Analysis (BS) antennas for perfect CSI. Furthermore, we show

of power consumption and throughput using joint-bit ADCs in massive MIMO



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The sensible
implementation of massive multiple-input

-output (MIMO) inside the  fifth
generation  (5G)

communication structures is challenging due to its high hardware cost and power

This paper
investigated the uplink of massive multi-input multi-output (MIMO) systems with
a joint analog-to-digital converter (ADC) receiver structure, in which some
antennas are equipped with expensive full-resolution ADCs , a few antennas are
equipped with intermediate-resolution ADCs and some antennas with much less
expensive low-resolution ADCs. A closed-shape approximation of the achievable
sum rate with the maximum-ratio combining (MRC) detector is derived . we
perform a parametric energy efficiency analysis of MIMO uplink for the whole
base station receiver system with joint ADC resolutions. The analysis shows
that, for a wide variety of system parameters, ADCs with joint- bit
resolutions  are most beneficial in
energy efficiency sense, and that the usage of very low bit resolutions
outcomes in degradation of energy efficiency. We also achieve the power scaling
law that the transmit power of every consumer can be scaled down proportionally
to the inverse of the wide variety of base station (BS) antennas for perfect
CSI. Furthermore, we show the trade-off among the achievable rate and the
energy efficiency with respect to key system parameters, such as the quantization
bits, wide variety of BS antennas and consumer transmit power. in the end,
results are provided to show that the joint-ADC architecture can obtain a
higher energy-rate trade-off in comparison with 
high-resolution and 
low-resolution ADC architectures at a significantly lower hardware cost.

1. Introduction

The research on upcoming technology of wireless communication fifth generation
(5G) has been  undertaken to achieve 1000
time more data rate then the present technology 
(4G) 1. To

 meet this requirement, Massive multiple input multiple
output (MIMO) is key technology. By using the hundred of the antenna at the
base station(BS)  to achieve batter data
rate and energy efficiency.  Different
signal processing scheme as maximum ratio combining(MRC) and zero forcing(ZF) are
reduced the inter-user interference 2. Large number of antenna at (BS) have
more power consumption and complexity. It has costly hardwire implementation.  we cannot provide a specific radio frequency
(RF) chain to each antenna, different technique are proposed in recent past to
overcome these  problems. To reduce the
(RF) chain different analog and digital approaches are used as like switches,
phase shifters and lenses 4-6 of 2.

One basic problem is the power
consumption related  with the

conversion(ADC). In conventional

(MIMO) receiver architecture,
the analog-to-digital

convertors (ADCs) are supposed
to have high resolution.

In channels with larger
bandwidths, the correlated sampling

rate of the ADCs scales up.
Unlikely, high-resolution ADCs are

costly and power-hungry for
portable devices 3. For example,

in an ideal x-bit ADC with
flash design, there are

2x-1 comparators
and therefore the power consumption increase

exponentially with the
resolution 4-5.


The most direct answers to the
power assumption problem

are to reduce the sampling rate
and/or the quantization

resolution of ADCs.6 There is a massive

architecture at the receiver to reduce
the high resolution

of the ADCs to low resolution

while keeping the number of RF chains
unchanged. However,

the many  nonlinear distortion caused by low-resolution

necessarily causes different problems,
along with capacity loss at

high SNR ,high pilot overhead for
channel estimation

and complex precoder design 2.

Related Work

In Massive MIMO using the large number
antenna can enhance the capacity and the energy efficiency. But power
consumption and the hardwire cost is also increased. In (RF) chain analog to
digital  convertor (ADC) is  most power hungry 7.    The 
power consumption of ADC is increased exponentially  when the quantization bits increase.8. To
overcome this problem  low resolution
ADCs get attention in last few years. The 1-bit ADC
is most attractive due to the lower

hardware complexity. In this scenario,
the in-phase and quadrature

components of the
continuous-valued received signals are

distinctly quantized using
simple zero-threshold comparators;

so that, there is no use for an
automatic gain controller(AGC) 9. while all ADCs have low resolution,
time-frequency syn-

chronization and channel
estimation are difficult and

require immoderate overhead  10

In 9

a mixed-ADC

receiver structure was proposed
for massive MIMO sys-

tems, wherein a fraction of the
ADCs has complete-resolution

to promote system overall
performance, and the others have low-

resolution in consideration of
the hardware price and power

consumption. In 10

the mixed-ADC receiver

was developed for multiuser
massive MIMO systems, in

which a circle of relatives of
Bayes detectors were developed by means of con-ducting Bayesian estimate of the
consumer indicators with preferred approximate message passing algorithm. by
way of analyzing  the general mutual
information (a beneficial lower bound on the channel capability with mismatched

. in12the evaluation of generalized

information has been emphasized
to illustrate

that the mixed-ADC architecture
is capable of obtain a massive

fraction of the channel
capability of best ADC architectures

over frequency-flat channels.


authors derived a closed-form
approximation of the

manageable rate of mixed-ADC
massive MIMO structures with

the MRC detector. These initial  works validate the deserves of

the mixed-ADC structure for
massive MIMO systems 13.

System model

In this paper, we suppose R number of
antennas at BS station of single cell Massive MIMO system and U number of users
with single antenna 14.



Fig. 1.
System model of joint-ADC massive MIMO receivers with

 high-resolution ADCs, Intermediate-resolution
ADCs and low-resolution ADCs.

The power consumption and the hardwire cost
is linearly with number of antenna’s. In fig.1 we introduce a joint Massive
MIMO architecture rather than using high resolution ADCs. In the

Joint-ADC architecture,
there are three different groups of RF chains. One group is connected with high
resolution ADCs, second with intermediate resolution and third with low
resolution ADCs.

the power consumption of the receiver is
precipitated by means of the RF chain and the baseband processor. The local
oscilator (LO) that is used with a mixer to alternate the frequency of a signal
is shared by using all RF chains. furthermore, each RF chain is composed of a
low-noise amplifier (LNA), and the LO buffer. The in-phase and quadrature
circuit consist of a mixer which includes a quadrature hybrid coupler, an ADC,
and an automatic gain control (AGC), respectively, observe that the AGC is used
to amplify the obtained signal to use the overall dynamic range of the ADC. the
usage of one-bit ADCs can simplify the RF chain, e.g., an AGC isn’t

important due to the fact only the signal of
the input signal is output 2

   Receiver has W antenna
elements. However, only H antennas
are connected to the full-resolution ADCs, I  antennas are connected

to the intermediate-resolution
ADCs and  L antennas are connected to the
low-resolution ADCs.


Let G be the W×U channel matrix
from the users to the BS. The channel matrix is modeled





 contains the fast-fading
coefficients, whose entries that are independent For ease of expression, we

G =

 T , where

 is the  

× u channel matrix

from the users to the  

 BS antennas with
full-resolution ADCs,

 is the  

× u channel matrix

from the users to the  

 BS antennas with
full-resolution ADCs and

 is the

×u channel matrix
from the users to the  

BS antennas with low-resolution ADCs.

Let pu be the average
transmitted power of each user and x be the u×1 vector of

symbols. The received signals at
the full-resolution ADCs can be given by

Signal at the receiver is given as






Signal   at AGC is defined as




Amplitude AGC gains pi can be
conveniently collected in a

diagonal matrix  




            The q represented by the
quantization noise ,where b is represent quantization bits.                                          







Signal after ADCs of  three different groups is received as










 The overall signal received after passing
through maximum ratio combining (RMC) is given by






For prefect channel state information CSI
and signal received after MRC at BS           


By  (9)  it
can be expressed as



x+ (

) + (



The received
signal-to-interference-plus-noise ratio (SINR) of the kth stream for MRC
is given by expression:








achievable sum rate

 is expressed as




By using eq  (11 ) Spectral efficiency is derived as



consumption model


 First consider a general power consumption

of the joint-ADC architecture. The
energy efficiency (EE) is

defined as

 bit / Joule,                 (15)


denotes the sum rate, W denotes the transmission

bandwidth assumed to be 1 GHz and Ptotal is the total





the power consumption
of local oscillator, mixer, AGC, high-resolution, intermediate-resolution  and low resolution ADCs respectively. In addition, f is

the flag  associated to the quantization bit of
low-resolution ADCs

and is given by




Furthermore, the power consumed in the
ADCs can be

expressed in terms of the number of
quantization bits as

,            (17)


where fs is the Nyquist
sampling rate, b is the number of

quantization bits, and

is Walden’s figure-of-merit for

evaluating the power efficiency with
ADC’s resolution and

speed. With state-of-the-art

technology, the power consumption
value of FOMW
at 1

bandwidth is  

= 5

15 fJ/conversion-step 15.


Fig:2 power
consumption  of joint-ADC massive MIMO
systems over Rician     fading channels
for K = 10 dB,  and pu = 10 dB.



Fig:3  Energy efficiency of joint-ADC massive MIMO
systems against different ADC quantization bits for K =10
dB, and pu
= ?10 dB.

The first insight obtained from Fig.2 is
that the joint- ADC structure requires more power than the only with pure
low-resolution ADCs, however with a exceedingly massive increase within the
achievable rate for small quantization bits. in addition,  the distance of power consumption decreases
with the increasing ADC’s resolution. For the joint-ADC structure, the
attainable rate significantly will increase while the quantization bit will
increase from 1 to 4, with a negligible increase in the receiver power
consumption. but, the power consumption will increase significantly whilst the
quantization bit going from 4 to 11 bits. This means the joint-ADC architecture

obtain a better trade-off between the
power consumption and

achievable rate via the usage of
different bits.

It’s far clean from Fig. 3 that the
premier ADC quantization bit is encouraged by using both the part of high-resolution
ADCs and the Rician k-element. For the joint-ADC architecture, the energy
efficiency simplest increases up to a certain wide variety of quantization
bits, while it decreases at higher ADC quantization bits. this is because of
the reality that the plausible charge is a sub-linear increasing feature of the
quantization bits, while the power consumption of ADCs will increase
exponentially with b.


Fig:4  Sum achievable rate of
joint-ADC massive MIMO systems over Rician fading channels against the ADC
quantization bits and pu = 10 dB.


Fig: 5 
Energy efficiency of joint-ADC massive MIMO systems over

Rician fading channels against
different numbers of antennas for K=10 dB 
and pu
= 0 dB.


Fig. 4 gives the simulated and sum

rate of joint-ADC massive MIMO
structures for diverse

numbers of ADC quantization bits. Without
lack of generality,

we count on that all customers have
the identical Rician k-aspect as

Kn = k. The simulation outcomes
extensively coincide with the

derived outcomes for all ADC
quantization bits. We also locate

from Fig. 4 that better sum charge can
be performed by way of using

extra high-resolution ADCs. moreover, the

rate increases with the range of
quantization bits (b), and

converges to a constrained manageable
rate with high-resolution

ADCs. For Rayleigh fading channels (k
= zero), the joint-

ADC structure can achieve the same sum
viable charge by

using 5 bits, at the same time as for
Rician fading channels (k = 10),

extra ADC quantization bits are
wished, that’s in settlement

with statement 1. This is genuine due
to the fact the quantization noise is large with greater received power in LoS
dominating scenarios.


In Fig. 5, we analyze the impact of
the quantity of receive

antennas on the strength efficiency.
because of the truth that each antenna is attached with one RF chain, it may be

to apply greater antennas at the BS.
The Energy Efficiency(EE) of

low-resolution ADCs is biggest among
others. indeed, if the

BS has simplest around 30 antennas,
the joint-ADC structure

achieves its most appropriate power
performance for the deciding on system.





in this paper, the overall performance
of joint-ADC massive MIMO systems over Ricin fading channels is investigated.
We derive closed-shape approximate expressions for the achievable rate for
massive-antenna limit. The cases of perfect are incorporated in our analysis.
With similar hardware cost, the joint-ADC structure can acquire larger sum rate
than the ideal-ADC architecture. we conclude that realistic massive MIMO can
achieve a considerable performance with small power consumption by adopting the
joint-ADC structure for 5G.

We conclude that the joint-ADC
structure can carry most of the favored overall performance enjoyed through
massive MIMO receivers with complete perfect-resolution ADCs. A parameterized
evaluation of energy efficiency within the uplink of a massive MIMO system with
varying ADC bit resolutions at the base station has been carried out. system
setup and models have been selected with the purpose of being close to
practical system implementations. consequences suggest that using ADCs with
very low bit resolutions is not an premiere technique from energy efficiency
factor of view, except for highly unique system architectures. instead, for a
wide form of systems, ADCs with joint bit resolutions (1 – 11 bits) are shown
to maximize system energy efficiency.

 Further, the joint-ADC architecture may have a
large working area with few high-decision ADCs. more energy efficiency may be
executed when operating over stronger LoS situations.




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