channel characteristics of rail traffic tunnel scenarios based on...

Research ArticleChannel Characteristics of Rail Traffic Tunnel ScenariosBased on Ray-Tracing Simulator

Jinmeng Zhao 1 Lei Xiong 1 Danping He1 and Jiadong Du2

1State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University China2The China Academy of Information and Communications Technology (CAICT) China

Correspondence should be addressed to Lei Xiong lxiongbjtueducn

Received 30 March 2018 Accepted 27 June 2018 Published 1 August 2018

Academic Editor Sana Salous

Copyright copy 2018 Jinmeng Zhao et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The tunnel scenario is a major rail communication scenario In this paper the radio channel characteristics of tunnel scenarios withdifferent carrier frequencies different distances between the transmitter (Tx) and receiver (Rx) and cross sections are simulatedwith a ray-tracing tool Key parameters such as path loss Rician K-factor rootmean square (RMS) delay spread and angular spreadare studied According to the results higher frequencies introduce larger path loss and the presence of the vehicle body increasesthe path loss by about 35 dB in the scenario at the same time it will also cause the fluctuation and instability of the path loss Besidesthe influence of reflections from the side walls is significant on radio propagation The channel experiences more severe fading ina narrow tunnel compared with others

1 Introduction

The rail traffic communications have experienced a rapiddevelopment recently such as high-speed railway municipalrailway and urban railway system The rail traffic scenariois indispensable for both private and public mobile com-munications It is widely agreed that the wireless channelmodel is significant to carry out mobile communicationsresearch system development and network deployment andso on [1] Currently the Long-Term Evolution Railway (LTE-R) system has been recommended to replace the globalsystem for mobile communication railway (GSM-R) systemfor high-speed train (HST) communication system as a partof intelligent transportation systems (ITS) [2 3] In additionthe research on 5th-Generation wireless systems (5G) basedon high-speed railway (HSR) has become a trend to meet theneed of transmission capabilities [4ndash6] Thus the study onchannel models in rail traffic system for new communicationsystem is indispensable

The wireless channel research needs to be carried outfor various typical rail traffic scenarios (viaducts tunnelscuttings etc) considering the significant differences betweenthe rail traffic scenarios and the public network scenarios [7]

Field test and ray tracer (RT) are two well-known methodsfor implementing channel characterization Field test in thefield of rail traffic is hard costly and long-term RT providesa means of accurately prediction of the wave propagationwhich is timesaving and convenient Therefore RT is widelyused in channel modeling for confined environments

Tunnel scenario is one of the most common scenariosespecially in the mountainous and hilly areas Consideringthe unique construction the wireless propagation in tunnelscenarios is different fromotherHST scenarioswhich attractsa lot of research interests [8ndash10] Leaky cables andDistributedAntenna System (DAS) [11 12] are mainly two promisingmethods to provide radio coverage in tunnels Several tunnelchannel models were proposed in recent years such as ray-tracing model multimode model and propagation-graphtheory based model [13 14] A real multipath propagationmodel for radio transmission in typical rectangular subwaytunnel was presented in [15] using RT to analyze Dopplerspread The three-dimensional (3D) models of six scenariomodules for mmWave and THz train-to-infrastructure chan-nels were defined and constructed for the first time in[16] which considered reality obstacle objects Based on thewideband measurements conducted in the tunnel scenario

HindawiWireless Communications and Mobile ComputingVolume 2018 Article ID 9284639 9 pageshttpsdoiorg10115520189284639

2 Wireless Communications and Mobile Computing

by using the mobile hotspot network system the authors in[17] explored key channel characteristics in different HSRscenarios by 3D RT Besides suggestions on symbol ratesubframe bandwidth and polarization configuration wereprovided to guide the 5G mmWave communication systemdesign in typical HSR scenarios

The aforementioned research summarized that themajor-ity of existing works contribute to modeling methods basedon large-scale parameters However previous models wereanalyzed and compared based on field test The measure-ments results such as channel impulse response (CIR) aremixed with a variety of factors In addition measurementsfocusing on narrowband single-input single-output (SISO)systems at low frequency band result in missing multipathparameters such as angular spread and Doppler shift Thereis still an urgent demand for an accurate complete chan-nel model considering large-scale parameters small-scaleparameters and spatial parameters [18 19] for multitypetunnel scenarios in SISO systems or multiple-input multiple-output (MIMO) systems Based on RT channel parameterssuch as the path loss multipath delay and angular spreadcan be obtained exactly and analyzed This paper providesthe simulation results in different type of tunnels at 18 GHzOptimized deployment recommendations are provided forMIMO systems and antenna configuration

The rest of the paper is organized as follows The existingchannel models for the tunnel scenario of 3GPP are intro-duced in Section 2 The defined tunnel scenarios and simu-lation setup are presented in Section 3 Key parameters suchas path loss Rician K-factor root mean square (RMS) delayspread and angular spread in tunnels with different crosssections at different frequencies are analyzed in Section 4Conclusions are drawn in Section 5

2 Channel Models

3GPP TSG-RAN WG4 in RAN66 meeting defined fourtypical high-speed railway scenarios A variety of standardchannel models in tunnel scenarios were adopted by 3GPP[20ndash23] like the single tap channel time delay line (TDL)model etc

Scenarios 2c and 2g are corresponding to tunnel scenarioscovered by leaky cables The coverage of the Evolved NodeB (eNB) is extended by deploying leaky cables in the 2g and2c scenarios which is shown in Table 1 In scenario 2g theUser Equipment (UE) communicates directly with the leakycable in the tunnel The signal is severely attenuated dueto the shielding of the train body in this case In scenarios2c relays are set up on the train The UE achieves two-hopcommunication with the leaky cable through relay as shownin Figure 1 Since the transmit power gradually attenuatesalong the leaky cable RF amplifiers will typically be appliedto ensure adequate signal strength The propagation channelbetween the in-car relay and the UE does not involve high-speed movement

3GPP R4-154106 proposes a one-tap channel model forleaky cables deployment in the tunnel scenario as shown inFigure 2 where D0 is the distance between two neighbor

RF amplifier

d

Leaky Feeder

Radiating point

Relay velocity vTrainUE

D

d

Figure 1 Leaky cable coverage with relay

Leaky cable

Dc

D

d

Figure 2 Detail illustration of leaky cable

radiating points the radiation angle of radiating point isdenoted as 1205790 It can be assumed that the receiver (Rx) iscovered by 8-9 radiation spots The RF receive signal is

119903 (119905) = sum119896

119909 (119905)radic1198751198961198901198952120587(119891119888minus119891119889119896)119905 + 119911 (119905)

= 119909 (119905) 1198901198952120587119891119888119905sum119896

radic119875119896119890minus1198952120587119891119889119896119905 + 119911 (119905)(1)

where 119875119896 denotes the normalized received power of the 119896119905ℎradiation spot 119891119889119896 is the respective Doppler shift z(t) is thereceived noise and x(t) is the transmitted signalThepower ofthe fading gain can bemodeled as a Rician distribution basedon the central limit theorem

However this model is only a simplifiedmodel It ignoresthe reflection component and the scattering componentwhich should be considered in a limited space Besidesthe parameters such as tunnel size cross section internalelectromagnetic (EM) properties of tunnel walls surfaceroughness and antenna polarizationmode affect the channelcharacteristics RT views radio waves reflected by surfacesof the tunnel It solves the problem of large workload andpoor applicability in field test and also compensates for theinability of the traditional model to provide specific wirelesschannel parameters such as amplitude delay Doppler shiftand angular spread which is of great significance for wirelesscommunication systems It is an effective modeling methodto establish a 3D channel model of the rail communicationscenarios and analyze the radio signal propagation under dif-ferent coverage patterns and multiple fading characteristics

3 Scenario Definition and Simulation Setup

31 Tunnel Scenarios Definition Given the different geologi-cal conditions the cross section of the tunnel varied in realityFour typical shapes of cross sections rectangular archedlong arched (combined rectangular and semicircular) and

Wireless Communications and Mobile Computing 3

Table 1 Tunnel scenarios by leaky cables

Scenarios Description Notation

2cThe tunnel is equipped with a leaky cablethat communicates with the trainrsquos roofRP and with the UE through the RP

Two hop

2g Laying leaky cables in the tunnel toachieve direct coverage of the UE One hop

semicircular are shown in Figure 3 The side length ofrectangular is 6m in tunnel a the height of arched is 6m andthe center of circle is 2m high above the ground in tunnel btunnel c contains a rectangular whose side length is 4m and asemicircular whose radius is 2m the radius of semicircularis 6m in tunnel d The number of tunnel surface in thesimulation is 4 10 9 and 13 respectively Figure 4 showsthe details of the simplified tunnel model referring to themetro tunnel project boundary map provided by the ChinaRailway Fourth Survey and Design Institute Group Co LtdThe train model is shown in Figure 5 The 3D tunnel modelsin this work are built by Google SketchUp These models areconsidered in the following simulation analysis

32 Parameters Setup The simulation parameters should becarefully determined to ensure that the simulation results areaccurate and effective and make simulation energy-friendlyand timesaving RT supports a variety of radio wave propa-gation mechanisms such as direction reflection scatteringdiffraction and transmission Reflection order means thatrays experience up to several times specular reflection fromtransmitter (Tx) to Rx The appropriate reflection order isnecessary not only to reflect the actual reflectance but alsoto avoid a longer simulation time

Based on the above ideas the channel characteristicsunder different reflection orders are simulated and analyzedin tunnel scenario in Figure 4 with all radio wave propagationmechanisms The key channel characteristics such as RicianK-factor delay spread angle spread of angle of arrival (AOA)and angle of departure (AOD) are compared respectivelyunder different reflection orders range from 6119905ℎ-9119905ℎWhen thereflection order is set to higher than 6119905ℎ there is rarely achange In addition we define

119875119871error (119894 119895) =10038161003816100381610038161003816119875119871 119894119891 minus 119875119871119895119891

10038161003816100381610038161003816119875119871119895119891

(2)

where the 119875119871119894119891 is the path loss when the frequency is 119891 andthe reflection order is 119894 The 119875119871119890119903119903119900119903(i j) shows the differencerate between 119894119905ℎ and 119895119905ℎ order in a series of frequencies TheCDF of 119875119871119890119903119903119900119903 is shown in Figure 6 The means of 119875119871119890119903119903119900119903(89) 119875119871119890119903119903119900119903(7 8) and 119875119871119890119903119903119900119903(6 7) are 426 times 10minus12 19 times10minus2 and 018 respectively The 119875119871119890119903119903119900119903(8 9) is the smallestranging from 641 times 10minus13 to 172 times 10minus11 The 119875119871119890119903119903119900119903(7 8)ranges from 497 times 10minus5 to 012 The 119875119871119890119903119903119900119903(6 7) ranges from173 times 10minus4 to 053 which is larger than others As a resultthe path loss up to higher than 8119905ℎ order is hardly changeThus the 8119905ℎ order is adopted in simulation due to a tradeoff

Table 2 Parameters setup

Parameter ValueFrequency 18 GHz 58 GHzTransmitting power 25 dBm

Antenna(Tx Rx) Omnidirectional antenna(vertically polarized)

Tx location (0 0 3)Rx location (x 0 5)Reflection order 8Bandwidth 10 MHzResolution 1 MHz

between computational complexity and precision as shownin Table 2 Considering the fact that the tunnel scenarios arelong straight tunnels covered by concrete with no vents andpipes and other obstacles diffraction is irrelevant here as wellas transmission because the Tx is not fixed in the wall

Detailed parameters setup is shown in Table 2 Thefrequency is set to 18 GHz and 58GHz in order to comparechannel characteristics at different frequencies Signal propa-gates with 25 dBm of transmitting power Tx is fixed at oneend of the tunnel with the height of 3m Rx moves alongthe x-axis with the height of 5m Both of them use verticallypolarized omnidirectional antennas The channel bandwidthB = 10MHz and the system time domain resolution Δt = 1 B In order to better observe the path with the maximumexcess delay max the number of simulated frequency points119873119891 should be determined enough [24]

120591max le 119873119891 times Δ119905 (3)

in which in other words the frequency domain resolutionΔf= B N119891 should be set sufficiently

4 Simulation Results and Analyses

In this section the simulation results of tunnel channel char-acteristics in different cross sections and different frequenciesare presented and analyzed Furthermore suggestions onoptimized deployment are provided

41 Large-Scale Parameters The reliable large-scale channelmodels are essential to network deployment and optimiza-tion Typically the path loss is expressed as

119875119871 (119889) = 119860 + 10119899 lg (119889) + 119883 (4)


4 2 0 minus2 minus4

TX

RX

6 m

6 m

Y

ZX

0

4

8

(a)

4 2 0 minus2 minus4

TX

RX

8 m

Y

ZX

6 m

0

4

8

(b)

4 2 0 minus2 minus4

TX

RX

6 m

4m

0

4

8

Y

ZX

(c)

8 4 0 minus4 minus8

TXRX

12 m

Y

ZX

6 m

0

8

16

(d)

Figure 3 Regular cross sections for tunnels (a) Rectangular (b) Arched (c) Long arched (d) Semicircular

Figure 4 Simplified tunnel model (actual scenario)

Figure 5 Train model for HST

where the PL(d) is path loss without small-scale fading andit is a function of the distance between Tx and Rx [25] n ispath loss exponent and X (shadow fading) is the zero-meanGaussian randomvariablewith standard deviation120590 Figure 7shows the path loss at 18 GHz in different cross sections Inthe 0-190m section the path loss is nearly the same However

6ＮＢ VS 7ＮＢ

7ＮＢ VS 8ＮＢ

8ＮＢ VS 9ＮＢ

172times10-11

times10-110

05

08

06

CDF

1

04

02

01 02 03 04 05 0600

01

1

2

０ＬＬＩＬ

Figure 6 CDF of 119875119871119890119903119903119900119903

in the 190-500m section the path loss in tunnel c has ahigher path loss than other tunnels The path loss in tunnelc can be divided into two phases and path loss exponentsare 196 and 362 respectively which means that there isa breakpoint (1198890 = 19010m) in this scenario These tunnelcross sections have the same height and the width varies inshape and size The path loss fitting result given in Table 3


10ＦＡ(d0) = 2279d0 = 19010 m

Tunnel aTunnel b

Tunnel cTunnel d

90

80

0

70

50

40105 15 20

60

100

Distance [10lg(d)]25 30

Path

Los

s [dB

]

Figure 7 Path loss in different tunnel cross sections at 18 GHz

18 GHz58 GHz

minus20

minus10

minus30

minus40

minus50

minus60

minus70

minus800 100 450150 500200 250 300 350 40050

Distance [m]

11 dB

Rece

ived

Pow

er [d

Bm]

Figure 8 Received power at different frequencies in tunnel c

indicates that the lateral shape has an important impact onthe path loss in the empty tunnel with strong line of sight(LOS) pathThe path loss exponent in tunnel c is greater than2 because of the existing breakpoint The path loss exponentsare 177 184 and 188 in tunnel a d and b respectivelyCompared with the measurement results in straight archedtunnel [26 27] and rectangular tunnel [28ndash30] the value ofpath loss exponent 196 in tunnel c is similar to 140-203 at954-2000MHz in straight arched tunnel Meanwhile pathloss exponent 177 in tunnel a is similar to 165-194 at 945-2650MHz in rectangular tunnel Simulation results in thispaper are basically consistent with the measurement resultsin previous work

Figure 8 shows the received power at different frequenciesin tunnel c As the frequency increases the received powerdecreasesWhen the distance betweenTx andRx equals 50mthe received power at 18 GHz is 11 dB higher than that at58 GHz Received power has larger fluctuation and deeper

Tunnel c with trainEmpty Tunnel c

0

60

100 450150 500200 250 300 350 40050

Distance [m]

140

120

100

80

40

Path

Los

s [dB

]

Figure 9 Path loss in empty tunnel and tunnel with train

Table 3 Path loss fitting result at 18 GHZ

Parameter A n 120590Tunnel a 4129 177 074Tunnel b 3946 188 045Tunnel c 3182 230 160Tunnel d 4129 184 060

Table 4 Path loss fitting result in tunnel c

Parameter A n 12059018 GHz 3182 231 16058 GHz 5151 178 145

fading is prone to occur in higher frequency Based on thesimilar simulation scenario and parameters setup the sameconclusion is also reflected on the simulation results at threedifferent typical carrier frequencies ie 900MHz 245GHzand 575GHz in [31] Table 4 shows the fitting parametersat different frequencies The path loss exponent is 231 at18 GHz while the path loss exponent is less than 2 at higherfrequency Results confirm that the frequency band has astrong impact on the wireless propagation

For the tunnel with train the path loss result in selectedlocations is shown in Figure 9 Rx is fixed on the head oftrain when the train gradually moves away from the Tx Theobstruction and reflection of the train make the receivedsignal experience longer distance and greater attenuationThecorresponding number of arriving rays reduces sharply Thepath loss increases by 3558 dBwith the presence of the vehiclebody The result shows that the path loss in the empty tunnelscenario rises more steadily Suggestions are given that theantenna deployment in reality scenarios should make sureof the existence of LOS path between Tx and Rx Moreoverantenna placement is selected carefully to make the blockingeffect of the train as small as possible for which furtherresearches are needed


Tunnel aTunnel b

Tunnel cTunnel d

0 100 450150 500200 250 300 350 40050

Distance [m]

0

10

Rici

an K

-fact

or [d

B]

5

15

20

25

30

Part 1

Part 2

(a)

Kmax

Kmax= 2738

Kmax= 2881Kmax= 2883

= 2653

Tunnel aTunnel b

Tunnel cTunnel d

Rician K-factor [dB]0 105 15

26 27096

098

1

28 29

20 25 30

08

06

1

04

02

0

CDF

(b)

Figure 10 (a) Rician K-factor at 18 GHz (b) CDF of Rician K-factor at all the snapshots

Table 5 Small scale parameters

ParameterMean

K-factor[dB]

Percentageof Klt25 dB

Meandelay spread[ns]

95 ofdelay spreadrange [ns]

Tunnel a 137 88 047 031-076Tunnel b 1498 86 037 009-075Tunnel c 1082 948 033 017-066Tunnel d 1446 87 040 016-080

42 Small-Scale Parameters Small-scale parameters have animportant impact in wireless communication system designand analysis Rician K-factor RMS delay spread and angularspread are key parameters to describe the small-scale charac-teristics Table 5 shows the K-factor and RMS delay spread indifferent tunnel scenarios

421 Rician K-Factor Rician K-factor is defined as the radioof the power of LOS path to the power of non-line-of-sight(NLOS) paths [32] Figure 10 shows K-factor at 18 GHz andCDF of K-factor at all the snapshots Figure 10(a) depicts thatthe simulation section can be divided into two parts K-factorfluctuates severely in part one (0-100m) and then decreasessmoothly in part two (100-500m) In the first 50m the fadingis weak but after that the fading is increasingly seriouswhatever the tunnel scenario is Table 5 demonstrates that948 of K-factor in all the snapshots in tunnel c is lower than25 dB but there is about 88 of K-factor lower than 25 dB inother tunnel scenarios as shown in Figure 10(b)Themean K-factor of tunnel scenarios is around 1349 dB larger than theresult 115 dB of empirical cluster characteristics extracted fortunnel scenarios at 214GHz [33] Since the path loss increaseswith frequency LOS path experiences a deeper fading at214GHz In conclusion channel characteristics in tunnel cexperience a severe fading than others

422 RMS Delay Spread Figure 11 shows that RMS delayspread at 18 GHz and CDF of RMS delay spread at all thesnapshotsTunnel a is the rectangular tunnel (W6mtimesH6m)and tunnel c is the long arched tunnel (W4m times H6m) Themost apparent difference between tunnel a and tunnel c istheir widths RMS delay spread in tunnel a is larger than thatin tunnel c along the simulation section In Table 5 we noticethat RMS delay spread is lower than 08 ns in at least 95at all the snapshots and the maximum RMS delay spread is118 ns The results in Table 5 illustrate that 95 of the RMSdelay spreads at all the snapshots in tunnel a and tunnel c are045 ns and 049 ns respectively which is narrow comparedwith other scenarios On the other hand mean RMS delayspread is the largest in tunnel a and the weighted average ofthe delay spread in tunnel c is the smallest As a result thechannel in tunnel c experiences amore stable fadingTheRMSdelay spread varies in ns because of fewer obstacles in emptytunnel which is similar to the measurement results of delayspread 2-27 ns in mine tunnels [34]

43 Spatial Parameters The RMS angular spreads in tunnelc and CDF of angular spreads are shown in Figure 12 ASAESA ASD and ESD are angular spreads of the azimuth angleof arrival the elevation angle of arrival the azimuth angleof departure and elevation angle of departure respectively


Tunnel aTunnel c

0 100 450150 500200 250 300 350 40050Distance [m]

08

06

1

04

02

Del

ay S

prea

d [n

s]12

0

(a)

max= 1059

max= 1157

Tunnel aTunnel c

0996

0998

1

1

Delay Spread [ns]0806

11 12

10402 120

08

06

1

04

02

0

CDF

(b)

Figure 11 (a) RMS delay spread at 18 GHz (b) CDF of RMS delay spread at all the snapshots

ASAESA

ASDESD

0

00

5

10

15

100

100

450150 500200 250 300 350 40050

50

Distance [m]

60

140

120

100

80

40

20

0

ASmax=1239∘

Ang

ular

Spr

ead

[∘]

(a)

60 1201008040

00

5

05

10

20

ASAESA

ASDESD

1

08

06

1

04

02

0

CDF

Angular Spread [∘]

(b)

Figure 12 Tunnel c scenario (a) RMS angular spread at 18 GHz (b) CDF of RMS angular spread at all the snapshots

Figure 11 illustrates that ESA ASD and ESD decrease slowlyas the Rx moves far away from Tx and they are lowerthan 1020∘ at all the snapshots The means of ASA ESAASD and ESD are 5125∘ 067∘ 163∘ and 095∘ respectively99 of ESA ASD and ESD are less than 5∘ However ASAvaries differently comparedwith others It gradually increasesand the max ASA is 12390∘ when the distance between Txand Rx reaches 500m Angular spread in straight tunnelscenario in work [17] varies similarly in which ASD becomeslarger as the distance of Tx and Rx increases and othersdecrease at the same time ASA is greater than others in themajority of the snapshots which indicates that the impactof reflections from the side walls is significant on radiopropagation Multiantennas can be considered to implement

a MIMO system so that the system capacity can be increasedby achieving diversity and multiplexing Besides directionalantennas can be deployed to drop the ASA and reduce theimpact of Doppler spread on the channel

Simulation results reveal that ASA ESA ASD and ESDvary similarly in tunnels b c and d The ASA is comparedin tunnels b c and d as shown in Figure 13 The maximumof ASA in tunnels b c and d is 658∘ 1239∘ and 738∘respectively It is obvious that ASA in tunnel c is larger thanthat in tunnel d whereas ASA in tunnel b is the lowest at themajority of snapshots This observation indicates that spatialfading is affected by the cross section Furthermore the sidewalls have a more significant impact on the channel in anarrow tunnel than a wider one

8 Wireless Communications and Mobile ComputingA

SA [∘

]

Tunnel bTunnel cTunnel d

00

100 450150 500200 250 300 350 40050

Distance [m]

60

140

120

100

80

40

20

ASmax= 1239∘

ASmax= 738∘

ASmax= 658∘

Figure 13 ASA in tunnels b c and d

5 Conclusion

In this paper the radio channel characteristics of severaltunnel scenarios were simulated with RT The channelcharacteristics in different carrier frequencies and tunnelcross sections were analyzed The key parameters such aspath loss Rician K-factor RMS delay spread and angularspread were simulated and analyzed The presence of thevehicle body introduces additional 35 dB of the path losswhich leads to the fluctuation and instability of the channelK-factor changes severely when the distance between Tx andRx is smaller than 100m and then decreases smoothly infar region The channel has short delay spread (118 ns) dueto strong LOS and the limited space The side walls havea significant influence on radio propagation especially in anarrow tunnel Therefore the conclusion can be drawn thatthe channel experiences a severe and stable fading in longarched tunnels compared to other tunnel scenariosThe otherparameters (ie Doppler spread coherence time antennapolarization etc) and leaky cable for coverage will be studiedin the future work

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported in part by the FundamentalResearch Funds for the Central Universities (2018JBM079)the National Key Research and Development Program under

Grant 2016YFE0200900 the National Science and Technol-ogy Major Project (2015ZX03001027-003) the National KeyRampD Program of China under Grant no 2016YFB1200100the National Natural Science Foundation of China underGrant 61471030 the State Key Laboratory of Rail TrafficControl and Safety under Grant RCS2018ZZ006 and theFundamental Research Funds for the Central Universitiesunder Grant no 2017YJS014

References

[1] C-X Wang A Ghazal B Ai Y Liu and P Fan ldquoChannelmeasurements andmodels for high-speed train communicationsystems a surveyrdquo IEEE Communications Surveys amp Tutorialsvol 18 no 2 pp 974ndash987 2015

[2] D W Matolak M Berbineau D G Michelson and C ChenldquoFuture railway communications [Guest Editorial]rdquo IEEE Com-munications Magazine vol 53 no 10 pp 60-61 2015

[3] J Marais J Beugin and M Berbineau ldquoA Survey of GNSS-Based Research and Developments for the European RailwaySignalingrdquo IEEE Transactions on Intelligent Transportation Sys-tems vol 18 no 10 pp 2602ndash2618 2017

[4] J Zhang Z Zheng Y Zhang J Xi X Zhao and G Guildquo3D MIMO for 5G NR Several Observations from 32 toMassive 256 Antennas Based on Channel Measurementrdquo IEEECommunications Magazine vol 56 no 3 pp 62ndash70 2018

[5] T S Rappaport Y Xing G R MacCartney A F Molisch EMellios and J Zhang ldquoOverview of millimeter wave communi-cations for fifth-generation (5G) wireless networks-with a focuson propagation modelsrdquo IEEE Transactions on Antennas andPropagation no 99 article 1 2017

[6] C T Neil M Shafi P J Smith P A Dmochowski and JZhang ldquoImpact of Microwave and mmWave Channel Modelson 5G Systems Performancerdquo IEEE Transactions on Antennasand Propagation vol 65 no 12 pp 6505ndash6520 2017

[7] A Hrovat G Kandus and T Javornik ldquoA survey of radio prop-agationmodeling for tunnelsrdquo IEEECommunications Surveys ampTutorials vol 16 no 2 pp 658ndash669 2014

[8] Y Liu AGhazal CWang XGe Y Yang andY Zhang ldquoChan-nel measurements and models for high-speed train wirelesscommunication systems in tunnel scenarios a surveyrdquo ScienceChina Information Sciences vol 60 no 10 2017

[9] C Zhou ldquoRay tracing and modal methods for modeling radiopropagation in tunnels with rough wallsrdquo IEEE Transactions onAntennas and Propagation vol 65 no 5 pp 2624ndash2634 2017

[10] K Guan B Ai Z Zhong et al ldquoMeasurements and Analysis ofLarge-Scale Fading Characteristics in Curved Subway Tunnelsat 920 MHz 2400 MHz and 5705 MHzrdquo IEEE Transactions onIntelligent Transportation Systems vol 16 no 5 pp 2393ndash24052015

[11] K Guan Z Zhong B Ai and C Briso-Rodriguez ldquoStatisticmodeling for propagation in tunnels based on distributedantenna systemsrdquo in Proceedings of the 2013 IEEE Interna-tional Symposium on Antennas and Propagation amp USNCURSINational Radio Science Meeting pp 1920-1921 Orlando FLUSA July 2013

[12] C Briso-Rodriguez JM Cruz and J I Alonso ldquoMeasurementsand modeling of distributed antenna systems in railway tun-nelsrdquo IEEE Transactions on Vehicular Technology vol 56 no 5pp 2870ndash2879 2007


[13] J A Castiblanco D Seetharamdoo M Berbineau et al ldquoSur-face impedance boundary conditions in time domain for guidedstructures of arbitrary cross section with lossy dielectric wallsrdquoInstitute of Electrical and Electronics Engineers Transactions onAntennas and Propagation vol 63 no 3 pp 1086ndash1097 2015

[14] A Hrovat G Kandus and T Javornik ldquoFour-slope channelmodel for path loss prediction in tunnels at 400 MHzrdquo IETMicrowaves Antennas amp Propagation vol 4 no 5 pp 571ndash5822010

[15] K Guan Z D Zhong J I Alonso and C Briso-RodrıguezldquoMeasurement of distributed antenna systems at 24 GHz ina realistic subway tunnel environmentrdquo IEEE Transactions onVehicular Technology vol 61 no 2 pp 834ndash837 2012

[16] K Guan X Lin D He et al ldquoScenario modules and ray-tracing simulations of millimeter wave and terahertz channelsfor smart rail mobilityrdquo in Proceedings of the 2017 11th EuropeanConference on Antennas and Propagation (EUCAP) pp 113ndash117Paris France March 2017

[17] DHe B Ai K Guan et al ldquoChannelMeasurement Simulationand Analysis for High-Speed Railway Communications in5G Millimeter-Wave Bandrdquo IEEE Transactions on IntelligentTransportation Systems no 99 pp 1ndash15 2017

[18] L Zhang C Briso J R O Fernandez et al ldquoDelay spread andelectromagnetic reverberation in subway tunnels and stationsrdquoIEEEAntennas andWireless Propagation Letters vol 15 pp 585ndash588 2016

[19] J Zhang C Pan F Pei G Liu and X Cheng ldquoThree-dimensional fading channel models a survey of elevation angleresearchrdquo IEEE Communications Magazine vol 52 no 6 pp218ndash226 2014

[20] NokiaNetworks ldquoChannelmodelling for high speed leaky cablescenariosrdquo in Proceedings of the 3GPP TSG-RAN WG4 Meeting76 R4-154106 Beijing China 2015

[21] Huawei ldquoChannel models for the leaky cablerdquo in Proceedings ofthe 3GPP TSG-RAN WG4 Meeting 76 HiSilicon R4-154241Beijing China 2015

[22] Huawei HiSilicon ldquoChannel models for the leaky cablerdquo in3GPP TSG-RANWG4 Meeting 75 Japan Fukuoka 2015

[23] Huawei ldquoTP Channel model for leaky cable in tunnelrdquo inProceedings of the 3GPPTSG-RANWG4Meeting 76 HiSiliconR4-154242 Beijing China 2015

[24] S Priebe towards THz communications propagation studiesindoor channel modeling and interference investigations ShakerVerlag 2013

[25] D He J Yang K Guan et al ldquoRay-tracing simulation andanalysis of propagation for 3GPP high speed scenariosrdquo inProceedings of the 2017 11th European Conference on Antennasand Propagation (EUCAP) pp 2890ndash2894 Paris FranceMarch2017

[26] Ningde high-speed railway tunnel covering research report GCIScience Technology Co Ltd Guangzhou China Tech Rep2008

[27] N Wang ldquoA uniform path-loss model by power balance theory(PBT) and its application on tunnelsrdquo in Proceedings of the 20109th International Symposium on Antennas Propagation and EMTheory ISAPE 2010 pp 481ndash484 China December 2010

[28] D Didascalou J Maurer and W Wiesbeck ldquoSubway tunnelguided electromagnetic wave propagation at mobile commu-nications frequenciesrdquo IEEE Transactions on Antennas andPropagation vol 49 no 11 pp 1590ndash1596 2001

[29] S Shinozaki M Wada A Teranishi H Furukawa and YAkaiwa ldquoRadio propagation characteristics in subway platformand tunnel in 25 GHz bandrdquo in Proceedings of the 1995 6thIEEE International Symposium on Personal Indoor and MobileRadio Communications PIMRCrsquo95 Part 3 (of 3) pp 1175ndash1179September 1995

[30] M Choi D Kim H Jo J Yook and H Park ldquoPath-losscharacteristics in subway tunnels at 265 GHzrdquo Microwave andOptical Technology Letters vol 48 no 2 pp 383ndash386 2006

[31] Y Zhang Y Liu J Sun CWang andXGe ldquoImpact ofDifferentParameters on Channel Characteristics in a High-Speed TrainRay Tracing Tunnel Channel Modelrdquo in Proceedings of the 2017IEEE 85th Vehicular Technology Conference (VTC Spring) pp1ndash5 Sydney NSW June 2017

[32] A F Molisch Wireless Communications IEEE-Wiley 2nd edi-tion 2011

[33] X Cai X Yin X Cheng and A Perez Yuste ldquoAn EmpiricalRandom-Cluster Model for Subway Channels Based on PassiveMeasurements in UMTSrdquo IEEE Transactions on Communica-tions vol 64 no 8 pp 3563ndash3575 2016

[34] R He Z Zhong B Ai et al ldquoPropagation channel mea-surements and analysis at 24 GHz in subway tunnelsrdquo IETMicrowaves Antennas amp Propagation vol 7 no 11 pp 934ndash9412013

International Journal of

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Active and Passive Electronic Components

VLSI Design



Shock and Vibration


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Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawiwwwhindawicom

Volume 2018

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

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Journal ofEngineeringVolume 2018

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RotatingMachinery


Modelling ampSimulationin EngineeringHindawiwwwhindawicom Volume 2018


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Submit your manuscripts atwwwhindawicom


by using the mobile hotspot network system the authors in[17] explored key channel characteristics in different HSRscenarios by 3D RT Besides suggestions on symbol ratesubframe bandwidth and polarization configuration wereprovided to guide the 5G mmWave communication systemdesign in typical HSR scenarios

The aforementioned research summarized that themajor-ity of existing works contribute to modeling methods basedon large-scale parameters However previous models wereanalyzed and compared based on field test The measure-ments results such as channel impulse response (CIR) aremixed with a variety of factors In addition measurementsfocusing on narrowband single-input single-output (SISO)systems at low frequency band result in missing multipathparameters such as angular spread and Doppler shift Thereis still an urgent demand for an accurate complete chan-nel model considering large-scale parameters small-scaleparameters and spatial parameters [18 19] for multitypetunnel scenarios in SISO systems or multiple-input multiple-output (MIMO) systems Based on RT channel parameterssuch as the path loss multipath delay and angular spreadcan be obtained exactly and analyzed This paper providesthe simulation results in different type of tunnels at 18 GHzOptimized deployment recommendations are provided forMIMO systems and antenna configuration

The rest of the paper is organized as follows The existingchannel models for the tunnel scenario of 3GPP are intro-duced in Section 2 The defined tunnel scenarios and simu-lation setup are presented in Section 3 Key parameters suchas path loss Rician K-factor root mean square (RMS) delayspread and angular spread in tunnels with different crosssections at different frequencies are analyzed in Section 4Conclusions are drawn in Section 5

2 Channel Models

3GPP TSG-RAN WG4 in RAN66 meeting defined fourtypical high-speed railway scenarios A variety of standardchannel models in tunnel scenarios were adopted by 3GPP[20ndash23] like the single tap channel time delay line (TDL)model etc

Scenarios 2c and 2g are corresponding to tunnel scenarioscovered by leaky cables The coverage of the Evolved NodeB (eNB) is extended by deploying leaky cables in the 2g and2c scenarios which is shown in Table 1 In scenario 2g theUser Equipment (UE) communicates directly with the leakycable in the tunnel The signal is severely attenuated dueto the shielding of the train body in this case In scenarios2c relays are set up on the train The UE achieves two-hopcommunication with the leaky cable through relay as shownin Figure 1 Since the transmit power gradually attenuatesalong the leaky cable RF amplifiers will typically be appliedto ensure adequate signal strength The propagation channelbetween the in-car relay and the UE does not involve high-speed movement

3GPP R4-154106 proposes a one-tap channel model forleaky cables deployment in the tunnel scenario as shown inFigure 2 where D0 is the distance between two neighbor

RF amplifier

d

Leaky Feeder

Radiating point

Relay velocity vTrainUE

D

d

Figure 1 Leaky cable coverage with relay

Leaky cable

Dc

D

d

Figure 2 Detail illustration of leaky cable

radiating points the radiation angle of radiating point isdenoted as 1205790 It can be assumed that the receiver (Rx) iscovered by 8-9 radiation spots The RF receive signal is

119903 (119905) = sum119896

119909 (119905)radic1198751198961198901198952120587(119891119888minus119891119889119896)119905 + 119911 (119905)

= 119909 (119905) 1198901198952120587119891119888119905sum119896

radic119875119896119890minus1198952120587119891119889119896119905 + 119911 (119905)(1)

where 119875119896 denotes the normalized received power of the 119896119905ℎradiation spot 119891119889119896 is the respective Doppler shift z(t) is thereceived noise and x(t) is the transmitted signalThepower ofthe fading gain can bemodeled as a Rician distribution basedon the central limit theorem

However this model is only a simplifiedmodel It ignoresthe reflection component and the scattering componentwhich should be considered in a limited space Besidesthe parameters such as tunnel size cross section internalelectromagnetic (EM) properties of tunnel walls surfaceroughness and antenna polarizationmode affect the channelcharacteristics RT views radio waves reflected by surfacesof the tunnel It solves the problem of large workload andpoor applicability in field test and also compensates for theinability of the traditional model to provide specific wirelesschannel parameters such as amplitude delay Doppler shiftand angular spread which is of great significance for wirelesscommunication systems It is an effective modeling methodto establish a 3D channel model of the rail communicationscenarios and analyze the radio signal propagation under dif-ferent coverage patterns and multiple fading characteristics

3 Scenario Definition and Simulation Setup

31 Tunnel Scenarios Definition Given the different geologi-cal conditions the cross section of the tunnel varied in realityFour typical shapes of cross sections rectangular archedlong arched (combined rectangular and semicircular) and





Two hop





119875119871error (119894 119895) =10038161003816100381610038161003816119875119871 119894119891 minus 119875119871119895119891

10038161003816100381610038161003816119875119871119895119891

(2)








120591max le 119873119891 times Δ119905 (3)





119875119871 (119889) = 119860 + 10119899 lg (119889) + 119883 (4)


4 2 0 minus2 minus4

TX

RX

6 m

6 m

Y

ZX

0

4

8

(a)

4 2 0 minus2 minus4

TX

RX

8 m

Y

ZX

6 m

0

4

8

(b)

4 2 0 minus2 minus4

TX

RX

6 m

4m

0

4

8

Y

ZX

(c)

8 4 0 minus4 minus8

TXRX

12 m

Y

ZX

6 m

0

8

16

(d)





6ＮＢ VS 7ＮＢ

7ＮＢ VS 8ＮＢ

8ＮＢ VS 9ＮＢ

172times10-11

times10-110

05

08

06

CDF

1

04

02

01 02 03 04 05 0600

01

1

2

０ＬＬＩＬ

Figure 6 CDF of 119875119871119890119903119903119900119903



10ＦＡ(d0) = 2279d0 = 19010 m

Tunnel aTunnel b

Tunnel cTunnel d

90

80

0

70

50

40105 15 20

60

100


Path

Los

s [dB

]


18 GHz58 GHz

minus20

minus10

minus30

minus40

minus50

minus60

minus70

minus800 100 450150 500200 250 300 350 40050

Distance [m]

11 dB

Rece

ived

Pow

er [d

Bm]





0

60

100 450150 500200 250 300 350 40050

Distance [m]

140

120

100

80

40

Path

Los

s [dB

]









Tunnel aTunnel b

Tunnel cTunnel d

0 100 450150 500200 250 300 350 40050

Distance [m]

0

10

Rici

an K

-fact

or [d

B]

5

15

20

25

30

Part 1

Part 2

(a)

Kmax

Kmax= 2738


= 2653

Tunnel aTunnel b

Tunnel cTunnel d


26 27096

098

1

28 29

20 25 30

08

06

1

04

02

0

CDF

(b)



ParameterMean

K-factor[dB]










Tunnel aTunnel c

0 100 450150 500200 250 300 350 40050Distance [m]

08

06

1

04

02

Del

ay S

prea

d [n

s]12

0

(a)

max= 1059

max= 1157

Tunnel aTunnel c

0996

0998

1

1


11 12

10402 120

08

06

1

04

02

0

CDF

(b)


ASAESA

ASDESD

0

00

5

10

15

100

100

450150 500200 250 300 350 40050

50

Distance [m]

60

140

120

100

80

40

20

0

ASmax=1239∘

Ang

ular

Spr

ead

[∘]

(a)

60 1201008040

00

5

05

10

20

ASAESA

ASDESD

1

08

06

1

04

02

0

CDF


(b)






SA [∘

]


00

100 450150 500200 250 300 350 40050

Distance [m]

60

140

120

100

80

40

20

ASmax= 1239∘

ASmax= 738∘

ASmax= 658∘


5 Conclusion


Data Availability




Acknowledgments



References






































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia






Two hop





119875119871error (119894 119895) =10038161003816100381610038161003816119875119871 119894119891 minus 119875119871119895119891

10038161003816100381610038161003816119875119871119895119891

(2)








120591max le 119873119891 times Δ119905 (3)





119875119871 (119889) = 119860 + 10119899 lg (119889) + 119883 (4)


4 2 0 minus2 minus4

TX

RX

6 m

6 m

Y

ZX

0

4

8

(a)

4 2 0 minus2 minus4

TX

RX

8 m

Y

ZX

6 m

0

4

8

(b)

4 2 0 minus2 minus4

TX

RX

6 m

4m

0

4

8

Y

ZX

(c)

8 4 0 minus4 minus8

TXRX

12 m

Y

ZX

6 m

0

8

16

(d)





6ＮＢ VS 7ＮＢ

7ＮＢ VS 8ＮＢ

8ＮＢ VS 9ＮＢ

172times10-11

times10-110

05

08

06

CDF

1

04

02

01 02 03 04 05 0600

01

1

2

０ＬＬＩＬ

Figure 6 CDF of 119875119871119890119903119903119900119903



10ＦＡ(d0) = 2279d0 = 19010 m

Tunnel aTunnel b

Tunnel cTunnel d

90

80

0

70

50

40105 15 20

60

100


Path

Los

s [dB

]


18 GHz58 GHz

minus20

minus10

minus30

minus40

minus50

minus60

minus70

minus800 100 450150 500200 250 300 350 40050

Distance [m]

11 dB

Rece

ived

Pow

er [d

Bm]





0

60

100 450150 500200 250 300 350 40050

Distance [m]

140

120

100

80

40

Path

Los

s [dB

]









Tunnel aTunnel b

Tunnel cTunnel d

0 100 450150 500200 250 300 350 40050

Distance [m]

0

10

Rici

an K

-fact

or [d

B]

5

15

20

25

30

Part 1

Part 2

(a)

Kmax

Kmax= 2738


= 2653

Tunnel aTunnel b

Tunnel cTunnel d


26 27096

098

1

28 29

20 25 30

08

06

1

04

02

0

CDF

(b)



ParameterMean

K-factor[dB]










Tunnel aTunnel c

0 100 450150 500200 250 300 350 40050Distance [m]

08

06

1

04

02

Del

ay S

prea

d [n

s]12

0

(a)

max= 1059

max= 1157

Tunnel aTunnel c

0996

0998

1

1


11 12

10402 120

08

06

1

04

02

0

CDF

(b)


ASAESA

ASDESD

0

00

5

10

15

100

100

450150 500200 250 300 350 40050

50

Distance [m]

60

140

120

100

80

40

20

0

ASmax=1239∘

Ang

ular

Spr

ead

[∘]

(a)

60 1201008040

00

5

05

10

20

ASAESA

ASDESD

1

08

06

1

04

02

0

CDF


(b)






SA [∘

]


00

100 450150 500200 250 300 350 40050

Distance [m]

60

140

120

100

80

40

20

ASmax= 1239∘

ASmax= 738∘

ASmax= 658∘


5 Conclusion


Data Availability




Acknowledgments



References






































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



4 2 0 minus2 minus4

TX

RX

6 m

6 m

Y

ZX

0

4

8

(a)

4 2 0 minus2 minus4

TX

RX

8 m

Y

ZX

6 m

0

4

8

(b)

4 2 0 minus2 minus4

TX

RX

6 m

4m

0

4

8

Y

ZX

(c)

8 4 0 minus4 minus8

TXRX

12 m

Y

ZX

6 m

0

8

16

(d)





6ＮＢ VS 7ＮＢ

7ＮＢ VS 8ＮＢ

8ＮＢ VS 9ＮＢ

172times10-11

times10-110

05

08

06

CDF

1

04

02

01 02 03 04 05 0600

01

1

2

０ＬＬＩＬ

Figure 6 CDF of 119875119871119890119903119903119900119903



10ＦＡ(d0) = 2279d0 = 19010 m

Tunnel aTunnel b

Tunnel cTunnel d

90

80

0

70

50

40105 15 20

60

100


Path

Los

s [dB

]


18 GHz58 GHz

minus20

minus10

minus30

minus40

minus50

minus60

minus70

minus800 100 450150 500200 250 300 350 40050

Distance [m]

11 dB

Rece

ived

Pow

er [d

Bm]





0

60

100 450150 500200 250 300 350 40050

Distance [m]

140

120

100

80

40

Path

Los

s [dB

]









Tunnel aTunnel b

Tunnel cTunnel d

0 100 450150 500200 250 300 350 40050

Distance [m]

0

10

Rici

an K

-fact

or [d

B]

5

15

20

25

30

Part 1

Part 2

(a)

Kmax

Kmax= 2738


= 2653

Tunnel aTunnel b

Tunnel cTunnel d


26 27096

098

1

28 29

20 25 30

08

06

1

04

02

0

CDF

(b)



ParameterMean

K-factor[dB]










Tunnel aTunnel c

0 100 450150 500200 250 300 350 40050Distance [m]

08

06

1

04

02

Del

ay S

prea

d [n

s]12

0

(a)

max= 1059

max= 1157

Tunnel aTunnel c

0996

0998

1

1


11 12

10402 120

08

06

1

04

02

0

CDF

(b)


ASAESA

ASDESD

0

00

5

10

15

100

100

450150 500200 250 300 350 40050

50

Distance [m]

60

140

120

100

80

40

20

0

ASmax=1239∘

Ang

ular

Spr

ead

[∘]

(a)

60 1201008040

00

5

05

10

20

ASAESA

ASDESD

1

08

06

1

04

02

0

CDF


(b)






SA [∘

]


00

100 450150 500200 250 300 350 40050

Distance [m]

60

140

120

100

80

40

20

ASmax= 1239∘

ASmax= 738∘

ASmax= 658∘


5 Conclusion


Data Availability




Acknowledgments



References






































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



10ＦＡ(d0) = 2279d0 = 19010 m

Tunnel aTunnel b

Tunnel cTunnel d

90

80

0

70

50

40105 15 20

60

100


Path

Los

s [dB

]


18 GHz58 GHz

minus20

minus10

minus30

minus40

minus50

minus60

minus70

minus800 100 450150 500200 250 300 350 40050

Distance [m]

11 dB

Rece

ived

Pow

er [d

Bm]





0

60

100 450150 500200 250 300 350 40050

Distance [m]

140

120

100

80

40

Path

Los

s [dB

]









Tunnel aTunnel b

Tunnel cTunnel d

0 100 450150 500200 250 300 350 40050

Distance [m]

0

10

Rici

an K

-fact

or [d

B]

5

15

20

25

30

Part 1

Part 2

(a)

Kmax

Kmax= 2738


= 2653

Tunnel aTunnel b

Tunnel cTunnel d


26 27096

098

1

28 29

20 25 30

08

06

1

04

02

0

CDF

(b)



ParameterMean

K-factor[dB]










Tunnel aTunnel c

0 100 450150 500200 250 300 350 40050Distance [m]

08

06

1

04

02

Del

ay S

prea

d [n

s]12

0

(a)

max= 1059

max= 1157

Tunnel aTunnel c

0996

0998

1

1


11 12

10402 120

08

06

1

04

02

0

CDF

(b)


ASAESA

ASDESD

0

00

5

10

15

100

100

450150 500200 250 300 350 40050

50

Distance [m]

60

140

120

100

80

40

20

0

ASmax=1239∘

Ang

ular

Spr

ead

[∘]

(a)

60 1201008040

00

5

05

10

20

ASAESA

ASDESD

1

08

06

1

04

02

0

CDF


(b)






SA [∘

]


00

100 450150 500200 250 300 350 40050

Distance [m]

60

140

120

100

80

40

20

ASmax= 1239∘

ASmax= 738∘

ASmax= 658∘


5 Conclusion


Data Availability




Acknowledgments



References






































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



Tunnel aTunnel b

Tunnel cTunnel d

0 100 450150 500200 250 300 350 40050

Distance [m]

0

10

Rici

an K

-fact

or [d

B]

5

15

20

25

30

Part 1

Part 2

(a)

Kmax

Kmax= 2738


= 2653

Tunnel aTunnel b

Tunnel cTunnel d


26 27096

098

1

28 29

20 25 30

08

06

1

04

02

0

CDF

(b)



ParameterMean

K-factor[dB]










Tunnel aTunnel c

0 100 450150 500200 250 300 350 40050Distance [m]

08

06

1

04

02

Del

ay S

prea

d [n

s]12

0

(a)

max= 1059

max= 1157

Tunnel aTunnel c

0996

0998

1

1


11 12

10402 120

08

06

1

04

02

0

CDF

(b)


ASAESA

ASDESD

0

00

5

10

15

100

100

450150 500200 250 300 350 40050

50

Distance [m]

60

140

120

100

80

40

20

0

ASmax=1239∘

Ang

ular

Spr

ead

[∘]

(a)

60 1201008040

00

5

05

10

20

ASAESA

ASDESD

1

08

06

1

04

02

0

CDF


(b)






SA [∘

]


00

100 450150 500200 250 300 350 40050

Distance [m]

60

140

120

100

80

40

20

ASmax= 1239∘

ASmax= 738∘

ASmax= 658∘


5 Conclusion


Data Availability




Acknowledgments



References






































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



Tunnel aTunnel c

0 100 450150 500200 250 300 350 40050Distance [m]

08

06

1

04

02

Del

ay S

prea

d [n

s]12

0

(a)

max= 1059

max= 1157

Tunnel aTunnel c

0996

0998

1

1


11 12

10402 120

08

06

1

04

02

0

CDF

(b)


ASAESA

ASDESD

0

00

5

10

15

100

100

450150 500200 250 300 350 40050

50

Distance [m]

60

140

120

100

80

40

20

0

ASmax=1239∘

Ang

ular

Spr

ead

[∘]

(a)

60 1201008040

00

5

05

10

20

ASAESA

ASDESD

1

08

06

1

04

02

0

CDF


(b)






SA [∘

]


00

100 450150 500200 250 300 350 40050

Distance [m]

60

140

120

100

80

40

20

ASmax= 1239∘

ASmax= 738∘

ASmax= 658∘


5 Conclusion


Data Availability




Acknowledgments



References






































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



SA [∘

]


00

100 450150 500200 250 300 350 40050

Distance [m]

60

140

120

100

80

40

20

ASmax= 1239∘

ASmax= 738∘

ASmax= 658∘


5 Conclusion


Data Availability




Acknowledgments



References






































RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia



























RoboticsJournal of




VLSI Design



Shock and Vibration







Journal of



Volume 2018



Volume 2018


Journal of




SensorsJournal of



RotatingMachinery





Propagation






Hindawi


Advances in

Multimedia


channel characteristics of rail traffic tunnel scenarios based on...

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