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Radiation Analysis in a Gradual 5G Network Deployment Strategy

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In a world where many overlapping 2G, 3G, and 4G electromagnetic radiation sources already exist, concerns regarding the potential increase in these radiation levels following the roll-out of 5G networks are growing. The deployment of 5G is expected to increase power density levels drastically, given the limitations of mmWave communications that impose a notably higher number of base stations to cover a given area of interest. In this paper, we propose a gradual deployment strategy of a 5G network for a small area in downtown Austin, Texas, using the already existing 4G LTE sites of the area. The radiated power density of the proposed 5G network is then analyzed according to several electromagnetic field (EMF) exposure limits and compared to the radiation levels of the same area where only the LTE network is present. Simulation results for the selected area demonstrate the significant increase in radiation levels resulting from the addition of 5G cell towers.
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Radiation Analysis in a Gradual 5G Network
Deployment Strategy
Ahmad M. El-Hajj
Electrical & Computer Eng. Department
Beirut Arab University
Beirut, Lebanon
a.elhajj@bau.edu.lb
Tarek Naous
Electrical & Computer Eng. Department
Beirut Arab University
Beirut, Lebanon
tareknaous@ieee.org
Abstract—In a world where many overlapping 2G, 3G, and
4G electromagnetic radiation sources already exist, concerns
regarding the potential increase in these radiation levels following
the roll-out of 5G networks are growing. The deployment of 5G
is expected to increase power density levels drastically, given the
limitations of mmWave communications that impose a notably
higher number of base stations to cover a given area of interest.
In this paper, we propose a gradual deployment strategy of a
5G network for a small area in downtown Austin, Texas, using
the already existing 4G LTE sites of the area. The radiated
power density of the proposed 5G network is then analyzed
according to several electromagnetic field (EMF) exposure limits
and compared to the radiation levels of the same area where
only the LTE network is present. Simulation results for the
selected area demonstrate the significant increase in radiation
levels resulting from the addition of 5G cell towers.
Index Terms—5G, Network Planning, Radiation Analysis
I. INTRODUCTION
The notably large bandwidth available in the millimeter-
wave (mmWave) band and the potential multi-gigabit-per-
second (Gbps) data rates that can be achieved for future
communication services have made mmWave communications
a key part of Fifth Generation (5G) mobile networks. Despite
the promising advantages of millimeter wave communications
in terms of improved quality of service requirements, its usage
for the 5G wireless standards comes at significant costs. First,
working with such high frequencies will reduce coverage
ranges of base transceiver stations (BTS). For proper coverage
of an area, a densification of 5G BTSs is required to achieve
the same coverage provided for this same area by today’s
4G BTSs. Also, high propagation loss and increased signal
blockage occurs, motivating the introduction of multi-antenna
approaches such as Massive MIMO [1], [2].
This potential addition of a large number of transmitters
gives rise to another problem that needs to be considered,
which is the increase in radiation levels in the rolled-out
5G network. Although these transmissions are non-ionizing
radiations, they cause thermal heating at the eyes and skin
level. Extensive heating for long periods of time is when
adverse health effects may occur. These health concerns
have stimulated interest in the biological safety of mmWave
transmissions. In this respect, several exposure limits have
been specified in standards and regulations developed by
commissions and organizations that many governments will
rely on when future 5G networks are deployed. However, these
regulations have contradicting limits, many of which have
remained the same before the year 2000. Therefore, designing
a 5G network with radiation levels that complies with all the
safety limits is a difficult task given the current regulations.
Despite the ongoing standardization of 5G technology,
several works in the literature have presented 5G network
deployment studies. The cost and coverage implications of
deploying a 5G network in Britain has been presented in [3]
where it was shown that full coverage had exponentially rising
costs due to network densification. Additional 5G network de-
signs for different cities were presented in [4]–[6] without any
consideration for the constraints of electromagnetic radiations
or the implications of the environment in mmWave propaga-
tion. Network design has been studied under such radiation
constraints in [7], [8] but for 4G networks. Power density
assessment of 5G cellular nodes in an indoor environment has
been presented in [9] where results showed that the peak power
density remained below the specified threshold and can thus
be deemed safe for the general public. However, not all of the
guidelines and exposure limits were considered in this work
and the simulation did not represent a real-world scenario.
To the best of our knowledge, no work has provided a
thorough analysis of the deployment of 5G networks in terms
of its impact on the increase in radiation levels. Existing work
in the literature has either focused on the cost (e.g., [3]) or
radiation levels for older standards (e.g., [7]). To this end,
this paper presents a mmWave-based 5G network deployment
strategy given pre-existing LTE nodes in a small geographical
area in Austin, Texas. We then approximate the power density
levels that would be experienced in such outdoor environments
and analyze their variations and compliance with the specified
exposure limits for different transmission powers and transmit
antenna gains. We also compare this radiated power density
in the deployed 5G network to the power density levels of the
same area when only the pre-existing LTE BTSs are present.
The rest of this paper is organized as follows: Section II
presents the 5G simulation environment considered in this
work. The proposed deployment strategy of the 5G network in
a small area in downtown Austin, Texas is presented in Section
III. Radiation analysis of the deployed network is performed
in Section IV. Concluding remarks follow in Section V.
II. 5G ENVIRONMENT SETU P
A. Pathloss Model
The close-in free space reference distance (CI) path loss
model [10] is considered. It is defined by the following
equation:
P LCI (f , d)[dB] =FS P L(f, 1m) + 10nlog10 d
d0+XCI
σ
(1)
where the free space path loss (FSPL) for a frequency of
operation fis given by:
F SP L(f , 1m) = 20log10 4πf
c(2)
The CI path loss model can be rewritten as:
P LCI (f , d)[dB] = 20 log10 4πf
c+10nlog10 d
d0+XCI
σ
(3)
where:
n: is the single model parameter or the path loss exponent
d0:is the reference distance taken as 1 meter
d: is the distance in meters between the BTS and the
mobile station
XCI
σ: a zero mean Gaussian random variable with stan-
dard deviation σin dB. It represents large scale channel
fluctuations due to shadow fading (SF ). The standard
deviation of this random variable is given by:
σCI =qXXC I2
σ/N
=q(P LCI F S P L n10 log10 (d))/N
(4)
where Nrepresents the number of measured path loss
data points
The values for parameters nand SF vary from one sce-
nario to another. Table I presents the values of these model
parameters in different environmental setups, which have been
obtained by ray tracing and measurements in [11].
TABLE I: CI Model parameters for different environments
[12]
Scenario CI Model Parameters
UMa-LOS n = 2.0, SF = 4.1 dB
UMa-NLOS n = 3.0, SF = 6.8 dB
UMi-S.C.-LOS n = 1.98, SF = 3.1 dB
UMi-S.C.-NLOS n = 3.19, SF = 8.2 dB
UMi-O.S.-LOS n = 1.85, SF = 4.2 dB
UMi-O.S.-NLOS n = 2.89, SF = 7.1 dB
UMa: denotes Urban Macrocell (Tx Heights >25 m), UMi:
denotes Urban Microcell (Tx Heights <25 m), LOS: denotes
line-of-sight, NLOS: denotes no line-of-sight, S.C.: denotes
Street Canyon, O.C.: denotes Open Square
B. mmWave Specific Attenuation Factors
In mmWave propagation, attenuation due to atmospheric
and weather conditions constitutes an important factor to con-
sider [13]. Specifically, we will consider oxygen attenuation
O(d)and rain attenuation R(d), which are both dependant
on the separation distance d. Oxygen attenuation has been
observed to be equal 16dB/km in [14], and hence can be
obtained by the following:
O(d)[dB] =16d
1000 = 0.016d(5)
The rain attenuation factor depends on the climate of the
zone under study. The International Telecommunication Union
(ITU) have segmented these zones and provide measurements
for the rain rates of each zone [15]. Based on these measure-
ments and considering that the area under study in this paper
will be in Austin, Texas, the rain attenuation rate will be taken
to be 3.5 dB/Km. This loss can then be obtained using:
R(d)[dB] =3.5d
1000 = 0.0035d(6)
C. Link Budget Estimation
The link budget equation upon which the cell radius will be
estimated can now be defined as:
PRx[dBm] =E IRP [dBm]P LCI O(d)R(d)+GRx (7)
where PRx is the power received by the mobile station,
GRx is the antenna gain in dBi of the mobile station, and the
effective isotropic radiated power (EIRP) is given by:
EI RP [dBm] =PT x +GT x LT x (8)
where PT x is the transmission power in dBm of the BTS,
GT x is the transmitting antenna gain in dBi, and LT x is the
cable loss in dB due to possible antenna mismatch. Table II
lists the values chosen for each parameter of the link budget
equation.
TABLE II: Simulation Parameters
Parameter Value
Frequency f28 GHz
Max EIRP 43 dBm
Antenna Gain GT x 24 dBi
Transmission Power PTx 19 dBm
Receiver Antenna Gain GRx 0 dBi
Cable Losses LT x 0 dB
D. Identifying Cell Ranges
By using the link budget equation in (7) and considering the
simulation parameters given in Table II, the separation distance
can be found for several receiver sensitivities. The calculated
distance constitutes the cell range for a given BTS that
satisfies the received power requirement. These calculations
are summarized in Table III. A main observation is that the
resulting cell ranges become significantly smaller when the
receiver sensitivity is higher. Cell ranges that are too small
(below 10 meters) are not considered since such small ranges
are not desirable for real deployment.
III. NET WORK DEPLOYM EN T
We now consider a small geographical area in downtown
Austin, Texas, to deploy the 5G network. A diagrammatic
view of our proposed strategy is shown in Fig. 1. The selected
area is shown in Fig. 2(a) and delimited in red on the map of
Fig. 2(b). This area already contains several locations where
LTE sites are already built and which will be the starting
points of the gradual 5G network deployment strategy. The
initial LTE cell tower locations are obtained from an online
cell tower database (www.opencellid.org). We consider a worst
case scenario where no line-of-sight components are available.
Install initial 5G BTSs in pre-existing LTE site
locations
Identify coverage holes in the area after initial
installations
Install 5G BTSs in large coverage holes
Install reduced-range 5G BTSs in medium coverage
holes
Install 5G repeaters in small coverage holes
between neighboring cells
Fig. 1: Gradual Deployment Strategy
The first step of deployment starts by building 5G BTSs
in the areas where LTE BTSs already exist, a technique
known as co-siting. The main aim of co-siting is to reduce
capital expenditures (CapEx) required to erect the 5G sites
and minimize the operational expenditures (OpEx) needed to
sustain their operation. UMa-NLOS towers will be placed in
these locations. The receiver sensitivity is considered to be
-78 dBm which, according to Table III, sets the cell range
of each UMa to be 53 meters. The coverage of the initial
BTSs installed is shown in Fig. 3, after slightly changing the
location of the BTS within the same area it is built on, which
may be any building rooftop, to lessen interference and provide
better coverage. It can be noticed that these initial cells do not
provide coverage to the whole area due to the small cell range
of each BTS. Theoretically, this range can be increased but
would demand the EIRP to be increased above the allowed
limit of 43 dBm, by increasing the transmission power and
selecting a higher-gain massive MIMO antenna configuration
The next step is the identification of coverage holes, as
shown in Fig. 4. Large coverage holes are can be noticed,
where several UMa towers can be distributed to provide good
coverage. Smaller coverage hole are also be identified. Some
of these holes are very small areas between neighboring cells
where 5G repeaters, such as the one described in [16], can
be placed to cover these small holes. Other small holes are
not small enough to be fixed merely by the placement of a
repeater, and are neither too big to place a BTS with a cell
(a)
(b)
Fig. 2: Geographical area of interest in Austin, Texas (a)
Satellite View (b) Map View
Fig. 3: Coverage of initial 5G BTSs built at the locations of
pre-existing LTE cell towers
range of 53 meters. In such locations, reduced-range towers
can be placed to provide coverage. The coverage range for
these towers can be shrinked by reducing transmission power
and choosing smaller MIMO antennas. We calculate the cell
range for the reduced-range BTS towers to be approximately
30 meters and estimate the coverage of the 5G repeater to be
15 meters. The final design of the deployed 5G network is
shown in Fig. 5. It can be observed that the deployment of a
5G network in an area as small as the one presented requires
a densification of cell towers and signal repeaters, which in
turn will cause much more radiation.
TABLE III: Calculated Cell Ranges for Several Receiver Sensitivities in Various Environments
Cell Range (meters) for EIRP = 43 dBm
Receiver
Sensitivity UMa-LOS UMa-NLOS UMi-S.C.-LOS UMi-S.C.-NLOS UMi-O.S.-LOS UMi-O.S.-NLOS
-78 dBm 302 53 334 38.5 385 60
-70 dBm 165 29.7 186 22.3 216 33
-65 dBm 105.5 22 120 15.7 139 22.5
-60 dBm 65 14.1 74.5 11 85 15.3
-55 dBm 38.5 ×44.5 ×55 ×
-50 dBm 22.6 ×26 ×27 ×
-47 dBm 16.2 ×18.6 ×20 ×
Fig. 4: Coverage holes identified after initial BTS installations
Fig. 5: Deployed 5G Network
IV. RAD IATION ANALYS IS
A. Exposure Limits
Although mmWave radiation is non-ionizing, the absorption
of mmWave energy in the human body causes heating to the
skin and eyes. This has caused serious concerns in terms
of potential health risks that might come along with the
introduction of 5G networks [17]. For this reason, before
introducing mmWave devices into the market, they need to
comply to several exposure limits that have been specified in
several standards and specifications. The specific absorption
rate (SAR) has often been used as the metric to determine
exposure compliance. The SAR measures the amount of en-
ergy absorbed by the human body while using a mobile phone.
However, at high frequencies, this absorption is restricted to
the skin level and thus it would be difficult to use the SAR
as a measure for exposure limits at mmWave frequencies. The
power density (PD) measured in W/m2has been the preferred
metric in the mmWave domain.
For the frequency range of 2 to 300 GHz, the IEEE C95.1-
2019 standard [18] specifies a limit power density value of 10
W/m2in restricted environment and 50 W/m2in unrestricted
environments. These correspond to an averaging time of
30 minutes. The International Commission on Non-Ionizing
Radiation Protection (ICNIRP) 2020 guidelines for limiting
exposure to electromagnetic fields [19] specify the general
public exposure limit at 10 W/m2for frequencies between
2 and 300 GHz with the averaging time being 30 minutes.
Similar limits are specified by the Federal Communications
Commission (FCC) in [20] where a restriction of 10 W/m2
for the general public has been set. In contrast, the institute
for building biology and sustainability (IBN) in Germany have
specified the exposure limit to be less than 0.1 µW/m2in their
2015 Standard of Building Biology Measurement Technique
(SBM-2015) [21], which is a million-fold lower than what is
specified by the aforementioned guidelines. This suggests that
negative health effects can occur at levels much lower than 10
W/m2. Finally, the Chinese ministry of health [22] have set
the power density exposure limit to 0.1 W/m2.
TABLE IV: General Public Power Density Restrictions for the
Frequency Range of 2 to 300 GHz
IEEE
C95.1-2019 ICNIRP FCC China SBM-2015
PDLimit
(W/m2)10 10 10 0.1 106
B. Power Density Assessment
The power density PDradiated by a transmit antenna can
be expressed at a far-field distance dusing the following:
PD=GT xPT x
4πd2(9)
The far-field distance is defined as the Fraunhofer distance
expressed by:
dfarfield =2D2
λ(10)
where Dis the largest dimension of the antenna and λis the
wavelength that corresponds to a frequency of operation. For
distances less than the far-field distance, the power density
cannot be computed using (9) and there would be a need
to resort to numerical modeling methods such as the finite
element method or finite-difference time domain.
C. Results
Fig. 6 shows the value of the power density for several
choices of transmission power and transmit antenna gain in the
distance range of 1 to 5 meters. For the proposed 5G network,
we considered a transmission power of 19 dBm and a transmit
antenna gain of 24 dBi. This corresponds to a value of 1.59
W/m2at 1 meters which drops to 0.06 W/m2at 5 meters.
These values comply with the limits set by IEEE, ICNIRP,
and FCC, since they are much lower than 10 W/m2, but do
not comply with SBM-2015 and Chinese Ministry of Health
regulations. Fig. 7 shows the variations of the power density
over the range of 20 to 50 meters. At 50 meters, which is at
proximity of the cell edge, the power density drops further to
6.35×104W/m2which is still much higher than the limit of
the SBM-2015 guidelines. As shown in both Fig. 6 and Fig.
7, increasing the transmission power or choosing an antenna
with a higher gain leads to an increase in the radiated power
density. To comply with the limit set by China, the total EIRP
needs to be dropped to achieve a power density below 0.1
W/m2which comes at the expense of a reduced cell range
(below 50 meters). This makes it more difficult to plan cost-
efficient 5G networks.
1 1.5 2 2.5 3 3.5 4 4.5 5
Distance (meters)
0
0.5
1
1.5
2
2.5
3
Power Density (W/m2)
PD for Several Pt and Gt
Pt=19dBm, Gt=24dBi
Pt=20dBm, Gt=10dBi
Pt=20dBm, Gt=20dBi
Pt=25dBm, Gt=10dBi
Pt=25dBm, Gt=20dBi
Fig. 6: Power Densities for Several Transmission Powers and
Antenna Gains for the range of 1 to 5 meters
Cumulative Distribution Function (CDF) plots for the power
density levels experienced in both the pre-existing LTE net-
work and the newly deployed 5G network are shown in
Fig. 8. The additional radiations imposed by the 5G network
significantly increase the probability of being exposed to
power density levels of more than 0.5 W/m2and that could
reach up to the range of 2 to 2.5 W/m2, while such power
20 25 30 35 40 45 50
Distance (meters)
0
1
2
3
4
5
6
7
8
Power Density (W/m2)
10-3 PD for Several Pt and Gt
Pt=19dBm, Gt=24dBi
Pt=20dBm, Gt=10dBi
Pt=20dBm, Gt=20dBi
Pt=25dBm, Gt=10dBi
Pt=25dBm, Gt=20dBi
Fig. 7: Power Densities for Several Transmission Powers and
Antenna Gains for the range of 20 to 50 meters
0 0.5 1 1.5 2 2.5
Power Density (W/m2)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
F(PD)
CDF for the Power Density in LTE and 5G Networks
5G & LTE Network
LTE Network
Fig. 8: CDF for the power densities levels for both pre-existing
LTE and deployed 5G network
density levels were not experienced in the pre-existing LTE
network. This is why the CDF of the power density in the
pre-exisitng LTE network reaches the limiting factor of 1 for
a power density around 0.65 W/m2
Fig. 9 shows a heat-map representing the radiated power
by the LTE BTSs in the area under study before deploying
the 5G network, where a simplified path loss model [23] is
considered for an urban macrocell. In Fig. 10, a similar heat-
map is shown after the deployment of the 5G network. The
remarkable increase in radiation levels after integrating 5G
infrastructure with the original LTE network can be easily
observed through the predominance of the red color in the
heat map.
The presented results clearly show that the potential ra-
diation levels that will be reached upon the roll out of
5G networks do not comply with all of the aforementioned
exposure limits. This suggests that 5G mobile networks can
not yet be classified as safe for the public, and demands
serious considerations before using mmWave communications
for 5G networks, given the potential harms it could afflict on
the public. This paves the way to the consideration of hybrid
transmission techniques including traditional electromagnetic
waves, free-space optics and visible light communication
Longitude
Latitude
Power Density Map of the Initial LTE Network (W/m^2)
0
1
2
3
4
5
610-3
Fig. 9: Power Density Map of the Initial LTE Network
Longitude
Latitude
Power Density Map of the Deployed 5G Network (W/m^2)
0
1
2
3
4
5
610-3
Fig. 10: Power Density Map of the Deployed 5G Network
V. CONCLUSION
This paper presented an analysis of the radiation levels in
a deployed 5G network in an urban outdoor environment.
Under the constraints of exposure limits, several challenges
face the design and planning of such radiation aware 5G
networks. Cell ranges need to be reduced to comply with the
maximum allowed radiated power, requiring the densification
of small cells in small areas and making it more costly to
deploy these radiation-aware 5G networks. Although in this
work we considered the maximum allowed EIRP prior to
network deployment, results showed power density levels that
do not satisfy all the exposure limits set by several sources. In
this regard, a positive impact can be imposed by radiation-
aware 5G networks on several levels. On a governmental
level, the exposure limits for the power density need to be
revised using today’s data and approaches to bridge the gap
between the thresholds specified by the different institutes
and commissions. On a technological and scientific level, the
radiation exposure constraint can open the door for innovative
5G solutions targeted to limit the health risks and economic
barriers associated with this problem. This work can be
extended by developing an analytical framework to efficiently
rank and rate different cell allocation alternatives to minimize
the potential radiations given a carefully chosen list of key
performance indicators.
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... Cellphone networks should be planned to emit reduced exposures -but global plans are only to expand exposure, on land and in space [70]. A recent study analyzed the expected exposure effects of planned G5 antenna density [72]. Calculating from known power consumption modeling, Ben Ishai [73] suggests that G5 networks would emit a 6-fold increased ambient radiation compared to current networks, and would require a thousand times as much electricity to power the networks. ...
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Man-made electromagnetic waves are the most widely and rapidly expanding exposure in today's world, including exposure in several frequency groups: extremely low frequencies (ELF) from electricity lines, hybrid car batteries and high power lines (>3 Hz–3 kHz), radiofrequency (RF) and microwave frequencies including millimeter waves (3 kHz–300 GHz) from mobile phones, towers, base stations and wireless devices, and intermediate frequencies "Dirty Electricity" emitted from power lines. While such organizations as ICNIRP (the International Commission on Non-Ionizing Radiation Protection) still continue to claim that electromagnetic radiation can cause "only thermal effects", clinging to theory that does not match facts and upholding obsolete thermal safety standards, extensive scientific evidence has clearly demonstrated that non-thermal health effects produced by electromagnetic radiation do exist, are important to health, and should be taken into consideration when safety standards are set. This review aims to highlight some evidence of biologic effects in various body systems, and to suggest preventive measures to reduce such effects on health. Exposure to electromagnetic radiation at intensities lower than thermal safety standards has been associated with non-thermal biological effects including damage and changes to cells and DNA. This review presents evidence of such effects demonstrated in: the hematologic system, the nervous system, the immune system, the reproductive system, the skin and muscles, the cardiovascular system, glucose metabolism, and Electrohypersensitivity ("Microwave sickness"). Protective measures are then suggested to reduce these effects.
... Cellphone networks should be planned to emit reduced exposures -but global plans are only to expand exposure, on land and in space [70]. A recent study analyzed the expected exposure effects of planned G5 antenna density [72]. Calculating from known power consumption modeling, Ben Ishai [73] suggests that G5 networks would emit a 6-fold increased ambient radiation compared to current networks, and would require a thousand times as much electricity to power the networks. ...
Article
Man-made electromagnetic waves are the most widely and rapidly expanding exposure in today's world, including exposure in several frequency groups: extremely low frequencies (ELF) from electricity lines, hybrid car batteries and high power lines (>3 Hz–3 kHz), radiofrequency (RF) and microwave frequencies including millimeter waves (3 kHz–300 GHz) from mobile phones, towers, base stations and wireless devices, and intermediate frequencies "Dirty Electricity" emitted from power lines. While such organizations as ICNIRP (the International Commission on Non-Ionizing Radiation Protection) still continue to claim that electromagnetic radiation can cause "only thermal effects", clinging to theory that does not match facts and upholding obsolete thermal safety standards, extensive scientific evidence has clearly demonstrated that non-thermal health effects produced by electromagnetic radiation do exist, are important to health, and should be taken into consideration when safety standards are set. This review aims to highlight some evidence of biologic effects in various body systems, and to suggest preventive measures to reduce such effects on health. Exposure to electromagnetic radiation at intensities lower than thermal safety standards has been associated with non-thermal biological effects including damage and changes to cells and DNA. This review presents evidence of such effects demonstrated in: the hematologic system, the nervous system, the immune system, the reproductive system, the skin and muscles, the cardiovascular system, glucose metabolism, and Electrohypersensitivity ("Microwave sickness"). Protective measures are then suggested to reduce these effects.
... The Uma [8,9] model is a new propagation model defined in the 3GPP protocol that is suitable for the current 5G high frequency development trend. The channel measurement frequency range is 0.5G-100 GHz, and the signal propagation effective distance is 10-5000 m [10]. 3GPP protocol 38.901 defines UMa, and its empirical formula is as follows: ...
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Millimeter wave (mmWave) communications have recently attracted large research interest, since the huge available bandwidth can potentially lead to rates of multiple Gbps (gigabit per second) per user. Though mmWave can be readily used in stationary scenarios such as indoor hotspots or backhaul, it is challenging to use mmWave in mobile networks, where the transmitting/receiving nodes may be moving, channels may have a complicated structure, and the coordination among multiple nodes is difficult. To fully exploit the high potential rates of mmWave in mobile networks, lots of technical problems must be addressed. This paper presents a comprehensive survey of mmWave communications for future mobile networks (5G and beyond). We first summarize the recent channel measurement campaigns and modeling results. Then, we discuss in detail recent progresses in multiple input multiple output (MIMO) transceiver design for mmWave communications. After that, we provide an overview of the solution for multiple access and backhauling, followed by analysis of coverage and connectivity. Finally, the progresses in the standardization and deployment of mmWave for mobile networks are discussed.
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