uhf-rfid wireless control system modeling and...

215 Khomdram Jolson Singh, Dhanu Chettri, Th. Jayenta Singh

International Journal of Electronics, Electrical and Computational System

IJEECS

ISSN 2348-117X

Volume 6, Issue 3

March 2017

ABSTRACT

This Paper presents the analysis and simulation of UHF RFID

system in Matlab/Simulink environment. The simulation is

divided into the transmitter, channel and receiver part. Some

Negative effects are concerned in the system model, such as

phase noise, reflection of the environment, AWGN noise, I/Q

mismatch, etc. The architecture of the model is described in

details, and is flexible to achieve different modulation and

encoding types. Finally, the results of the simulation are

presented and analysed. These result will be very helpful for the

further development work of RFID system.

Index Terms— RFID, ASK, Manchester coding, Gaussian

noise, modelling and simulation.

I. INTRODUCTION

ost of the Radio Frequency Identification (RFID)

systems used radio frequency to automatically

identify products. RFID system consists of two

modules namely Reader and Tag. The different

frequencies used for transmission are classified into the

four basic ranges, LF (low frequency, 100-500 KHz), HF

(high frequency 1-400 MHz), UHF (Ultra high frequency,

850-950 MHz) and microwave (1-5.8 GHz). For LF and

HF RFID, the scan distance is upto 10 cm and 1 m

respectively. For microwave RFID, because of the

sensitivity to the environment, the maximum reader range

is about 10 m. For UHF RFID, the read range can

generally reach to 7 m. Further, the RFID system can be

classified into active RFID (Tag with battery) and passive

RFID (Tag without battery). In this paper, we discuss only

the passive UHF RFID system. For a passive RFID, first

the Reader should send out electromagnetic waves to

wake-up the Tag, and then transmit the modulated wave to

command Tag. A passive tag absorbs power from the field

created by the reader and uses it to power the microchip's

circuits. Then Reader transmits continuous wave (CW),

while Tag backscatters the information. There are many

protocols about UHF RFID, in this paper, the simulation is

mainly based on EPC Class 1 and EPC Class 1 Generation

2 UHF RFID (abbreviate as Gen 2) protocols.

Figure 1 A complete generalized RFID system

II. MODELLING AND SIMULATION

The following figure shows a block diagram of our

model

Figure 2 Schematic of RFID simulink Model

The Simulink® platform developed by MathWorks was

used to build our models. The input data consists of binary

1s and 0s, which are modulated using amplitude shift

keying (ASK). The signal power level can be adjusted, and

the signal attenuation due to orientation or distance can be

varied. Environmental noise is modeled in terms of

random Gaussian noise. The signal that traverses the

transmission channel is subsequently decoded to form the

received signal.

For the first set of simulation runs, the data is coded using

NRZ coding and later by Manchester coding. The data

sent and received are compared and the number of tags

read correctly determined, thereby obtaining the read

reliability under the varying factors.

In this paper, a system model is developed with some

simulation results. At first, the simulation model is

introduced briefly. Models of DSP, transmitter and

wireless channel, front-end of tag and receiver model are

introduced. Finally,

UHF-RFID Wireless Control System Modeling and

Simulation

M

Khomdram Jolson Singh, and Dhanu Chettri and Th. Jayenta Singh Department of Electronics and Communication Engineering, Manipur Institute of

Technology, Takyelpat, Imphal, Manipur, INDIA



IJEECS

ISSN 2348-117X

Volume 6, Issue 3

March 2017

Figure 3 Complete RFID system design in SIMULINK

some simulation results are presented. There are some

critical problems to be discussed. The raised cosine filter

affects the spectrum of the output, and the parameters

should be handled carefully. The SSB transmission is not

very ideal from the simulation results since a finite length

of data is processed. In receiver of reader, the suppression

of DC offset and transient response may drive the follow-

up circuits into saturation. The bandwidth of channel

select filters is also important because it is related to noise

floor. Baseband circuits, variable gain stage and detector

of receiver are also challenges. The reflection of the

objects in environment will mainly affect the operation of

tag, and special attention should be paid to diminish the

effect of Fresnel zones. All the problems mentioned above

should be solved in further study and cost much of efforts

to get a best performance. The system simulation is

focused on reader side with a simple wireless channel and

a simple reflection model of tag for evaluating the

performance of reader. More complicated models should

be constructed in frequency domain simulation to

determine and optimize the parameters of building blocks

of reader and tag.

A. Transmitter

When you Forward Link Encoding. In both the Class

1 and the Gen 2 protocols, binary data from Reader to Tag

is encoded as Manchester Encoding of the low amplitude

pulse.

Figure 4 Subsytem of Reader showing Demodulator for

RX and different Carrier signals used for TX.

B. Encoding

Data embedded within RFID tags consists of n bits of

data, with each bit either a binary 1 or 0. Some of the

frequently used encoding for the transmission of binary

data includes Unipolar, NRZ, Unipolar RZ, Bipolar and

Manchester coding. Presently, the data stored in RFID tags

are typically coded using Unipolar (also commonly known

as on-off keying), polar, Unipolar return-to-zero, or

Manchester coding (as shown in the figure below).

Some methods of encoding are better than others in

terms of error detection. The superiority of the Manchester

coding as compared to the NRZ coding is evident in the

case of a collision. Consider a tag using the NRZ

encoding. Transponder 1 transmits the bit stream

10110010, while transponder 2 transmits 10011100. The

signal received by the signal is 10111111, which does not

correspond to either of the bit streams transmitted by

transponder 1 or 2. The reader is not aware that an error

has occurred - undetectable collision has occurred.

Figure 5 Different types of coding

If Manchester encoding was used instead, collisions

might result in a steady state period. As transitions have to



IJEECS

ISSN 2348-117X

Volume 6, Issue 3

March 2017

occur in Manchester encoded signals, the steady state

period that results is an indication that an error has

occurred.

Figure 6 Detection of collision

Figure 7 Subsystem model for Manchester Encoding

Figure 8 Waveforms of Binary ID input signal and its

Manchester Encoded signal.

Figure 9 Power Spectral Density (PSD) of the

Manchester Encoded Signal

C. Modulation

In Class 1 protocol, the reader shall communicate with

the tag by Amplitude Shift Keying (ASK) modulation, and

the modulation depth is from 30% to 100%. In Gen 2

protocol, the reader shall use double-sideband amplitude

shift keying (DSB-ASK), single-sideband amplitude shift

keying (SSB-ASK) or phase-reversal amplitude shift

keying (PR-ASK), and the modulation depth is from 80%

to 100%. By the architecture of the simulation model, it

can implement all these modulation types.

Figure 10 Complete waveform obtained from the ASK

modulator used in our RFID system model

D. Reciever

Return Link Encoding: In Class 1 protocol, Tags reply

to Reader commands with backscatter modulation with the

encode form shown in below, where two transitions are

observed for a binary zero and four transitions are

observed for a binary one during one Bit Cell. In Gen 2

protocol, Tags shall encode the backscattered data as

either FM0 baseband or Miller modulation of a subcarrier

at the data rate. The Reader selects the encoding type

Figure 11 Demodulator subsystem Model with Digital

Filter for RX in reader

Figure 12 Direct Form Digital FIR filter design used

for final Tag ID recovery.



IJEECS

ISSN 2348-117X

Volume 6, Issue 3

March 2017

Figure 13 Different waveforms showing the recovery of

Tag ID from ASK Modulated Signals.

III. CALCULATIONS

A. Free Pass Loss

Free Space Path Loss. In telecommunication, free-space

path loss (FSPL) is the loss in signal strength of

an electromagnetic wave that would result from a line-of-

sight path through free space (usually air), with no

obstacles nearby to cause reflection or diffraction. It does

not include factors such as the gain of the antennas used at

the transmitter and receiver, nor any loss associated with

hardware imperfections.

The formula of the free space pass loss is

)(lg20)(lg2045.32)( KmdMHzfdbLs

Where „f‟ is the carrier frequency „d‟ is the distance

between Reader and Tag.

Figure 14 Inside the communication channel system

model with different noises such as AWGN and Free

Space Path Loss

A convenient way to express FSPL is in terms of dB

))4

((log10)( 2

10 dfc

dBFSPL

)4

(log20 10 dfc

)4

(log20)(log20)(log20 101010c

fd

55.147)(log20)(log20 1010 fd

Where the units are as before.

For typical radio applications, it is common to find f

measured in units of GHz and d in km, in which case the

FSPL equation becomes

45.92)(log20)(log20)( 1010 fddBFSPL

For fd, are in meters and megahertz, respectively, the

constant becomes 55.27

B. Additive white Gaussian noise (AWGN)

It is a channel model in which the only impartment to

communication is a linear addition of wideband or white

noise with a constant spectral density (expressed as watts

per hertz of bandwidth) and Gaussian distribution of

amplitude. The model doesn‟t account for fading,

frequency selectivity, interference, linearity or dispersion.

However, it produces simple and tractable mathematical

models which are useful for gaining insight into the

underlying behavior of a system before these other

phenomena are considered.

Signal to noise ratio (SNR), where the block calculates the

variance from these quantities that you specify in the

dialog box:

SNR, the ratio of signal power to noise power

Input signal power, the actual power of the samples at the

input of the block

Changing the symbol period in the AWGN Channel block

affects the variance of the noise added per sample, which

also causes a change in the final error rate.

For complex input signals, the AWGN Channel block

relates Eb/N0, Es/N0, and SNR according to the following

equations:

Es/N0 = (Tsym/Tsamp) · SNR

Es/N0 = Eb/N0 + 10log10(k) in dB

Where

Es = Signal energy (Joules)

Eb = Bit energy (Joules)

N0 = Noise power spectral density (Watts/Hz)

Tsym is the Symbol period parameter of the block in Es/No

mode

k is the number of information bits per input symbol

Tsamp is the inherited sample time of the block, in seconds.

For real signal inputs, the AWGN Channel block relates

Es/N0 and SNR according to the following equation:

Es/N0 = 0.5 (Tsym/Tsamp) SNR

C. Backscatter

In the return link, Tag communicates with the Reader by

backscatter modulation. During backscatter Reader

transmits an un-modulated continuous wave (CW) signal,



IJEECS

ISSN 2348-117X

Volume 6, Issue 3

March 2017

then Tag modulates its reflection of the CW signal. In

Class 1 protocol, Tag modulates the amplitude of the

carrier (ASK). In Gen 2 protocol, Tag modulates the

amplitude and/or phase of the carrier (ASK and/or

PSK).Modulation of the backscattered wave is achieved

by changing the tag IC‟s input impedance between two

different states ZR_jX and ZR _ jX.

For ASK, it is achieved by a change in the real part of the

impedance and of the reflection coefficient. And PSK is

achieved by changing the imaginary part of the input

impedance and of the reflection coefficient. In this paper,

it will only discuss the ASK case.

D. Tag Received Power

In forward link, the output power is

TXPAEIRP GPP

The Effective Isotropic Radiated Power (EIRP) of the

reader is PEIRP. The typical maximum output power is

500mW, 2W (ERP, CEPT) and 4W (EIRP, FCC).

Converted to dBm, the permitted maximum limits are

about 29dBm (500mW ERP, 825mW EIRP), 35dBm (2W

ERP, 3.3W EIRP) and 36dBm (4W EIRP). GTX is the

gain of the transmitter antenna. The typical value is

assumed to be 6dBi. Therefore, the maximum output

power from power amplifier should be 23dBm, 29dBm

and 30dBm, respectively.

The power transmitted from reader to tag can be expressed

as

22 )4

()4

(d

GPd

GGPP tagEIRPtagTXPArec

λ is the wavelength of the carrier. d is the distance from

reader to tag.

E. Tag Reflection Model

As we all know, tag received power includes two parts, the

reflected power and the available power can be used by

the chip. The distribution of these, two parts is very

critical for a maximum distance. In [7]

a detail calculation is performed.

The available power from antenna can be used by the

rectifier is

2,,21,,1, inRFinRFinRF PpPpP

)]||1()||1([8

2

22

2

11

2

0 ppR

v

ant

The reflect power is

radbs RiiP 2

21 ||8

1

0v is the peak source voltage that would be observed if the

antenna were not loaded by the IC. In time domain, the

probabilities that chip in state 1 and state 2 are p1 and p2.

ρ1, 2 are the reflection coefficients. Rant is the real part of

the antenna impedance. 21 & ii are the current flow

through the impedance. radR is radiation impedance of

antenna.

Figure 15 RFID Tag Subsystem

F. Demodulation

As analysis above, the Tag reflection power is much

weaker than the Reader transmit power, and Reader

transmits CW signal

IV. RESULT AND DISCUSSION

As shown above, the IDs are well recovered from the

noisy Manchester code stream. Comparing with the source

IDs, the recovered just have a time delay. In the

simulation, we adjusted the noise power in the model to

obtain the Bit Error Rate (BER) by the Error Rate

Calculation block. Their results (not shown in this thesis)

indicate that when the SNR >=1:0 dB, the BER is still

zero, which implies a good performance of the simulation

proposed in this thesis.

Figure 16 Comparison of Transmitted ID data with

Recovered ID Data.

Figure 7 Close-Up Waveform of Recovered ID Data

showing a small phase delay from transmitted Id data.

V. CONCLUSION

An UHF passive RFID system have been designed and

simulated using Matlab/Simulink environment. Some

Negative effects such as phase noise, reflection of the

environment, AWGN noise, I/Q mismatch etc. are also



IJEECS

ISSN 2348-117X

Volume 6, Issue 3

March 2017

taken into account in the system model. The architecture

of the model is described in details which is flexible to

achieve different modulation and encoding types. Finally,

the results of the simulation are presented and analysed.

These result will be very helpful for the further

development work of RFID system.

REFERENCES

[1] MIT Auto-ID Center Publications:

http://www.autoidcenter.org

[2] Daniel W. Engels, “The Reader Collision Problem”, MIT-

AUTOID-WH 007

[3] EPC Radio-Frequency Identity Protocols Generation 2

Identity Tag (Class 1): Protocol for Communications at

860MHz-960MHz. EPC Global Hardware Action Group (HAG),

EPC Identity Tag (Class 1) Generation 2, Last-Call Working

Draft Version 1.0.2, 2003-11-24

[4] John G. Proakis, “Digital Communications (Fourth

Edition)”, McGraw-Hill Companies, Inc, 2001

[5] Behzad Razavi, “RF Microelectronics”, Prentice Hall, Inc.

1998

[6] David Johns, Ken Martin, “Analog Intergrated Circuit

Design”, John Wiley & Sons, Inc, 1997

[7] Udo Karthaus，Martin Fischer，“Fully Integrated Passive

UHF RFID Transponder IC With16.7-uW Minimum RF Input

Power”， IEEE Journal of Solid-State Circuits, Vol.38, No. 10,

October 2003.

[8] The Palomar system Deliverable D7, Version V2.1,2002

[9] European Standard (Telecommunications series),

“Electromagnetic compatibility and Radio spectrum Matters

(ERM); Radio Frequency Identification Equipment operating in

the band 865MHz to 868MHz with power levels up to 2W; Part

1: Technical requirements and methods of measurement”, Draft

ETSI EN 302 208-1 V1.1.1, 2003-

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