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Massive MIMO Design for 5G Networks: An Overview on Alternative Antenna
Configurations and Channel Model Challenges
Conference Paper · July 2017
DOI: 10.1109/HPCS.2017.52
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Massive MIMO Design for 5G Networks: An
Overview on Alternative Antenna
Configurations and Channel Model Challenges
H. M. El Misilmani and A. M. El-Hajj
ECE Department, Beirut Arab University, Lebanon
hilal.elmisilmani@ieee.org, a.elhajj@bau.edu.lb
Abstract—With the growth of mobile data application and the
ultimate expectations of 5G technology, the need to expand the
capacity of the wireless networks is inevitable. Massive MIMO
technique is currently taking a major part of the ongoing research,
and expected to be the key player in the new cellular technologies.
This papers presents an overview of the major aspects related to
massive MIMO design including, antenna array general design,
configuration, and challenges, in addition to advanced
beamforming techniques and channel modeling and estimation
issues affecting the implementation of such systems.
Keywords—Massive MIMO, 5G, Antenna arrays, Channel
estimation, Beamforming.
I. INTRODUCTION
The fifth generation of wireless communication standards is
the next evolution that is expected to hit the markets by 2020.
In addition to improved data rates of up to 10 Gbps and
reduced latencies below 1 ms, this evolution promises to
enable a network of connected machines, devices that operate
in conjunction with regular subscribers [1]. This will introduce
new communication mechanisms such as device to device
communication (D2D). The road to 5G deployment is
essentially facilitated by the introduction of new concepts that
will help 5G systems reach the projected theoretical
specifications. Among others, ultra-network densification will
transform the traditional cell architecture from a collection of
macrocells covering large areas to multitude of small cells
providing higher capacity and better services to the users while
using a lower transmit power. The jump to the millimeter wave
band is another novelty which will allow to benefit from very
large bandwidths and achieving very high data rates. However,
these high frequencies impose additional constraints to the
system design in terms of signal blockage and attenuation.
This is why multi-antenna approaches such as Massive MIMO
become a necessity in future communication standards since
they enable an efficient adaptation of the parameters of the
transmitted signal to counteract the millimeter wave channel
effects.
The interference is the main limitation of wireless networks.
Communications engineers have strived to exploit the prop-erties
of multipath wireless channel in order to improve the performance
of communications standards through an increase
of the radio link capacity. Several interference reduction
techniques have been studied, such as: multiuser MIMO [2],
multicell processing [3], and interference alignment [4]. However, these techniques cannot be used to reach the high data
rates expected from future technologies. Network densification
is taking a big interest in research as a candidate solution. On
way of applying this technique is by cell-size shrinking. This
could be done by installing femto or small cells [5]
, but this increases interference and adds cost of additional
equipment. Another option that is taking huge interest in
wireless communication is the use of Very Large MIMO arrays
or Large-Scale Antenna Systems, known as Massive MIMO.
This technique, similarly called Full Dimension MIMO, Hyper
MIMO, and ARGOS, use a great number of elements, fully
operating in a coherent and adaptive way. Massive MIMO
takes the original concept of multiple-input multiple-output to
another level going from tens to hundreds or thousands of
antennas with the aim of increasing the spectral efficiency in
the system, and providing a uniform quality of service in
different environments, notably in urban and suburban areas
complementing or even replacing the process ultra-network
densification.
Usually, a single element antenna possesses a poor di-rectivity
with a relatively wide and wide radiation pattern. For 5G
technology, high directivity is strongly required. This can be
achieved through constructing antenna arrays, in a suitable
electrical and geometrical configuration, without the need for
optimizing the size of antenna elements, which is the motivation
behind the use of Massive MIMO. Since it was first introduced [6],
the use of massive antennas has been receiving important interest
in wireless technology [6]–[14]. Some of the work focused on the
number of antenna elements needed to achieve optimized
performance [10], other investigated detec-tion methods that can
further enhance the gain [11]. In [12] the motivation of massive
MIMO and a comparison between using more antennas or more
base stations are presented. Moreover, a TDD cellular system
employing nocooperative BSs equipped with Massive MIMO is
presented in [6]. A recitation on MIMO progress, importance, and
challenges facing Massive MIMO from a detection perspective is
presented in [13].
Massive MIMO are considered to be adopted in 5G network, at
the Base Station. These large-sized antenna arrays can adapt
(a)
(a)
(b)
Figure 1. (a) Single element structure, (b) Array configuration using 4 4
antenna elements [15]
(b)
flexibly to complex environment, and by scaling up the order of
MIMO system and applying beamforming techniques, the signal
transmitted from the BSs can be highly focused into small regions
of interest, towards each user, resulting in greatly reduced
interference. As a result, the spatial multiplexing in each timefrequency resource block, along with multi-antenna diversity and
beamforming, is expected to improve the transmission rate, the
multiplexing capability, the spectrum efficiency, and maximize the
signal-to-noise-plus-interference ratio (SNIR or SINR). Even, a
nearly interference-free com-munication link would be established
between the user and its BS, if highly directly beams with low
sidelobe levels are used. The performance can be further
enhanced if more antennas are at the BS, and eventually higher
data rates required in 5G can be achieved. Further enhancement
can be realized by installing more antennas in the users’ mobile
devices. In addition, as a result of the channels orthogonality of
different users, increasing the number of antennas can actually
result in simpler transmit/receive processing techniques, even in
the presence of interference. Nevertheless, through averaging out
many random impairments, Massive MIMO systems are able to
enhance the energy efficiency with potential power savings, while
providing robust and secure communicating link.
In the following section a brief overview on the
antennas used in Massive MIMO is presented, along
with the main configurations and challenges found. Next,
5G channel mod-eling and estimation in the presence of
Massive MIMO is investigated, and finally the
beamforming concepts in Massive MIMO are examined.
II. MASSIVE MIMO ANTENNAS
A. General Description and Review
Usually, for a simpler and practical antenna system, the
design of different array elements constituting the antenna
array is identical, however this is not necessary. Having such
an array results in more freedom in controlling the array
pattern of an array without changing its physical dimensions.
This is done through adopting proper geometrical antenna
Figure 2. (a) Prospective view the proposed antenna unit, (b) Subarray
with four antenna units [18]
array configuration. This antenna configuration, along
with the pattern of a single element, the separation
between different elements and mutual coupling, exhibit
a significant effect on performance of the system.
Theoretically speaking, and neglecting the coupling between
the different elements, the fields radiated by the individual
elements can be added using vector addition to determine the total
field of the array. Since every element has its own pattern, a
constructive interference of the different fields is essential in the
desired direction, whereas a destructive interference is required to
cancel the radiation in other directions, resulting in a maximum
intensity at a specific desired location [16]. More advanced
antenna array design consists of the use of phased arrays. In a
phased array, the feeding mechanism is designed in such a way
that different relative phases will be used with the different
antenna elements, reinforcing the maximum radiation pattern in a
desired direction [17].
An essential objective behind the use of Massive MIMO in
5G technology is to control the overall pattern of the antenna
for interference reduction and long distance communication
over high frequency. This pattern is highly affected by the array configuration, the separating distance between the
antenna elements, the phase and amplitude of the excitation of
different elements, and the corresponding pattern of each.
In the design process, the chosen configuration should
be studied in terms of the total number of antenna elements, the resulting radiation characteristics: radiation
pattern, beamwidth and gain. In addition, a care should be
taken in studying the mutual coupling between the
elements and how they affect the power of the received
signal, the coverage, and the overall channel capacity. A
proper study of the above should be done on one or more
of the operating frequencies of the 5G technology, the 6
GHz, 27 to 28 GHz band, and 60 to 70 GHz bands.
Different anttennas can be utilized in such arrays, such as
(a)
Figure 3. The configuration of Turning Torso antenna array [24]
(b)
(c)
Figure 4. (a) Horizontal array, (b) Vertical array, (c) Planar or
Rectangular array
printed or microstrip antennas, horn, and dipoles antennas.
The choice of the element type depends on the application in
hand, the performance needed, the overall size of the system.
A 4 4 array configuration of a compact millimeter wave BS,
having 36 sub-sectors consisiting each of a 16 planar ALTSA
elements is presented in [15]. The antenna, shown in Fig. 1,
has a half-power beamwidths of 10:7 and 5:3 , in the H- and Eplanes respectively, with a realized gain of 25.6 dBi. An
antenna array of 144 ports having dual polarization, horizontal
and vertical, and operating at 3.7 GHz is presented in [18]. The
array has 18 low profile sub-arrays, each sub-array consists of
4 elements connected to power splitters. The antenna array is
shown in Fig. 2. A three stack levels Massive MIMO system of
orthohexagonal rings consisting each of six sub-arrays is
presented in [19] to establish a compact dual-polarized
antenna. The antenna, shown in Fig. 3, has a gain of 16.6 dBi,
with a HPBW of 12:5 in the azimuth plane. Using the steerable
feature, 18 beams can be generated covering a whole
circumference. Massive MIMO using active antennas of 32
ports is presented in [20], providing an increased cell average
throughput gain compared to conventional system. A massive
MIMO system based on multi-mode antennas design to
operate as an UWB system in the 6 8:5 GHz band is
presented in [21]. Different number of antenna elements
consisting each of a miniaturized circular patch microstrip
antenna, operating at 1.8 GHz, is presented in [22]. A method
to synthesize the array patterns with a desired sidelobe level
with uniform circular arrays using Dolph-Chebyshev approach
has been presented in [23].
Taylor ULAs, it is possible to control the sidelobe level but
not the beamwidth. More recently, a method for the design
of ULAs with independently controllable beamwidth and
SLL has been proposed in [26]. To provide additional
variables, planar arrays, shown in Fig. 4 (c), are adopted to
control the radiation of the antenna. In planar arrays, the
antenna elements are arranged over some planar surface,
called UPA, in a planar or rectangular form. The use of
such array configuration results in reduced lower sidelobes,
while directing the maximum radiation in a desired location,
one of the main objectives of 5G transmission.
For M and N elements arranged along the x- and yaxes respectively, and assuming different excitation of
each element, the array factor can be given by [16]:
AF = SxmSyn
where:
M
X
Im1ej(m
Sxm =
1)(kd sin cos + )
x
x
m=1
(2)
N
X
I1nej(n
Sym =
1)(kd sin sin + )
y
y
n=1
with dx, dy are the separating distance between the elements,
and x, y, are the progressive phase shift between them, along
the x and y axes respectively. Assuming a uniform excitation,
the normalized array factor can be given by [16]:
AFn( ; ) =
B. Antenna Configuration
Massive MIMO antennas could be collocated at the
base station site in a uniform linear, square, circular, or
cylindrical
arrays.
They
can
be
distributed
geographically or installed on the face of a building.
1) Planar Array: In linear arrays, the elements are located
along a straight line, vertically or horizontally, as shown in
Figs. 4, (a) and (b). This topology is called uniform linear
arrays (ULAs) when the inter-element spacing is uniform.
ULAs with equal sidelobes, which lead to the narrowest
beamwidth, are presented in [25] and are denoted the Chebyshev arrays. Taylor arrays, on the other hand, are famous for
their decaying sidelobes. In the synthesis of Chebyshev and
(1)
0 M sin
1 sin
2
xx
10
M
@
A@
2
with x = kdx sin cos + x and
N sin
1 sin
2
y
y
1
(3)
N
2
A
y = kdy sin sin +
y.
A planar version of Chebyshev ULAs is presented in
[27]. The planar version of Taylor arrays is given in [28].
The design of planar arrays with independently
adjustable beamwidth and SLL is introduced in [29].
2) Circular and Cylindrical Arrays: In circular arrays, shown
in Fig. 5 (a), the antenna elements are arranged in a circular
ring, called UCA. This configuration usually provides
21)
13) 15)direction. Assuming the costs. One solution for this is to decrease the size of the antenna
22)
wider angle radiation
peak of the main beam is directed in the ( 0; 0) direction,element. This can be done through working with millimeter wave
the array factor in this case can be given by [16]:
19)
17)
20)
X
14)
n
16)
11)
antennas operating at high frequency ranges, for which 5G
N
18)
Inejk 0 cos( n
technology is expected to operate at. Another
)
AF ( ;
8)
=1
0
10)
2
0)
=a (sin cos
sin 0 cos
+ (sin sinsin 0 sin 0)2 1=2
6)
4)
3)
cos
sin
5)
(4)
technique to reduce this cost is to use electromagnetic lens
antenna (ELA). This lens, shown in Fig. 6, focuses the power of
any indicent plane wave to a small subset of the antenna array
[32], [33]. This system requires less number of required RF
chains, and as a result the implementation cost is reduced.
12)with In being the amplitude excitation of the n, 0 and
given by [16]:
9)
)=
(5)
sin 0 cos
sin sinsin 0 sin 0
0
= tan
1
(6)
Figure 6. Proposed design with the EM-lens embedded antenna array [32]
7)
b)
(
(a)
Figure 5. (a) Circular array, (b) Cylindrical array
Through stacking circular arrays of equal radius one
above the other, separated by the same displacement,
cylindrical arrays can be formed. Cylindrical array, shown in
Fig. 5 (b), can be actually seen as a linear array along the
vertical line on the cylindrical surface, and a circular array
along the transversal plane cutting the cylindrical surface.
Both Circular and cylindrical arrays possess the advantage
of symmetry in azimuth, which makes them ideally suited
for full 360 coverage. One of the most important properties
of cylindrical arrays is that the multiplication of the array
factors of both, linear and circular array, results in the array
factor of the whole cylindrical array [30], [31], i.e.:
AF ( ; ) = AFlinear( ; ) AFcircular( ; )
(7)
Hence, while the circular arrays provides 360
coverage, stacking them in such cylindrical way provides
increased gain and directivity.
C. Design Challenges
Although Massive MIMO systems provide significant
per-formance enhancement with essential advantages,
the use of a large antenna of antenna arrays bring
several challenges that must be considered.
For instance, the use of Massive MIMO at the BSs could
result in increased hardware complexity and signal processing
Another issue is related to the different antenna array
configurations, for which each configuration results in
different channel characteristics and hence will have an
impact on the performance of the overall system. Assuming
a linear array system in adopted and for a fixed total
number of elements, a higher spectrum efficiency can be
achieved by placing more antennas in the horizontal
direction, whereas, for the same total number of antenna
elements, the performance is degraded in the horizontal
direction if more antennas are used in the vertical direction.
The separation between the antenna elements is another
important factor that affects the array radiation. Although
reducing the antenna spacing could meet the installation
requirements, if the elements displacement is less than =2 of
the antenna, mutual coupling and fading correlation become
increasingly dominant, resulting in degrading the capability of
the Massive MIMO array to distinguish the users, and hence
degrading the system performance. Hence, an important
attention has to be made while choosing the separation
between the antenna elements. If the physical space is limited,
the separation between the antenna elements must be
reduced in order to increase the total number of antenna
elements. An investigation of this effect for a single- or multiusers has been presented in [34]–[36]. It was shown that that
due to these effects, a practical limit on the maximum number
of BS antennas could be found that results in a maximum
spectral efficiency. To optimize the system performance,
matching networks can be integrated with the design of
compact antenna arrays. If strong mutual coupling is found,
applying an optimal matching improves the performance, but
reduces the system bandwidth [37]–[44]. The impact of such
coupling and its effect on the bandwidth of circular arrays has
been investigated in [19].
IV. CHANNEL ESTIMATION
Inspecting the general configuration of an array system at
the BS, a conventional 2D beamforming exhibits an important
deficiency. The transmitted beam is only adjusted in the
horizontal dimension, i.e. the beam angle is only adjusted with
the azimuth angle. This could be done by controlling the signal
distribution through altering the phase and ampli-tude of the
excitation on each antenna port. In the vertical dimension, the
transmission between the BS and cell users is with a fixed
angle. Hence, an optimal throughput could not be achieved,
and eventually, with equal azimuth angles of the users, an
inevitable interference will occur. In order to solve this
deficiency, 3D MIMO system is recommended, for which
Active Antenna Systems (AAS) are used. These AASs consist
of RF modules integrated with the design, used to control each
element separately. This results in an increased efficiency, and
flexible beam control. Hence, a Massive MIMO should be
designed with a 3D spacial channel models through adjusting
the beam angle with both azimuth and elevation angles.
III. 5G CHANNEL MODELING AND MASSIVE MIMO
The move from current sub-6 GHz transmission to the
millimeter range has a significant impact on the performance of
the large-scale antenna systems. While MIMO systems have
been considered as additional feature for current wire-less
communication technologies, massive MIMO systems are a
necessity for the operation of millimeter-wave based systems
[45]. The main reason for that is that at very high frequencies,
the pathloss of each of the links become rather significant. The
frequency bands projected for 5G operation (e.g., 28 GHz)
suffer from new forms of losses related to rain, atmospheric
gas absorption, foliage, etc. Several properties of massive
MIMO systems, such high array gains, are needed to make
communication viable, even for small distances.
Currently employed channel models assume random
scat-tering model for each link in addition to the presence
of in-dependent scatterers [46]. Moreover, the scattering
considered is of diffuse nature, ignoring the specular
propagation where the latter become notably dominant at
high frequencies [47]. Hence, to correctly characterize the
performance of the MIMO system, a more realistic channel
model is needed. This model relies on spatial consistency
where geometric locations of the scatterers, in particular
near the transmitter and receiver, needs to be specified.
Furthermore, massive MIMO systems are characterized
by a high directly and pencil-shaped beamforms. Current
channel models based on plane wave propagation fail to
provide the necessary angular resolution in the analysis of
the propagation of each of the links originating from the
MIMO array. Thus, it has been recommended to use new
channel models that provide higher angular resolution and
a better representation of the amplitude distribution of each
of the rays. The channel models are also expected to rely
on spherical wave propaga-tion [46].
Channel estimation is at the core of the operation of any
MIMO system. The knowledge of the channel state information is necessary in order to perform adequate precoding in the
MIMO system. Time division duplexing (TDD) has been the
technique of choice to get channel information, mainly to make
use of the channel reciprocity principle [48]. According to this
principle, electromagnetic waves transmitted over the same
frequency band in the uplink and downlink, experience the
same propagation conditions. Using, this technology, the need
for feedback of channel estimates diminishes while having
channel state estimates at the transmitter. Recently, frequency
division duplexing was also investigated for channel
information acquisition in massive MIMO systems. The main
idea is to either implement precoding technique with partial
channel state information or use compressed sensing to
reduce the feedback overhead [49]. From an antenna array
point of view, there is a certain level of correlation among
antennas. Therefore, it is not always necessary to get the
channel estimates for all the antennas.
V. BEAMFORMING CONCEPTS IN MASSIVE MIMO
The conventional MIMO concept was built around the idea
of utilizing advanced signal processing techniques to generate
beams with high directivity that is pointed to a target user, and
in the optimal case, having the weakest sidelobes in the
direction of the non-served user (thus causing minimal interference). The implementation of the intended beamforming
technique at the transmitter (transmit beamforming) or at the
receiver (receiver beamforming) offer the network designer
several axes of freedom to optimize the network performance.
The advent of millimeter wave technologies adds new considerations to the design of beamforming systems. First and
foremost, the switch to higher frequency bands originated from
the need to use large bandwidths. A direct implication would
be a degradation in the SNR. As discussed in [50], this will
result in problems during the beam-formation especially that
the array gain is small in this phase since wide beams are
used for user localization.
Another issue is the large bandwidth employed which is
usually greater than the coherence bandwidth of the chan-nel
[51]. Normally, this indicates a frequency selective chan-nel
and a large possibility for intersymbol interference. So,
advanced equalization needs to be added, complementing the
selected beamforming technique. The deep changes in the
propagation properties of the channel also lead to two
emerging topics related to beamforming in Massive MIMO,
namely, elevation beamforming [52] and efficient codebook
design [53]. The main premise of elevation or 3D beamforming is to exploit the channels degrees of freedom in the
elevation direction [52], [54] paving the way to what is known
as full dimension MIMO systems. In simple terms, the beams
are adjusted in the horizontal and vertical direction. A
necessity for the implementation of such systems involves
the definition of double directional channel models [55]. In
addition to 3D beamforming, these channel model will allow us
to design beam-tracking which are necessary to circumvent
the shortcomings of millimeter wave transmission in terms of
signal blockage and small range (e.g., [56]).
Efficient codebook design is another green area of research.
The main premise of the approach is to reduce the hardware
complexity in the implementation of beamforming techniques
by having fixed beam patterns which are generated by predetermined antenna weight vectors at the transmitter and
receiver. One advantage of codebook design is that it can be
easily designed for any antenna array geometry and specifications [50]. In [53], an efficient codebook-design algorithm for
millimeter wave-based massive MIMO system is presented.
The approach is based on cross-entropy optimization to jointly
identify the optimal analog precoder and analog combiner pair.
VI. CONCLUSION
This paper presented an overview on 5G technology
require-ments that are expected to be facilitated by Massive
MIMO technology. An overview of this promising systems has
been presented, with a major focus on its antenna part,
general design and antenna configurations, along with major
design challenges. Then, the modeling of channels in 5G with
the presence of Massive MIMO has been discussed, along
with the channel estimation and beamforming concepts.
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