MHz
Bandwidth |  5, 10, 20, 50 MHz
gNB Antenna |  WR-229, 3.3-4.9 GHz, 20dBi, Horizontal HPBW $16.7^{\circ}$, Vertical HPBW $17.1^{\circ}$
nrUE Antenna |  W36-CP-9, 3.4-3.8 GHz, 10dBi, Horizontal HPBW $50^{\circ}$, Vertical HPBW $50^{\circ}$
Duplex Mode |  TDD
Broadband EMF meter |  Wavecontrol SMP2 DC-60GHz, WPF-40 Field Probe 1MHz - 40GHz
Figure 6: Experiment set-up for downlink EMF measurement as discussed in section-IV-B2 TABLE II: Downlink EMF measurement for experiments in section-IV-B |  Transmission Mode |  gNB Antenna Type |  TxP (dBm) |  Distance of probe from UE (cm) |  PDSCH EVM (%) |  Max-EMF (V/m) |  RMS-EMF (V/m)
---|---|---|---|---|---|---|---
R1.1 |  |  Low-directive |  14.7 |  10 |  3.75 |  1.64 |  1.214
R1.2 |  |  Low-directive |  14.7 |  150 |  3.75 |  1.69 |  1.256
R1.3 |  Bandwidth 5MHz, SCS 15KHz, TDD |  Low-directive |  14.7 |  400 |  3.75 |  1.62 |  1.272
R2.1 |  |  Low-directive |  14.7 |  10 |  3.75 |  1.64 |  1.322
R2.2 |  |  Low-directive |  14.7 |  150 |  3.75 |  2.16 |  1.366
R2.3 |  Bandwidth 10MHz, SCS 15KHz, TDD |  Low-directive |  14.7 |  400 |  3.75 |  2.17 |  1.31
R3.1 |  |  Low-directive |  14.7 |  10 |  4.5 |  2.28 |  1.803
R3.2 |  |  Low-directive |  14.7 |  150 |  4.5 |  2.31 |  1.798
R3.3 |  Bandwidth 20MHz, SCS 15KHz, TDD |  Low-directive |  14.7 |  400 |  4.5 |  2.27 |  1.795
R4.1 |  |  Low-directive |  14.7 |  10 |  6.3 |  2.45 |  2.11
R4.2 |  |  Low-directive |  14.7 |  150 |  6.3 |  2.39 |  2.05
R4.3 |  Bandwidth 50MHz, SCS 15KHz, TDD |  Low-directive |  14.7 |  400 |  6.3 |  2.41 |  2.01
R5.1 |  |  High-directive Horn |  9.8 |  10 |  0.42 |  1.58 |  1.114
R5.2 |  |  High-directive Horn |  9.8 |  150 |  0.42 |  1.01 |  0.93
R5.3 |  Bandwidth 5MHz, SCS 15KHz, TDD |  High-directive Horn |  9.8 |  400 |  0.42 |  0.81 |  0.73
R6.1 |  |  High-directive Horn |  9.8 |  10 |  0.5 |  2.1 |  1.21
R6.2 |  |  High-directive Horn |  9.8 |  150 |  0.5 |  1.27 |  0.95
R6.3 |  Bandwidth 10MHz, SCS 15KHz, TDD |  High-directive Horn |  9.8 |  400 |  0.5 |  1.16 |  0.76
R7.1 |  |  High-directive Horn |  9.8 |  10 |  0.63 |  2.15 |  1.6
R7.2 |  |  High-directive Horn |  9.8 |  150 |  0.63 |  1.33 |  1.31
R7.3 |  Bandwidth 20MHz, SCS 15KHz, TDD |  High-directive Horn |  9.8 |  400 |  0.63 |  1.1 |  1.05
R8.1 |  |  High-directive Horn |  9.9 |  10 |  1.26 |  2.33 |  1.85
R8.2 |  |  High-directive Horn |  9.9 |  150 |  1.26 |  1.42 |  1.4
R8.3 |  Bandwidth 50MHz, SCS 15KHz, TDD |  High-directive Horn |  9.9 |  400 |  1.26 |  1.17 |  1.1

####  IV-B4 Observations

The measurements are listed in Table-II and from that we observe the
following:

  1. 1.

For a given transmit power TxP:

    1. (a)

For the low-directive antenna, the EMF is almost the same for the three
locations a, b and c. This is observed for all the transmission modes.

    2. (b)

For the high-directive horn antenna, the EMF decreases as the probe is moved
from a$\rightarrow$b$\rightarrow$c. This is also observed for all the
transmission modes.

  2. 2.

The behavior above is consistent with respect to the increase of the
transmission bandwidth. As the transmission bandwidth is increased from
5$\rightarrow$10$\rightarrow$20$\rightarrow$50 MHz, the EMF increases,
however, it decreases as the probe is moved away from the UE.

  3. 3.

Using high-directive horn antenna at the gNB, lower EVM (compared to the low-
directive antenna at the gNB) is achieved at the UE even with a lower transmit
power TxP. For example: In R1.1, 1.2, and 1.3 the EVM is 3.75 at a TxP of 14.7
dBm, while for its counterparts in R5.1, 5.2, and 5.3 the EVM is 0.42 at TxP
of 9.8 dBm.

  4. 4.

From 1(a) and 1(b), it can be said that when a gNB makes a UE-specific beam,
the EMF in the vicinity of the UE is reduced.

  5. 5.

Further, from 2, it can be said that the SNR of the signal can be improved
with UE-specific beamforming and at the same time, the EMF in the vicinity of
the UE is decreased.

###  IV-C Uplink EMF

####  IV-C1 Experiment Objective

In the section-II-E, we discussed how the traffic pattern has changed, and now
the uplink traffic is comparable to downlink traffic. The objective of this
experiment is to verify the fact that UE may experience very high EMF during
audio and video calls when the RSRP is poor. We do not focus on a particular
operator, hence, we use the broadband meter for the uplink measurement.

####  IV-C2 Experiment Set-up

For this experiment, we have used a COTS smartphone as our UE which is
connected to a 5G base station. During the uplink traffic between COTS UE and
the gNB, the isotropic probe is placed at a height of 1.5 meters from the
ground on a tripod. A pictorial representation is shown in Figure-7. For
measuring the RSRP in the COTS UE, we have used Qualipoc[27].

Figure 7: Uplink EMF measurement very near to the UE and its vicinity

####  IV-C3 Experiment Methodology

The experiment was conducted in the following steps:

  * •

Step-1: The UE was connected to a gNB under low RSRP conditions. For our in-
lab measurement, the UE showed an RSRP fluctuating between -111 dBm to -100
dBm as shown by Qualipoc.

  * •

Step-2: The isotropic probe was placed at a distance of 10 cm from the UE.

  * •

Step-3: Traffic was initiated between UE and gNB through audio and video
calls. The EMF meter was turned on to measure 6 mins.

  * •

Step-4: Step-2 was repeated with the probe placed at a distance of 150 cm from
the UE.

  * •

Step-5: The set-up was relocated to an area with better RSRP and steps-1,2,3,4
were repeated.

In all the experiments above, time averaging was performed to eliminate the
floating traffic error in 5G, i.e., assuming that the cell is loaded with
traffic. Further, each mobile phone is equipped with an Automatic Power
Control system that adjusts the output power level to the minimum required
value necessary to establish a connection with a base station. Besides, the UE
goes thru DRX and TDD (duty cycle), hence, time averaging was necessary.

TABLE III: Uplink EMF measurement for experiments in section-IV-C | RSRP (dBm) | -111 | -96
---|---|---|---
| Distance of probe from UE (cm) | 10 | 150 | 10 | 150
Case-1 | Max / RMS EMF at no activity (V/m) | 11.57 / 5.547 | 3.32/1.692 | 5.62 / 2.447 | 1.75/0.991
Case-2 | Max / RMS EMF at audio traffic (V/m) | 19.44 / 5.899 | 3.06/1.676 | 6.99 / 2.518 | 1.88/1.011
Case-3 | Max / RMS EMF at video traffic (V/m) | 21.22 / 11.33 | 3.98/1.881 | 7.12 / 3.162 | 2.01/1.011
Figure 8: Screenshot of uplink EMF measurement from Wavecontrol-SMP2 during
the audio call. The X-axis represents time while Y-axis represents EMF(V/m).
Spikes in the EMF measurement can be seen as the user speaks while keeping the
UE near to the head. Figure 9: Screenshot of uplink EMF measurement from
Wavecontrol-SMP2 during a video call. The X-axis represents time while Y-axis
represents EMF(V/m). Spikes in the EMF measurement can be seen as the user
makes movement neat the UE camera while keeping the UE near to head. The area
enclosed in the black rectangle represents an elevated EMF level when the user
makes activity near the UE camera, the area enclosed in the green rectangle
represents an elevated EMF level when a user at makes activity near the gNB
camera, and the area enclosed in blue rectangle represents EMF level when none
of the users make any activity near their respective cameras.

####  IV-C4 Observations

The EMF measurement from the experiments is listed in Table-III. We observe
the following:

  1. 1.

When the RSRP is weak at the UE (due to a large distance from the gNB or the
user is inside a building or a car), the UE transmits at a higher power which
leads to a high EMF experience by the user. This behavior is consistent in all
three cases. Even during no activity, there is an exchange of messages between
the UE and gNB, which leads to excessive EMF measurement during case-1, i.e.,
No Activity. Maximum and RMS EMF in such cases exceed the defined limit of
3V/m [28].

  2. 2.

Probe when placed near to UE (10 cm) experiences higher EMF when placed far
(150 cm) from the UE. This behavior is also consistent in all three cases.
Thus it can be said that using the smartphone away from the body is relatively
safe.

  3. 3.

Furthermore, two interesting phenomena were observed while placing audio and
video calls:

     * •

When the user at the UE speaks during an audio call, there are sudden jumps in
the EMF which is shown in Figure-8. This can be explained by the fact that
when the user speaks, uplink traffic is generated. It is also observed that
EMF does not exceed when there is no voice activity from the UE side. This
behavior is observed only when the UE is placed near the probe. At a distance
far from the probe, such spikes are not observed.

     * •

When the user at the UE makes an activity during a video call, there are
sudden jumps in the EMF which is shown in a black rectangle in Figure-9.
Similarly, when the person at the gNB side makes activity, the EMF level
elevates as shown in a green rectangle in Figure-9. These can be explained by
the fact that when the user on the UE side makes activity near the smartphone
camera, new video frames are generated for uplink traffic and sent, and vice
versa for the gNB side. It is also observed that EMF does not exceed when
there is no video activity on both sides, i.e., a video call in progress but
none of the users are facing the camera. This is shown in a blue rectangle in
Figure-9. This behavior is observed only when the UE is placed near the probe.
At a distance far from the probe, such elevated levels of EMF are not
observed.

##  V EMF Measurements under spatio-temporal variations

Spatio-temporal characteristics are important factors to be considered while
measuring 5G EMF which exclusively uses AAS and dynamic-TDD. Such
characteristics must be considered while performing the measurement of EMF and
post-processing. This aspect can be motivated by the following two aspects:

  * •

Application of higher frequency bands such as mmWave and terahertz (THz)
require beamforming techniques to cope with the higher path losses (Section-
II). Besides, beam-tracking and beam-steering are also needed for mobile users
and this is achieved using AAS at the gNB. mmWave channel is mainly dominated
by a limited number of paths from _different angle of arrivals (AoAs)_[29,
30], as shown in Figure 10. Thus, different directions may experience
different EMF radiation, i.e., directional dependency of the EMF. Moreover, as
the user moves, the directional dependency also varies. However, the existing
EMF assessment techniques (Frequency selective, Code Selective, and Broadband
[31]), do not account for the directional dependency. This motivates the
development of direction/AoAs dependent EMF exposure assessment techniques
(and devices) in which the spatial characteristics of the EMF are also taken
into account such as EMF probes with multi-antenna.

Figure 10: Propagation from gNB to the receiver with direct and reflected
paths in mmWave.

  * •

Another critical aspect is Dynamic TDD (varying duty cycles for uplink and
downlink) which is provisioned in 5G to deal with the highly variable data
demands. This may lead to dynamic variations in the EMF exposure over time. To
capture such dynamicity of EMF over time, long-duration EMF measurement is
required which could be time-consuming and expensive. Thus, extrapolation
techniques, which also take into account the temporal dynamicity of the duty
cycle of 5G-NR transmissions, are required to obtain long-term data from the
measurements done over a short period.

##  VI Conclusions and Ongoing Work

Careful planning and safe deployment of 5G technologies will bring enormous
benefits to both society and the economy. Active Antenna Systems are the key
enabler for 5G technologies such as Massive MIMO, mmWave, and Dynamic
Beamforming. Unfortunately, superficial knowledge about these technologies has
created concerns among the general public over EMF radiation. Several
standardization bodies are studying the effects of EMF radiation on the human
body and set limits on the transmission by the 5G base stations. However,
over-conservative limits may hamper the 5G rollout and the capacity it can
achieve. Using the conventional EMF measurement methods may lead to misleading
conclusions that 5G frames are more dynamic and user-specific. Hence, it is
imperative to study and find the gaps in conventional EMF measurement
methodology and come up with adaptations/improvements.

In this work, we have focused on the measurement of EMF caused by using an AAS
at the gNB. We observed that an AAS, through UE-specific beamforming can
achieve same performance as a sectoral-antenna (low directive), however,
reducing the EMF radiation in the vicinity of the UE. Further, only the
transmission from base stations towards the users, i.e., downlink, are being
perceived as harmful. Through field experiments, we observed that uplink EMF
radiation can exceed the limits by many orders especially when the RSRP at the
UE is poor. Finally, we provide guidelines to develop novel EMF measurement
methodology which also takes spatio-temporal characteristics of the 5G
transmissions into account. This will be helpful for mmWave and dynamic TDD
based operations. propose

We believe that the study and field experiments conducted in this work will
help in providing clarity over the EMF concerns raised by the general public.
Nonetheless, the work is in progress and we have several planned activities
some of which are:

  1. 1.

UAV-based antenna pattern measurement of AAS: An apriori knowledge about the
antenna pattern is critical for proper placement of the measurement probes.

  2. 2.

EMF measurement with cell-barring at the gNB: Through cell barring, a
dedicated UE-specific beam can be formed for a duration suitable enough to
assess the worst-case EMF exposure.

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|  Sumit Kumar (S’14-M’19) received the B.Tech and M.S. in Electronics $\&$
Communication Engineering from Gurukula Kangri University, Haridwar, India
(2008) and the International Institute of Information Technology, Hyderabad,
India (2014), respectively, and the Ph.D. from Eurecom (France) in 2019.
Currently, he is working as a Research Associate at the Interdisciplinary
Centre for Security, Reliability, and Trust (SnT), University of Luxembourg.
His research interests are in wireless communication, interference management,
Integration of 5G with Non-Terrestrial-Networks and Software Defined Radio
prototyping.
---|---
|  Chandan Kumar Sheemar received his Bachelor in Information Engineering and
Master in Telecommunications Engineering degrees in 2016 and 2018 from the
University of Padua, Italy. He received his PhD in signal processing for
wireless communications from EURECOM, France, in 2022, under the supervision
of Prof. Dirk Slock. The topic of his PhD thesis was massive MIMO full duplex
communications, for which he developed several novel hybrid beamforming
designs to deal with the self-interference in the millimeter wave. He is
currently a research associate at the University of Luxembourg in the Signal
Processing $\&$ Satellite Communications research group, SIGCOM, headed by
Prof. Symeon Chatzinotas. His research interests include Statistical Signal
Processing, Optimization Theory, Beamforming, Intelligent Reflecting Surfaces
and Non-Terrestrial Networks.
---|---
|  ABDELRAHMAN ASTRO received the B.Sc. degree in electrical engineering from
the Canadian International College, Egypt, in 2017. He is currently an RnD
Specialist at the Interdisciplinary Centre for Security, Reliability and
Trust, University of Luxembourg. His research interests include software-
defined radios (SDR), wireless communication systems, real-time systems, and
systems architecture.
---|---
|  JORGE QUEROL (S’13–M’18) was born in Forcall, Castelló, Spain, in 1987. He
received the B.Sc. (+5) degree in telecommunication engineering, the M.Sc.
degree in electronics engineering, the M.Sc. degree in photonics, and the
Ph.D. degree (Cum Laude) in signal processing and communications from the
Universitat Politècnica de Catalunya - BarcelonaTech (UPC), Barcelona, Spain,
in 2011, 2012, 2013 and 2018 respectively. His research interests include
Software Defined Radios (SDR), real-time signal processing, satellite
communications, 5G nonterrestrial networks, satellite navigation, and remote
sensing. His Ph.D. thesis was devoted to the development of novel antijamming
and counter-interference systems for Global Navigation Satellite Systems
(GNSS), GNSS-Reflectometry, and microwave radiometry. One of his outstanding
achievements was the development of a real-time standalone pre-correlation
mitigation system for GNSS, named FENIX, in a customized Software Defined
Radio (SDR) platform. FENIX was patented, licensed and commercialized by MITIC
Solutions, a UPC spin-off company. Since 2018, he is Research Scientist at the
SIGCOM research group of the Interdisciplinary Centre for Security,
Reliability, and Trust (SnT) of the University of Luxembourg, Luxembourg. He
is involved in several ESA and Luxembourgish national research projects
dealing with signal processing and satellite communications. He received the
best academic record award of the year in Electronics Engineering at UPC in
2012, the first prize of the European Satellite Navigation Competition (ESNC)
Barcelona Challenge from the European GNSS Agency (GSA) in 2015, the best
innovative project of the Market Assessment Program (MAP) of EADA business
school in 2016, the award Isabel P. Trabal from Fundació Caixa d’Enginyers for
its quality research during his Ph.D. in 2017, and the best Ph.D. thesis award
in remote sensing in Spain from the IEEE Geoscience and Remote Sensing (GRSS)
Spanish Chapter in 2019.
---|---
|  SYMEON CHATZINOTAS (Senior Member, IEEE) is currently a Full
Professor/Chief Scientist I and the Head of the SIGCOM Research Group, SnT,
University of Luxembourg. He is coordinating the research activities on
communications and networking, acting as a PI for more than 20 projects and
main representative for 3GPP, ETSI, and DVB. In the past, he has been a
Visiting Professor with the University of Parma, Italy, lecturing on 5G
wireless networks. He was involved in numerous research and development
projects for NCSR Demokritos, CERTH Hellas and CCSR, and the University of
Surrey. He has coauthored more than 450 technical papers in refereed
international journals, conferences, and scientfic books. He was a co-
recipient of the 2014 IEEE Distinguished Contributions to Satellite
Communications Award and the Best Paper Awards at EURASIP JWCN, CROWNCOM, and
ICSSC. He is on the Editorial Board of the IEEE TRANSACTIONS ON
COMMUNICATIONS, IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY, and the
International Journal of Satellite Communications and Networking.
---|---