Analysis

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

Abstract

The sensible

implementation of massive multiple-input

multiple

-output (MIMO) inside the fifth

generation (5G)

wireless

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

consumption.

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

analog-to-digital

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.

Furthermore,

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

MIMO

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

ADCs

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

architecture

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

decoding)11

. in12the evaluation of generalized

mutual

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.

The

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

as

1

(1)

Where

contains the fast-fading

coefficients, whose entries that are independent For ease of expression, we

denote

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

information

symbols. The received signals at

the full-resolution ADCs can be given by

Signal at the receiver is given as

(2)

(3)

Signal at AGC is defined as

(4)

Amplitude AGC gains pi can be

conveniently collected in a

diagonal matrix

(5)

The q represented by the

quantization noise ,where b is represent quantization bits.

Signal after ADCs of three different groups is received as

=

(6)

=

(7)

=

(8)

The overall signal received after passing

through maximum ratio combining (RMC) is given by

(9)

For prefect channel state information CSI

and signal received after MRC at BS

R=

By (9) it

can be expressed as

R=

x+ (

) + (

(10)

The received

signal-to-interference-plus-noise ratio (SINR) of the kth stream for MRC

is given by expression:

(11)

¥=

+

+

(12)

The

achievable sum rate

is expressed as

(13)

By using eq (11 ) Spectral efficiency is derived as

i

(14)

Power

consumption model

First consider a general power consumption

model

of the joint-ADC architecture. The

energy efficiency (EE) is

defined as

bit / Joule, (15)

where

denotes the sum rate, W denotes the transmission

bandwidth assumed to be 1 GHz and Ptotal is the total

consumed

(15)

Where PLO,PLNA,PH,PM,PAGC,PH ADC,PLADC,PBB

denote

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

(16)

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

GHz

bandwidth is

= 5

15 fJ/conversion-step 15.

Results:

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

can

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

achievable

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

achievable

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

wasteful

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.

conclusion:

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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