IJCSNS International Journal of Computer Science and Network Security, VOL.23 No.5, May 2023

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Channel Transfer Function estimation based on Delay and Doppler
Profiler for 5G System Receiver targeting 500km/h linear motor car
Suguru Kuniyoshi1), Shiho Oshiro2), Gennan Hayashi3) and Tomohisa Wada4)
1) Magna Design Net Inc., 3-1-15 Maejima, Naha-shi, Okinawa, Japan
2) Information Technology Center, University of the Ryukyus, Okinawa, Japan
3) Graduate School of Engineering and Science University of the Ryukyus, Senbaru 1, Nishihara, Okinawa, Japan
4) Dept. of Engineering, University of the Ryukyus, Senbaru 1, Nishihara, Okinawa, Japan
Summary
A 500 km/h linear motor high speed terrestrial transportation
service is planned to launch 2027 in Japan. In order to support 5G
service in the train, the Sub-carrier spacing frequency of 30 kHz isplanned to be used instead of common 15 kHz sub-carrier spacing
to mitigate Doppler effect in such high-speed transportation.
In addition, to increase the cell size of 5G mobile system, pluralBase Station antenna will transmit the identical Down Link (DL)signal to form the expanded cell size along the train rail. In thissituation, forward and backward antenna signals will be Doppler
shifted by reverse direction respectively and the receiver in thetrain might suffer to estimate accurate Channel Transfer Function(CTF)
foritsdemodulation.
In this paper, Delay and Doppler Profiler (DDP) based Channel
Estimator is proposed and it is successfully implemented in signal
processing simulation system. Then the simulated performances
are compared with the conventional Time domain linear
interpolated estimator. According to the simulation results, QPSK
modulation can be used even under severe channel condition suchas 500 km/h, 2 path reverse Doppler Shift condition, although
QPSK modulation can be used less than 200 km/h withconventional Channel estimator.

Keywords:
5G, 5th Generation Mobile Communication System, Channelestimation

I.

Introduction

A 500 km/h linear motor high speed terrestrial
transportation service is planned to launch 2027 between
Tokyo and Nagoya in Japan. The maximum speed ofcurrent high speed train Shinkansen is 300 km/h.
However, the coming linear motor train’s speed will be
500 km/h by using magnetic levitation mechanism. Inorder to support 5G service in the train, 5G will use somedifferent configurations. First, increased sub-carrier
spacing f0 of 30 kHz is used instead of conventional 15
kHz to mitigate Doppler frequency shift. This change
automatically shortens OFDM symbol length by half.
Consequently, channel state change tracking
performance will increase. Second, to increase mobile
Manuscript received May 5, 2023
Manuscript revised May 20, 2023
https://doi.org/10.22937/IJCSNS.2023.23.5.14

Fig. 1: Two Down Link receiving situation in the high-speed train

service cell size, plural Base Station antennas transmit
the identical Down Link (DL) signal to form theexpanded cell size along the train rail. In this situation,
forward and backward antenna signals will be Doppler
shifted by reverse directions respectively and thereceiver in the train might suffer to estimate accurate
Channel Transfer Function (CTF) for demodulation. Fig.
1 shows the situation of two Down Link (DL) reception
in the car. Approaching TX1 antenna signal is +fd shiftedand backward TX2 signal is -fd shifted.
In this paper, in order to improve the receiver
performance, Delay and Doppler Profiler (DDP) based
estimation method of Channel Transfer Function (CTF),
which varies along with the train movement, is applied.
In section II, first, targeting 5G Mobile Communication
System is briefly shown. Then the proposed DDP method isexplained. Computer simulation results are shown insection III. Finally, in section IV, the conclusions will begiven.

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Table 1: 5th Generation Mobile Communication System Parameters

Parameters

Value

System Band Width

100 MHz

Sub-carrier Spacing (f0)30 kHzPass Band Frequency

3.9 GHz

OFDM symbol length (T)Number of CommonResource Blok (CRB)
Number of Sub-carriers

33.33 us (4096 points)

Sampling Frequency (Fs)

122.88 Msps

FFT size4096

CP length352 or 288 points

II. 5G Mobile
Architecture2733276

CommunicationSystem

5th Generation Mobile Communication System [1] is
OFDM communication system standard developed as
the successor to the 4G system with variousenhancements. For example, the sub-carrier spacing wasfixed as 15kHz in 4G but in 5G variable sub-carrier
spacing is supported such as 15 / 30 / 60 / 120 / 240 kHz.
For the application of the linear motor train, 30 kHz subcarrier frequency will be used for RF Carrier of 3.9 GHz
Band. Table I summaries the 5G system parameters forthis application. To support eMBB (enhanced MobileBroadband), 100MHz bandwidth is assumed with 3276
sub-carriers. Because of sub-carrier spacing f0 of 30 kHz,OFDM symbol length T of 33.33us (4096 samplingpoints) is used.
Fig. 2 shows the 5G Frame structure for f0 of 30 kHz.
10 ms Frame is divided into 20 Slots. In one Slot, 14
OFDM symbols are embedded. Cyclic prefix (CP) lengthis 288 sampling points for each 4096 points OFDMsymbols except the 1st CP. The length of the 1st CP is alittle expanded such as 352 points. In 5G system,Demodulation Reference Signals (DMRS) are inserted toFig. 2: 5G Frame structuresome Sub-carriers to measure Channel Transfer Function(CTF) and the DMRS can be placed with a high degreeof freedom according to the system configuration. Thistime, DMRS is asserted in S3, S6, S9, S12 OFDM
symbols to detect rapidly time-domain changing CTF [2].
Time-Frequency structure of this 5G system is shown inFig. 3. Since 12 sub-carriers and 14 OFDM symbols
constitute one Common Resource Block (CRB), the total
3276 sub-carriers correspond to 273 CRBs. The detail ofsub-carrier arrangement in a CRB is also shown in thefigure. For frequency direction (vertically), DMRS areplaced every 2 sub-carriers as shown in the odd numberplaces. Sub-carriers at the odd number in S3, S6, S9, S12
OFDM symbols are empty, although those empties might
be used for MIMO configurations system with multiple
antennas.

Fig. 3: Time-Frequency structure of SystemA)

Physical layer of 5G communication system

Fig. 4 shows the block diagram of the Physical Layer(PHY) for 5G SISO (Single Input Single Output) system.
The upper side is the transmitter and the lower side is thereceiver. The Bit Data, which are provided from theupper MAC, Protocol and Application layer, are digitalmodulated at Symbol mapper by QPSK / 16QAM / 64
QAM / 256 QAM. Then the modulated symbols andDMRS pilots signals configure Slots as shown in Fig. 3.
Then Inverse 4096 points Fourier Transform (IFFT) isperformed as OFDM modulation and Cyclic Prefix (CP)IJCSNS International Journal of Computer Science and Network Security, VOL.23 No.5, May 2023

Fig. 4: Physical layer of 5G communication system

is appended. This signal is Baseband (BB) signal. By
applying up-conversion to BB signal, path-band signal isgenerated then emitted through power amplifier andantenna.
The receiver side performs basically the reverse processof the transmitter. However, since the receiving signal isdistorted through the propagation channel, Channel
Transfer Function (CTF), which is a Frequency domain
representation of Channel Impulse Response in Timedomain, has to be estimated and the distortion has to becompensated at Equalizer using the estimated CTF. Thenthe accuracy of the CTF estimation greatly influence tothe receiver error performance. In conventional 5G
receiver, the measured CTF values at the DMRS position
are interpolated in Frequency and Time domain to get all
sub-carrier position CTF. In order to improve CTF
estimation, this paper studies new method such as Delayand Doppler Profiler based all CTF estimation.
B)

Improved Channel Transfer Function estimation
based on Delay and Doppler ProfileReferences [3-5] describe detail methods of Delay andDoppler Profile (DDP) based CTF estimation using pilot
signals embedded in OFDM sub-carriers. Fig. 5 is a123

block diagram of proposed DDP CTF generation. Theupper side of the figure represents the Time-Frequency
structure of sub-carriers with time-domain symbol index
k. The DDP estimates each Np multipath component
waves to receiving antenna. Each analyzed component
can be characterized using three parameters such as
Attenuation 𝑟 , Propagation Delay time 𝜏 , andnormalized Doppler shift 𝛼 for wave component index i.
Here the Attenuation 𝑟 is complex value including
amplitude attenuation and phase rotation and thenormalized Doppler shift is normalized by sub-carrier
𝑓𝑑 /𝑓 . Using the symbol k
spacing f0 such as 𝛼measured CTF(k) and symbol k-3 measured CTF(k-3),
the DDP detects Np sets of those three parameters. Using
those parameters, all position CTF ℎ 𝑘, 𝑙 can becalculated as Equation (1). Here, 𝑘 is symbol number, 𝑙is sub-carrier index, N is the FFT size, 𝑁 is the total
number of delay paths, 𝑇 is the sum of OFDM symbol
length and CP length.
1 sin 𝜋 𝛼𝜋 𝛼𝑁sin 𝑁ℎ 𝑘, 𝑙𝑒𝑒𝑟𝑒⋯ 1Once Delay and Doppler profile parameters are known,by changing the symbol number 𝑘 , CTF at different
times can be generated.
The method of obtaining the parameters in each delay
path by DDP is detailed in references [3-5], but now
DMRS pilots are inserted at symbol numbers 𝑘 and 𝑘
3. Consider the following estimated evaluation function
𝐸 𝑘 . CTF is measured at DMRS pilots, ℎ is the channeltransfer function to estimate by minimizing 𝐸 𝑘 .
Summation range 𝑃 corresponds sub-carrier indexes onDMRS positions.
𝐸 𝑘|𝐶𝑇𝐹 𝑘, 𝑙ℎ 𝑘, 𝑙 ||𝐶𝑇𝐹 𝑘3, 𝑙ℎ 𝑘

3, 𝑙 |⋯ 2First, the maximum power delayed wave is detected byminimizing the following equation.
𝐸 𝑘

𝐶𝑇𝐹 𝑘, 𝑙
𝐶𝑇𝐹 𝑘𝑓 𝛼 𝑒Fig. 5: Delay and Doppler Profiler based CTF estimator𝑓 𝛼 𝑟𝑒3, 𝑙𝑟𝑒… 3

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Table 2: Simulation Parameters

where 𝑓 𝛼 is given by𝑓 𝛼

1 sin 𝜋 𝛼𝜋 𝛼𝑁sin𝑁𝑒𝑒… 4According to [3-5], 𝑟 , 𝜏 , and 𝛼 can be obtained byminimizing 𝐸 𝑘 . This yields the channel transfer
function of the first pass (i=1) according to equation (1).
By subtracting the obtained channel transfer function of
the first pass from the measured CTF, remaining CTF
value can be obtained, and the same calculation isperformed to obtain the parameters of the second pass.
By repeating the above calculations 𝑁 times, allparameters for each pass can be obtained. Once theparameters of all 𝑁 paths are known, all CTF such asℎ 𝑘, 𝑙 according to equation (1) can be synthesized, andby varying the symbol number 𝑘 , channel transfer
functions corresponding to 𝑘 from 𝑘 5 can beobtained.

III. Computer Simulations
Since the actual test environment is not yet available,
computer simulations were used to simulate theenvironment. Fig. 6 shows a computer simulated runninglinear motor train situation. Nearby Base Station (gNB:g Node B in 5G notation) antennas are located from thetrain rail by D (m). In a Single Frequency Network (SFN),
the same DL signal is transmitted from antennas indifferent each gNBs. Communication area is assumed
then The distance of two antennas is 300 m between
gNBs. Assuming the location of the reception antenna asXr(t) of horizontal x-axis as shown in the figure. Thedistances between two antennas and the receiver antenna
are L1(t) and L2(t) as shown in the figure (Fig. 6).
More detail of simulation parameters is listed in Table
2. Assumed Radio passband frequency is 3.9 GHz. In thesimulation, moving train will start receiving 4 frames ofDL signal with Xr(t=0) = -50 m. Path1 DL signal comesfrom forward antenna with varying length L1(t) withrelative amplitude gain = 1.0. Path2 DL signal comesfrom backside with L2(t) distance with relative

Fig. 6: Simulated vehicle moving situation

Parameters

Value

RF pass band frequency

3.9 GHzQPSK / 16QAM /64QAM / 256QAM
0 km/h ~ 500km/h,(100km/h step)
Add to AWGN
-10 dB ~ 50 dB,(1 dB step)
4 Frames(40 ms, 80 slots)
90 CRBs(1080 Sub-carriers)
SISO, 2 Paths,
Single Frequency Network
Distance = ~50m
Amp gain = 1.0
Distance = ~250m
Amp gain = 0.5D=2m

Modulation
RX moving speed
CNR
Number of Frames
Used number of CRBs
ChannelPath1 (L1(t))
Path2 (L2(t))
Antenna Distance (D)amplitude gain = 0.5. Bit Error Rate (BER) is measured
in lower frequency 90 CRBs as shown in Fig. 3.
The Bit Error Rate (BER) was obtained by adding
Additive White Gaussian Noise (AWGN) to the signal
received as a composite wave of the 2gNB-derived
Down Link (DL) signal, varying from -10 dB to 50 dB
in 1 dB steps.
Simulated results for QPSK / 16QAM / 64QAM /256QAM BER with Carrier to Noise Ratio (CNR) wereshown in Figs. 7-10. In each figure, (a) corresponds toconventional linearly interpolated CTF estimation and(b) corresponds to proposed DDR based CTF estimation.
Figs. 11-14 show BER vs train moving speed for QPSKwith CNR=16dB, 16QAM with CNR=23dB, 64QAM
with CNR=30dB and 256QAM with CNR=30dB.
Assuming BER below 1.0E-03 can be error correctablewith associated error correction mechanism, QPSKmodulation can be used even under severe channelcondition such as 500 km/h with 2 path reverse Doppler
Shift condition, although QPSK modulation withconventional Channel estimator can be used less than
200 km/h. For 16QAM modulation, roughly 150km/h
limitation is extended to double speed of 300km/h. For
64QAM case, the limitation speed is improved frombelow 100km/h to 150km/h. For 256QAM modulation,
only small improvement has been confirmed.

IJCSNS International Journal of Computer Science and Network Security, VOL.23 No.5, May 2023

(a) Conventional CTF Linear Interpolator(a) Conventional CTF Linear Interpolator(b) Delay and Doppler Profiler based CTF(b) Delay and Doppler Profiler based CTF

Fig. 7: BER vs CNR (dB) for QPSK modulation

Fig. 9: BER vs CNR (dB) for 64QAM modulation(a) Conventional CTF Linear Interpolator(a) Conventional CTF Linear Interpolator(b) Delay and Doppler Profiler based CTF(b) Delay and Doppler Profiler based CTF

Fig. 8: BER vs CNR (dB) for 16QAM modulation

Fig. 10: BER vs CNR (dB) for 256QAM modulation

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Fig. 11: BER vs Moving Speed for QPSK

Fig. 14: BER vs Moving Speed for 256QAM

IV. Conclusion

Fig. 12: BER vs Moving Speed for 16QAM

Delay and Doppler Profiler (DDP) based Channel
Estimator is proposed targeting 500km/h train supportand it is successfully implemented in signal processing
simulation system. Simulated performances arecompared with the conventional Time domain linear
interpolated estimator. According to the simulation
results, QPSK modulation can be used even under severe
channel condition such as 500 km/h, 2 path reverse
Doppler Shift condition, although QPSK modulation canbe used less than 200 km/h with conventional Channel
estimator. For 16QAM modulation, roughly 150km/h
limitation is extended to double speed of 300km/h. For
64QAM case, the limitation speed is improved frombelow 100km/h to 150km/h. For 256QAM modulation,
only small improvement has been confirmed.

References

Fig. 13: BER vs Moving Speed for 64QAM[1] 3GPP TS38.211 V17.4.0 : “3rd Generation Partnership
Project; Technical Specification Group Radio AccessNetwork; NR; Physical channels and modulation” Dec.
2022.
[2] Erik Dahlman, Stefan Parkvall, Johan Sköld (2021). 5G
NR THE NEXT GENERATION WIRELESS ACCESSTECHNOLOGY SECOND EDITION. Academic Press.
[3] Mitsuru Nakamura, Makoto Itami, Kohji Itoh andHamid Aghvami, “ICI Cancellation Technique basedon Estimating Delay and Doppler Profile in OFDM
Reception,” The Institute of Image Information andTelevision Engineers, Vol. 56, No. 12, pp.1951-1958(2002).
[4] Mitsuru Nakamura, Masahiro Fujii, Makoto Itami andKohji Itoh, “MMSE ICI Canceller for OFDM Mobile

IJCSNS International Journal of Computer Science and Network Security, VOL.23 No.5, May 2023
Reception,” The Institute of Image Information andTelevision Engineers, Vol. 58, No. 1, pp.83-90 (2004).
[5] Akito Yamazaki, Mitsuru Nakamura, Masahiro Fujii,
Makoto Itami, Kohji Itoh and Hiroki Ohta, “A Studyon Improving Performance of an OFDM ICI Canceller,”
The Institute of Image Information and Television
Engineers, Vol. 58, No. 1, pp.94-101 (2005).

Suguru Kuniyoshi
received theB.E. and M.E. degrees, from the
University of the Ryukyus, Okinawa,
Japan in 2004 and 2006, respectively.
He joined Magna Design Net, Inc. in2006 and has engaged with digital
signal processing design of modulator
and demodulator part for a WirelessLAN, WiMAX, 4G-LTE, 5G-NR, and underwatercommunication. Currently he is the Engineering Managerof the Development Department at Magna Design Net, Inc.
Shiho Oshiro
received theB.E. and M.E. degrees, from theUniversity of the Ryukyus, Okinawa,
Japan in 2018 and 2020, respectively.
She received the Dr. Eng. degree from
University of the Ryukyus in 2023.
She has been an assistant professor at
University of the Ryukyus since 2023.
She has experienced short-term study abroad at Madan
Mohan Malaviya University of Technology (MMMUT)
Gorakhpur and Atal Bihari Vajpayee-Indian Institute ofInformation Technology and Management (ABV-IIITM)
Gwalior in India, Institute of Technology of Cambodia (ITC)
in Cambodia, and National Taiwan University of Scienceand Technology (Taiwan Tech). Her research interest
includes Underwater OFDM Acoustic communicationsystems, developed Underwater Acoustic OFDM wirelesscommunication systems, Underwater Acoustic Positioning
systems targeting for Underwater Drone controls, Flight
Control for Underwater Drone automatically controls, andAutoencoder for OFDM communication system.

127

Gennan Hayashi
graduated at
the Area of Computer Science andIntelligent Systems course in the
Faculty of Engineering at theUniversity of the Ryukyus, Okinawa,
Japan in 2023. He is now a master’s
student at the Graduate School ofEngineering and Science at theUniversity of Ryukyus. Since 2022, he joined Prof. Wada’s
laboratory and engages in the research related to 5G mobilecommunication system.

Tomohisa Wada
received B.S.
degree in electronic engineering from
Osaka University, Osaka, Japan, in
1983, M.S.E.E. degree from Stanford
University, Stanford CA, in 1992, andPh.D. in electronic engineering from
Osaka University in 1994. He joined
the ULSI Laboratory, Mitsubishi
Electric Corp. Japan in 1983 and engaged in the researchand development of VLSI such as High-speed Static
Random-access memories, Cache memories for Intel MPUsin 16 years. Since 2001, he has been a Professor at theDepartment of Information Engineering, the University ofthe Ryukyus, Okinawa, Japan. In 2001, He was thefounding member of Magna Design Net, Inc., which is afab-less LSI design Company for communication related
digital signal processing such as OFDM. Currently, he isalso the chief scientist of Magna Design Net, Inc. who isengaging in the research and development of a terrestrial
video broadcasting receiver, a wireless LAN, WiMAX, 4GLTE and 5G systems. After 2009, he also started
Underwater OFDM Acoustic communication systems anddeveloped Underwater Acoustic OFDM wirelesscommunication systems and Underwater Acoustic
Positioning systems targeting for Underwater Drone
controls.