Proposal of Channel Estimation Method for ITS systems by

36 ECTI TRANSACTIONS ON COMPUTER AND INFORMATION TECHNOLOGY VOL.8, NO.1 May 2014

Proposal of Channel Estimation Method forITS systems by using STBC MIMO-OFDM

Tanairat Mata1 , Member, Katsuhiro Naito2 , Pisit Boonsrimuang3 ,

Kazuo Mori4 , and Hideo Kobayashi5 , Non-members

ABSTRACT

This paper proposes a new road-to-vehicle com-munication system for the future ITS by using theSTBC MIMO-OFDM technique which can providethe safety and comfortable driving, and collection ofvariable information from the network in the real-time to the users on the vehicle. To realize the pro-posed STBC MIMO-OFDM system, it is requiredto estimate the channel frequency response at ev-ery symbol precisely in the time varying fading chan-nel which is the typical operation conditions for theroadto-vehicle communications system. In this paper,we propose a novel channel estimation method by us-ing the scattered pilots and null sub-carriers insertedinto the data sub-carriers both in the frequency andtime axes which enables the accurate channel esti-mation even in the higher time varying fading chan-nel. From the computer simulation results, this pa-per demonstrates the effectiveness of proposed systemwhich can achieve the higher transmission data ratewith keeping the higher signal quality even under thehigher mobile ITS environments.

Keywords: OFDM, MIMO, STBC, ITS, RVC

1. INTRODUCTION

Intelligent Transport Systems (ITS) have been ex-panding with the popularization of Electrical TollCollection System (ETC) and the Vehicle Informa-tion communication Systems (VICS) which enablethe drivers for the safety and comfortable driving, andcollection of variable information from the network inthe real-time [1-3]. Various transmission techniquesfor the communications systems in the ITS are cur-rently studying in the various projects and some ofthem have already been standardized in the ITS sys-tems.

Manuscript received on July 15, 2013 ; revised on November7, 2013.Final manuscript received December 8, 2013.1,2,4,5 The authors are with Electrical and Electronic En-

gineering, Graduate School of Engineering, Mie Univer-sity, Tsu-shi, 514-8507 Japan., Email:[email protected], [email protected], [email protected], [email protected] The author is with Telecommunication Engineering, Fac-

ulty of Engineering, King Mongkut’s Institute of TechnologyLadkrabang, 10520 Thailand., Email:[email protected]

From the above backgrounds, the ITS could be-come an advanced information network systems forthe transportation infrastructures which are essentialto greatly improve our social activities and the qualityof our social life. The Communications systems forthe ITS can be classified into the road-to-vehicle com-munication (RVC) and the vehicle-to-vehicle commu-nication (VVC). The communication services throughthe RVC has been investigated to provide variouskinds of information to the users on vehicles. Inthe RVC, the received signal power at the vehicle de-creases as increasing the distance from the base sta-tions located along the road. The received signal isalso fluctuated in the short time period due to thetime varying multipath fading when the vehicles aremoving at high speed. These conditions cause the fa-tal degradation of bit error rate (BER) performancein the RVC. From this fact, the achievable transmis-sion data rate in the current RVC is insufficient toprovide the mobile multimedia communications ser-vices to the users on the vehicles.

The IEEE 802.11p is adopted as the standardspecifications for the VVC and RVC in the ITS[4]. The IEEE 802.11p employs the Orthogonal Fre-quency Division Multiplexing (OFDM) as the trans-mission technique in the 5GHz band used by theIEEE 802.11a. Although the OFDM technique canachieve high signal quality in the multipath fadingchannel, this standard is insufficient to achieve thehigher transmission data rate with the higher signalquality especially in the higher time varying fadingchannels which are typical operation environments inthe ITS.

To solve the above problems, this paper pro-poses a new RVC system by using the STBC (SpaceTime Block Coding) MIMO (Multiple Input Mul-tiple Output)-OFDM [5-6] technique for the futureITS which can provide the mobile multimedia com-munications services to the users on the vehicle. Torealize the proposed STBC MIMO-OFDM systems,the channel estimation method is required as the keytechnique which enables the accurate channel esti-mation at every symbol in the higher time varyingfading channels. This paper proposes a channel esti-mation method by using the scattered pilot and nullsub-carriers which enables the demodulation of mul-tiplexed signal encoded with the STBC. The pro-posed STBC MIMO-OFDM system in conjunction

Proposal of Channel Estimation Method for ITS systems by using STBC MIMO-OFDM 37

H1=10m.

H2=1m.

DD0=200m.

DD1 DD2

PL1 PL2

BS#1 BS#2

v

θ�

θ�

H1=10m.MS

Fig.1: Overview of proposed system model

Mod Pilot Insertion

STBC encoding

DEMOD

STBC decoding

BS#1

BS#2

MS#1

MS#2

h11(m,k)

s2(m,k)

s1(m,k) h12(m,k)

h21(m,k)

h22(m,k)

Data

Data ( , )D m n

ˆ ( , )D m n

( , )X m n

IFFT/+GI

IFFT/+GI

r1(m,k)

r2(m,k)FFT/-GI

w2(m,k)

w1(m,k)R1(m,n)

R2(m,n)

ˆ ( , )X m n

ˆ( 1, )+X m n

12ˆ ( , )H m n

22ˆ ( , )H m n

11ˆ ( , )H m n

21ˆ ( , )H m n

Combiner

Channel estimator

Channel estimator FFT/-GI

S2(m,n)

S1(m,n)

Fig.2: Block diagram of proposed STBC MIMO-OFDM transceiver

with the proposed channel estimation method canachieve higher transmission data rate with keepingthe higher signal quality even in the time varying fad-ing channels.

This paper is organized as follows. Section 2 showsthe proposed STBC MIMO-OFDM system model,and Section 3 proposes a channel estimation methodfor the proposed system by using the scattered pilotsub-carriers assignment method. Section 4 presentsthe various computer simulation results to verify theeffectiveness of the proposed method as comparedwith the conventional methods. Finally Section 5draws some conclusions.

2. PROPOSED SYSTEM MODEL

Figure 1 shows the proposed STBC MIMO-OFDMsystem model to be used in this paper. The vehicle(MS ) with two receiving antennas receives the OFDMsignals with STBC encoded by Alamounti scheme [5]from both base stations (BS#1 and BS#2 ) locatedalong the road. The communication channel is mod-elled by the Rician fading including one direct pathand several reflected paths which follows the Rayleighfading. In Fig.1, PL represents the propagation lossbetween the BS and MS, θ is the signal arrival anglefrom the BS to the MS, and DD1 and DD2 are thedistances from the BS#1 and BS#2 to MS, respec-tively.

Figure 2 shows the block diagram of proposedSTBC MIMO-OFDM transceiver. In Fig.2, D(m,n)is the modulated information signal at the n-th sub-

carrier of m-th symbol in the frequency domain,X(m,n) is the modulated signal after insertion of scat-tered pilot signals, and S1(m,n) and S2(m,n) aretransmission signals from BS#1 and BS#2 whichare encoded by STBC. The STBC encoded signalsS1(m,n) and S2(m,n) are converted to the time do-main signal by using IFFT, and the guard interval(GI) is added to avoid the inter-symbol-interference(ISI). The time domain signal is transmitted to theMS receiver through the Rician fading channel withhaving the time impulse response hij(m,k) at the k-th time sampling of m-th symbol. At the receiver,r1(m,k) and r2(m,k) including the additive whiteGaussian noise w(m,k) are received at the MS re-ceiving antenna MS#1 and MS#2, respectively. Thereceived time domain signals are converted to thefrequency domain signal R1(m,n) and R2(m,n) byFFT after removing the GI. The received frequencydomain signal inputs to the channel estimator toestimate the channel frequency response (CFR) for

Hij(m,n) which represents the channel response fromBS#i to MS#j link at the n-th sub-carrier of m-thsymbol. The received signal also inputs to the com-biner to detect the modulated signals X(m,n) and

X(m+1, n) at the n-th sub-carrier of m and (m+1)-th symbols, respectively.

In the STBC MIMO-OFDM system with theAlamounti coding, the modulated information dataX(m,n) is encoded into two signals S1 and S2 as givenby the following equation;

S1(m,n) = X(m,n),S1(m+ 1, n) = −X∗(m+ 1, n),

S2(m,n) = X(m+ 1, n),S2(m+ 1, n) = X∗(m,n).

(1)

To easily understand the process at the receiver,we divide the processes into 4 parts as follows;

PART 1 : Received Signal

The frequency domain received signal R1(m,n)and R2(m,n) at MS#1 and MS#2 can be given by;

At MS#1,

R1(m,n) = H11(m,n)S1(m,n)+H21(m,n)S2(m,n).

R1(m+ 1, n) = H11(m+ 1, n)S1(m+ 1, n)+H21(m+ 1, n)S2(m+ 1, n).

(2)

At MS#2,

R2(m,n) = H12(m,n)S1(m,n)+H22(m,n)S2(m,n).

R2(m+ 1, n) = H12(m+ 1, n)S1(m+ 1, n)+H22(m+ 1, n)S2(m+ 1, n).

(3)

Substituting (1) into (2) and (3), they can berewritten by the following equation;


At MS#1,

R1(m,n) = H11(m,n)X(m,n)+H21(m,n)X(m+ 1, n).

R1(m+ 1, n) = −H11(m+ 1, n)X∗(m+ 1, n)+H21(m+ 1, n)X∗(m,n).

(4)

At MS#2,

R2(m,n) = H12(m,n)X(m,n)+H22(m,n)X(m+ 1, n).

R2(m+ 1, n) = −H12(m+ 1, n)X∗(m+ 1, n)+H22(m+ 1, n)X∗(m,n).

(5)

PART 2 : Channel EstimatorThe details of the CFR estimation method is pro-

posed in Section 3.

PART 3 : Combining SchemeFrom (4) and (5), X(m,n) can be rewritten into

the following equations by using the CFR Hij(m,n)estimated in Part 2;At MS#1,

XMS#1(m,n) = H∗11(m,n)R1(m,n)

+H21(m+ 1, n)R∗1(m+ 1, n).

XMS#1(m+ 1, n) = H∗21(m,n)R1(m,n)

−H11(m+ 1, n)R∗1(m+ 1, n).

(6)

At MS#2,

XMS#2(m,n) = H∗12(m,n)R2(m,n)

+H22(m+ 1, n)R∗2(m+ 1, n).

XMS#2(m+ 1, n) = H∗22(m,n)R2(m,n)

−H12(m+ 1, n)R∗2(m+ 1, n).

(7)

From (6) and (7), we obtain the combined receivedsignals as follows;

X(m,n) = H∗11(m,n)R1(m,n)

+H21(m+ 1, n)R∗1(m+ 1, n)

+H∗12(m,n)R2(m,n)

+H22(m+ 1, n)R∗2(m+ 1, n).

(8)

X(m+ 1, n) = H∗21(m,n)R1(m,n)

−H11(m+ 1, n)R∗1(m+ 1, n)

+H∗22(m,n)R2(m,n)

−H12(m+ 1, n)R∗2(m+ 1, n).

(9)

PART 4 : STBC decodingThe information data after the STBC decoding can

be given by;

D(m,n) = d(m,n)X(m,n)−b(m,n)X(m+1,n)a(m,n)d(m,n)−b1(m,n)c1(m,n)

D(m+ 1, n) = a(m,n)X(m+1,n)−c(m,n)X(m,n)a(m,n)d(m,n)−b(m,n)c(m,n)

(10)

where

a(m,n) = Ai(m,n) +Ai+1(m,n),b(m,n) = Bi(m,n) +Bi+1(m,n),c(m,n) = Ci(m,n) + Ci+1(m,n),d(m,n) = Di(m,n) +Di+1(m,n).

Ai(m,n) =∣∣∣H1i(m,n)

∣∣∣2 + ∣∣∣H2i(m+ 1, n)∣∣∣2 ,

Bi(m,n) = H∗1i(m,n)H2i(m,n)

−H∗1i(m+ 1, n)H2i(m+ 1, n),

Ci(m,n) = H1i(m,n)H∗2i(m,n)

−H1i(m+ 1, n)H∗2i(m+ 1, n),

Di(m,n) =∣∣∣H1i(m+ 1, n)

∣∣∣2 + ∣∣∣H2i(m,n)∣∣∣2 .

3. PROPOSAL OF CHANNEL ESTIMA-TION METHOD

In this section, we propose the channel estima-tion method for the proposed STBC MIMO-OFDMsystem. Firstly, we define the Rician fading chan-nel which consists of one direct path and several re-flected paths which follows the Rayleigh distribution.Secondly, we propose the scattered pilot and null sub-carriers assignment method both in the frequency andtime axes which enables the estimation of CFR forthe multiplexed signal with STBC coding transmit-ted from both BSs. Finally, we propose the CFRestimation method by using the the Maximum Like-lihood (ML) method in the frequency axis and thecubic spline interpolation method which enables thedemodulation of received signal with the STBC cod-ing.

3.1 Fading Channel Model

The channel impulse responses htr(m, k) in the Ri-cian Fading Channel between the t-th transmittingantenna at the BS#t and the r-th receiving antennaat the MS#r can be given by;

htr(m, k) =NP∑l=1

ρ(l)tr (m) · δ(k − l)

ρ(l)tr (m) =

Cl∑s=1

µls · ej2πfD cos(φls)m

(11)

where t (=1,2) and r(=1,2) represent the Tx antenna

and Rx antenna numbers, ρ(l)tr is the channel impulse

response in the time domain between the t-th trans-mitting antenna and the r-th receiving antenna forthe l-th delay path, NP is the number of delay paths,µls is the coefficient of scattered path for the s-th ar-rival angle of l-th delay path, Cl is the number ofscattered paths for the delay path l, and fD is themaximum Doppler frequency spread at the speed ofthe vehicle v (km/hr) in the radio frequency (fc).

By using (11), the time domain received signalr1(m,k) and r2(m,k) at each receiving antenna at theMS can be given by;At MS#1,

r1(m, k) = {h11(m, k)⊗ s1(m, k)} · PL1+ {h21(m, k)⊗ s2(m, k)} · PL2 + w1(m, k).

(12)

At MS#2,

r2(m, k) = {h12(m, k)⊗ s1(m, k)} · PL1+ {h22(m, k)⊗ s2(m, k)} · PL2 + w2(m, k).

(13)


where ⊗ denotes the convolution operation. Here,the channel frequency response Htr(m,n) can be ob-tained by converting the channel impulse responsegiven in (11) to the frequency domain by FFT whichis given by;

Htr(m,n) =NP∑l=1

ρ(l)tr (m) · e

−j2π(l−1)(n−1)N . (14)

3.2 Scattered Pilot Sub-carrier AssignmentMethod

From (14), it can be seen that the channel fre-quency response under the high mobile environmentsis required to estimate at every symbol for the fre-quency domain equalization of received signal. Fromthis fact, this paper proposes three types of pilot sub-carrier assignment methods to be used in the estima-tion of channel frequency response. Figure 3 showsthe pilot sub-carriers assignment method for Type I[7], Type II and Type III. In the figure, FIP and TIPrepresent the interval of sub-carriers in the frequencyaxis and interval of pilot symbols including the pi-lot sub-carriers in the time axis. The followings arethe details for these three types of pilot sub-carriersassignment methods.

Type I : As shown in Fig.3(a),every symbol in thetime axis includes the pilot sub-carriers and null sub-carriers inserted into the data sub-carrier with theinterval of FIP in which the locations of all pilot sub-carriers for the BS#1 are assigned by the null sub-carriers for the BS#2 so as to avoid the collision ofpilot sub-carriers between the received signals at theMS from BS#1 and BS#2. From this assignmentmethod, the MS can estimate the CFRs at the pilotsub-carriers for both links from the BS#1 and BS#2,separately. By using the estimated CFR at the pi-lot sub-carriers, the CFR over the OFDM frequencybandwidth can be estimated at every symbol basedon the ML method which is presented in Section 3.3.

Type II : As sown in Fig.3(b), consecutive two sym-bols with the interval of TIP include both the pilotand null sub-carriers or two null sub-carriers insertedinto the data sub-carrier with the interval of FIP.The pilot sub-carriers assignment method for the pi-lot symbols including both the pilot and null sub-carriers with the interval TIP is the same as Type I.The null sub-carriers for the pilot symbols includingonly the null sub-carriers are assigned at the consecu-tive two sub-carriers with the interval of FIP. All datasub-carriers except the pilot and null sub-carriers areencoded by the STBC over the consecutive two sym-bols. The estimation of CFR both for the frequencyand time axes for the Type II is the same as the TypeI. Here it should be noted that the null sub-carrier isassigned at the location of pilot sub-carrier in the firstpilot symbol within the consecutive two pilot symbolsfrom the reason that the consecutive two symbols areencoded by the STBC.

Type III : As shown in Fig.3(c), the consecutive twopilot symbols in which the pilot and null sub-carriersassignment method are the same as the Type I, areinserted into the data symbols with the interval ofTIP in order to improve the CFR estimation accu-racy. From this assignment method, it is possible touse the estimated CFR over the consecutive two pilotsymbols for improving the CFR estimation accuracy.

Table 1: Transmission Efficiency η (%)Type Transmission Efficiency η (%)

I 50.0%II 85.2%III 85.2%

Table 1 shows the transmission efficiency η for theabove three types of pilot sub-carriers assignmentmethods. In the evaluation, the FIP and TIP are4 and 1 for Type I and 4 and 8 for Type II and TypeIII. From the table, it can be observed that Type IIand Type III show the higher transmission efficiencythan the Type I.

3.3 Channel Estimation method

In the previous section, we propose three types ofscattered pilot sub-carriers assignment methods. Inthis section, we propose the channel estimation (CE)method by using the scattered pilot sub-carriers forthe STBC MIMO-OFDM system. The CFR can beestimated in both the frequency and time axes sep-arately. For the frequency axis, the CFR over theOFDM frequency bandwidth can be estimated by ap-plying the Maximum Likelihood (ML) method [7-9]for the estimated CFR at the pilot sub-carriers. Forthe time axis including the data symbols, the CFRover one frame can be estimated by applying thecubic spline interpolation method for the estimatedCFR over the OFDM frequency bandwidth at the pi-lot symbols. In this section, the ML method for thefrequency axis and interpolation method for the timeaxis are presented.

The time domain signals given in (12) and (13) areconverted to the frequency domain signals R1(m,n)and R2(m,n) by FFT which can be expressed by thefollowing;At MS#1,

R1(m,n) = H11(m,n)S1(m,n)PL1+H21(m,n)S2(m,n)PL2 +W1(m,n).

(15)

At MS#2,

R2(m,n) = H12(m,n)S1(m,n)PL1+H22(m,n)S2(m,n)PL2 +W2(m,n).

(16)

By dividing (15) and (16) by the known pilotsub-carrier data, the CFRs SP1(mp(k),np1(i)) andSP2(mp(k),np2(i)) at the location of pilot sub-carriers can be estimated as follows;


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NPilot Sub-carrier Null Sub-carrier Data Sub-carrier

BS#

1B

S#2

Frequency Axis

Tim

e A

xis

(a) Type I (b) Type II (c) Type III

Fig.3: Three types of scattered pilot sub-carriers assignment methods

At MS#1,

H11(mp(k), np1(i)) =R1(mp(k),np1(i))SP1(mp(k),np1(i))

− W1(mp(k),np1(i))SP1(mp(k),np1(i))

,



.

(17)

At MS#2,



,



.

(18)

where the pilot symbol number mp(k) and pilot sub-carrier number np1(i) for the BS#1 and np1(i) forthe BS#2 are given by;

mp(k) = (k − 1)TIP + 1 if k = 1 ∼ L/TIP + 1,np1(i) = (i− 1)FIP + 1, andnp2(i) = (i− 1)FIP + 2 if i = 1 ∼ N/FIP.

Since W1 and W2 are uncorrelated Gaussian variablein (17) and (18), the ML solution of both equationscomes into the minimum square error (MSE) opti-mization problem. To estimate the CFR precisely,the number of guard interval length (Ng) must betaken by larger than NPi. The unknown parameters

for the channel impulse response (CIR) ρ(l)xr(mp(k)) ,

where x is BS#1 or #2, can be obtained by;

LML(ρ(l)xr(mp(k)))

= argminρ(l)xr (mp(k))

NPi∑i=1

∣∣∣∣∣∣∣Hxr(mp(k), npx(i))

−Ng∑l=1

{ρ(l)xr(mp(k))

·e−j2π(l−1)(npi(i)−1)

N

} ∣∣∣∣∣∣∣2

ρ(l)xr(mp(k)) =

[ρ(1)xr (mp(k)), ...., ρ

(Ng)xr (mp(k))

](19)

Taking ∂(19)/∂ρ

∗(l)xr (mp(k)) = 0, where (*) denotes

conjugate, (19) can be expressed by the following;

NPi∑i=1

[{Hxr(mp(k), npx(i))

−Ng∑l=1

ρ(l)xr(mp(k)) · e

−j2π(l−1)(npx(i)−1)N }

·Ng∑ll=1

ej2π(ll−1)(npx(i)−1)

N ] = 0.

(20)

From (20), it can be rewritten as following;

NPi∑i=1

Ng∑ll=1

HfromBS#x(mp(k), npx(i)) · ej2π(npx(i)−1)(ll−1)

N

=NPi∑i=1

Ng∑l=1

Ng∑ll=1

ρ(l)xr(mp(k)) · e−j

2π(npx(i)−1)(l−ll)N .

(21)


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#1ˆ ( , )INTPijH m n


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Fig.4: Proposed CFR estimation method for TypeIII

From (21), since the dependence from optimization

parameters ρ(l)xr(mp(k)) is linear in (21), its solution

can be realized by the Moore-Penrose generalized ma-trix inversion which can be given by;[

ρ(l)xr(mp(k))

]= † [D] • [B(mp(k), npx(i))] . (22)

where[ρ(l)xr(mp(k)

]is the (Ngx1) matrix of the

ρ(l)xr(mp(k), [B(mp(k), npx(i))] is the(Ngx1) matrix of

the Rr(mp(k), npx(i))/SPx(mp(k), npx(i)),[D ] is the(NgxN) matrix of the exp(−j2π(npx(i)−1)(l−ll)/N).† denotes the Moore-Penrose inverse and • denotesmatrix multiplication. Because the matrix [D] de-pends on the locations of pilot sub-carriers and theyare known at the receiver, the Moore-Penrose inversematrix can be calculated in advance at the receiver.From this fact, the computation complexity for theestimation of CFR can be reduced relatively. The fre-quency channel response over the OFDM frequencybandwidth can be obtained by converting the CIRgiven in (22) to the frequency domain by FFT.

As for the estimation of CFR in the time axis, thecubic spline interpolation method is applied to theestimated CFR which is given by using ML methodas mentioned above. As for the Type III, the CFRs ofpilot symbol#1 and pilot symbol#2 with the intervalof TIP are estimated by performing two interpola-tions separately as shown in Fig. 4. From Fig. 4,it can be seen that the CFR for the pilot symbol#1

and pilot symbol#2 are interpolated every mp(k) =(k− 1)TIP +1 and mp(k) = (k− 1)TIP +2, respec-

tively. Then HINTP#1ij (m,n) and HINTP#2

ij (m,n)can be estimated for each interpolation. Where i andj are the index of BS and the receiving antenna, andINTP#1 and INTP#2 denote the interpolations 1and 2, respectively. By using two estimated CFR,the estimation accuracy of CFR can be improved bytaking the average of them which is given by,

Hij(m,n)

= mean[HINTP#1

ij (m,n) + HINTP#2ij (m,n)

].

(23)

Figure 5 shows the estimation results of CFRHij(m,n) which is given by (23). From the figure,

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plitu

de |H

(m,n

)| 2

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ˆ ( , )ijH m nProposed

Ideal

Fig.5: Example of the average estimated signal[Hij(m,n)] in (23)

it can be observed that the estimation accuracy ofCFR for the proposed method is better than thoseof using HINTP#1

ij (m,n) and HINTP#2ij (m,n) sepa-

rately and the estimation accuracy for the proposedestimation method given in (23) is closed to the idealCFR.

4. PERFORMANCE EVALUATION

This section presents the various computer simu-lation results to select the best pilot sub-carriers as-signment method and to verify the effectiveness of theproposed STBS MIMO-OFDM system in conjunctionwith the proposed CFR estimation method. The sim-ulation parameters used in the following evaluationsare listed in Table 2.

Figure 6 shows the CFR estimation accuracy forthree types of pilot sub-carriers assignment methodsas shown in Fig.3 when changing the distance fromboth base stations BS#1 and BS#2 to the vehicle(MS ). In the figure, the normalized minimum meansquare error (NMSE) is employed in the evaluationof estimation accuracy of CFR. From Fig.6, it can

Table 2: Simulation parametersInformation ParameterModulation for data sub-carriers 64QAMDemodulation CoherentNumber of Sub-carriers (N) 128Symbol Duration (Ts) 12.8µSecGuard Interval Duration (Tsg) 1.2µSecNumber of Sample points in GI (Ng) 12Modulation of Pilot sub-carriers QPSKInterval of Pilot Symbol (TIP) 1,4,8,16Interval of Pilot Sub-carrier (FIP) 1,4,8,16OFDM Occupied Bandwidth (W) 10MHzRadio Frequency (fc) 5.4GHzRician fading channel modelRice Factor(K) 6dBCNR at BS#1 and BS#2 50dBDelay Profile ExponentialDecay Constant -1dBNumber of delay paths (NP) 4Number of scattered paths (Cl) 20


� ��

��

��

��

��

��

��

��

��

��

��

Distances from BS#1 and BS#2 to Vehicle (m)

NM

SE

��

��

��

Fig.6: The channel estimation accuracy for threetypes of pilot sub-carriers assignments methods

be seen that the channel estimation accuracy of theCFRs for the BS#1 to MS link and BS#2 to MSlink are degraded and improved, respectively, untilat the center of location between both base stations(DD1 is 100m). It can be also observed that thechannel estimation accuracy of proposed Type III isbetter than that for both Type I and Type II. Fromthese results and the transmission efficiency as shownin Table 1, it can be concluded that the Type IIIwith the channel estimation method given in (23) isthe best pilot sub-carrier assignment method for theproposed STBC MIMO-OFDM system.

In the following, we optimize the parameters forthe intervals of FIP and TIP under the typical RVCenvironments. The selection of these parameters ismuch dependent on the fading conditions which in-cludes the number of delay paths and vehicle speed.In this paper, we employ the Rician fading modelwhich is the typical operation conditions for the RVC.The Rician fading model employed in this paper con-sists of one direct path and 4 reflected paths whichfollow the Rayleigh distribution. The vehicle speedis considered in this paper up to 200km/h. Underthese operation conditions, we conduct the computersimulations and decide the parameters of FIP andTIP which can achieve the better estimation accu-racy even under the higher mobile environments upto 200km/h.

Figure 7 shows the channel estimation accuracy forthe proposed CFR estimation method with Type IIIwhen the intervals of FIP are 4, 8, and 16, and the in-terval of TIP is fixed by 8. In the figure, the channelestimation accuracy is evaluated by the NMSE whenchanging the speed of the vehicle (km/h). From thefigure, it can be observed that the estimation accu-racy for the proposed method can achieve the betterperformance when the FIP is 4 even at 200km/h ve-hicle speed.

Figure 8 shows estimation accuracy for the pro-posed CFR estimation method with Type III whenthe intervals of TIP are 4, 8, and 16, and the interval

0 50 100 150 20010

-4

10-3

10-2

Speed of Vehicle (km/h)

NM

SE

Proposed Type III with FIP = 4.

Proposed Type III with FIP = 8.Proposed Type III with FIP = 16.

Fig.7: Channel estimation accuracy for the proposedType III method (FIP= 4, 8 and 16, and TIP=8)

0 50 100 150 20010

-4

10-3

10-2

10-1

Speed of Vehicle (Km/h)

NM

SE

Proposed Type III with TIP = 4.

Proposed Type III with TIP = 8.Proposed Type III with TIP = 16.

Fig.8: Channel estimation accuracy for the proposedType III method (TIP = 4, 8 and 16, and FIP=4)

of FIP is fixed by 4 which is obtained from the re-sults of Fig.7. From the figure, it can be seen that theestimation accuracy can keep the better performancewhen the interval of TIP is less than 8. From theresults in Figs.7 and 8, it can be concluded that theproposed CFR estimation method by using Type IIIcan achieve the better estimation accuracy with keep-ing the better transmission efficiency when FIP is 8and FIP is 4 even under higher mobile environments.The following evaluations for the BER performanceemploys 8 and 4 for the intervals of TIP and FIP,respectively.

Figure 9 shows the BER performance of the pro-posed Type III method of using one and two receivingantennas at the MS when changing the carrier-to-noise ratio (CNR). In the simulation, the vehicle islocated at the center of two base stations (DD1 is100m as shown in Fig.1) which corresponds to theworst condition for the road-to-vehicle communica-tion. The operation CNR is 50dB which is definedat the right beneath of BS#1. The vehicle speed is200km/h, and the FIP and TIP intervals are 4 and8, respectively. The conventional-OFDM employs the


20 25 30 35 40 45 5010

-7

10-6

10-5

10-4

10-3

10-2

10-1

100

CNR(dB)

BE

R

Conventional-OFDM with 2x1 antenna.

Conventional-OFDM with 2x2 antenna by using MRC.Proposed Type III with 2x1 antenna.

Proposed Type III with 2x2 antenna.

Fig.9: BER performance of the proposed Type IIImethod when changing CNR

0 20 40 60 80 10010

-7

10-6

10-5

10-4

10-3

10-2

10-1

100

Distance from BS#1(m)

BE

R

Conventional-OFDM with 2x1 antenna.Conventional-OFDM with 2x2 antenna by using MRC.

Proposed Type III with 2x1 antenna-Assuming H(m,n)=H(m+1,n)

Proposed Type III with 2x2 antenna-Assuming H(m,n)=H(m+1,n)

Proposed Type III with 2x1 antenna.Proposed Type III with 2x2 antenna.

Fig.10: BER performance of the proposed methodwhen changing the distance from the base station#1(BS#1) to the vehicle (MS)

Single Frequency Network technique (SFN) [10] inwhich both base stations transmit the same OFDMdata information and the MS can demodulates thedata information correctly from the multiplexed re-ceived signal when the maximum delay time deferencefor two received signals from the BS#1 and BS#2 iswithin the guard interval length Ng. The SFN tech-nique is employed in the terrestrial digital TV sys-tem of using OFDM method. In the figure, the BERperformances for both conventional-OFDM with andwithout the Maximum Ratio Combining (MRC) [11]technique are also shown as for the purpose of com-parison with the proposed method. From the figure,it can be observed that the proposed method with2x2 antennas shows much better BER performancethan that for the conventional OFDM of using SFNand MRC techniques.

Figure 10 shows the BER performance of the pro-

posed method of using one and two receiving an-tennas at the MS when changing the distance fromBS#1 to the MS. In the simulation, the opera-tion CNR is 50dB which is defined at the right be-neath of BS#1 and the vehicle speed is 200km/h.In the figure, the BER performances for the con-ventional OFDM method of using SFN and MRCtechniques, and the proposed method when assum-ing the H(m,n)=H(m+1,n) are also shown. Fromthe figure, it can be observed that the proposedmethod with two receiving antennas shows much bet-ter BER performance than the other methods espe-cially when the vehicle is located at the center of twobase stations (DD1 is 100m) which corresponds tothe worst case in the road to vehicle communica-tions. The BER performance of proposed methodwhen assuming H(m,n)=H(m+1,n) is worse than theconventional OFDM methods. From these results,the channel estimation is required at every symbolfor the proposed STBC MIMO-OFDM system underhigher mobile environments. From these results, itcan be concluded that the proposed STBC MIMO-OFDMmethod with the pilot sub-carriers assignmentmethod of Type III has a big advantage on the road tovehicle communication systems (RVCs) because thehigher transmission data rate with better BER per-formance can be achieved at any place of vehicle be-tween two base stations.

5. CONCLUSIONS

This paper proposed the new road-to-vehicle com-munication system for the future ITS which can pro-vide the mobile broadband multimedia wireless com-munications. The salient features of the proposedmethod are to employ the STBC MIMO-OFDM tech-niques and channel estimation method of using thescattered pilot sub-carriers both for the frequencyand time axes. From the various computer simulationresults, this paper demonstrated the effectiveness ofthe proposed STBC MIMO-OFDM system with TypeIII pilot sub-carriers assignment method even in thehigher time varying fading channel.

ACKNOWLEDGEMENT

The authors would like to thank to the JapaneseGovernment (Monbukagakusho:MEXT) Scholarshipswho has supported this research.

References

[1] W.-Y. Shieh, C.-C.J. Hsu, S.-L. Tung, P.-W. Lu,T.-H. Wang, and S.-L. Chang, “Design of In-frared Electronic-Toll-Collection Systems WithExtended Communication Areas and Perfor-mance of Data Transmission,” Intelligent Trans-portation Systems, IEEE Trans, Vol.12, pp.25-35, Mar. 2011.


[2] Y. Hattori, T. Shimoda, and M. Ito, “Develop-ment and Evaluation of ITS Information Com-munication System for Electric Vehicle,” in Proc.of VTC Spring 2012, pp.1-6, May 2012.

[3] A. Ono, K. Naito, K. Mori, and H. Kobayashi,“Roadside to Vehicle Communication Systemwith OFDM Cooperative Transmission,” inProc. of APWCS2011, MP2-7, Aug.2011.

[4] D. Jiang, and L. Delgrossi, “IEEE 802.11p: To-wards an International Standard for WirelessAccess in Vehicular Environments,” in Proc. ofVTC Spring 2008, pp.2036-2040, May 2008.

[5] S.M.Alamouti, “A simple transmit diversitytechnique for wireless communications,” IEEEJ. Select. Areas Commun, Vol.16, pp.1451-1458,Oct.1998.

[6] T. Mata, P. Boonsrimuang, P. Boonsrimuang,and H. Kobayashi, “Proposal of Improved PTSMethod for STBC MIMO-OFDM Systems,”IEICE Trans. Comm. Lett., Vol.E93B, no.10,Oct.2010.

[7] T. Mata, K. Naito, P. Boonsrimuang, K. Mori,and H. Kobayashi, “Proposal of STBC MIMO-OFDM for ITS Systems,” in Proc. of ECTI-CON2013, May 2013.

[8] G. Mkrtchyan, “Estimation, Parameter learn-ing and Prediction of Time-varying communica-tion channels,” Ph.D dissertation, Mie univer-sity, Sep. 2006.

[9] H. Kobayashi and K. Mori, “Proposal of chan-nel estimation method for OFDM systems un-der Time-varying fading environments,”IEICETrans Comm., Vol.J90B, no.12, Dec. 2007.

[10] G. Santella, R. De Martino, and M. Ricchiuti,“Single frequency network (SFN) planning fordigital terrestrial television and radio broadcastservices: the Italian frequency plan for T-DAB,”in Proc. of VTC Spring 2004, Vol.4, pp.2307-2311, May 2004.

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Tanairat MATA received the B.Eng(1st class honors) and M.Eng degrees inTelecommunications Engineering fromKing Mongkut’s Institute of Tech-nology Ladkrabang(KMITL),Thailandin 2007,and 2010,respectively.And Heworked in Strong Brothers1961 Co.,Ltd.,Thailand from 2007 to 2012.He is cur-rently a Ph.D candidates at the MieUniversity,Japan.He research interestsinclude mobile communications,wireless

LAN systems, MIMO-OFDM system,and the next generationITS communication systems.

Katsuhiro NAITO was born inTokyo, Japan in 1977. He received theB.S. degree in Electronics Engineeringfrom Keio University, Japan in 1999,and received the M.S. and Ph.D. degreesin Information Engineering from NagoyaUniversity, Japan in 2001 and 2004, re-spectively. From 2001 to 2004, he was aresearch fellow of the Japan Society forthe Promotion of Science. Since 2004, hehas been an Assistant Professor of the

Department of Electrical and Electronic Engineering at MieUniversity, Japan. He was a visiting scholar at University ofCalifornia, Los Angeles in 2011. His current research interestsinclude the packet radio networks, wireless internet access, andad hoc network. Dr.Naito is a member of IEEE and IPSJ.

Pisit Boonsrimuang received theB.Eng, M.Eng,and Doctor degrees inTelecommunications Engineering, in1997,2000,and 2007 respectively.He iscurrently an associate professor at theKing Mongkut’s Institute of Technol-ogy Ladkrabang(KMITL),Thailand.Hisresearch interests include transmissiontechniques for future multimedia wire-less LAN systems and next generation ofmobile communication systems. He re-

ceived the Student Award of Young Research’s EncouragementAward from IEICE Tokai branch and Doctor Thesis Award forinformation technology from Nation Research Council of Thai-land(NRCT) in 2005 and 2008,respectively.

Kazuo Mori received the B.E. degreein computer engineering from NagoyaInstitute of Technology, Japan, in 1986and received the Ph.D. degree in in-formation electronics engineering fromNagoya University, Japan in 2000. In1986, He joined the Hyper-media Re-search Center, SANYO Electric Co.,Ltd. and was engaged in research anddevelopment on telecommunication sys-tems. From 1995 to 2000, he was a re-

search engineer at YRP Mobile Telecommunications Key Tech-nology Research Laboratories Co., Ltd., where he was engagedin research on mobile communication systems. Since August2000 he has been with Mie University, Japan, where he is cur-rently a Professor in the division of Electrical and ElectronicEngineering, Graduate School of Engineering. During 2005–2006, he was a Visiting Research Fellow at King’s College Lon-don, UK. His research interests include mobile communicationsystems, wireless sensor networks, radio resource management,and teletraffic evaluation. Dr. Mori is a member of IEEE.

Hideo Kobayashi received the B.E.,M.E., and Dr.E. degrees in 1975, 1977and 1989, respectively from Tohoku Uni-versity. He joined KDDI in 1977, andengaged in research on digital fixedsatellite and mobile satellite communi-cations systems. From 1988 to 1990,he was with INMARSAT as a TechnicalStaff and involved in the development offuture INMARSAT systems. Since 1998he has been a Professor of Mie Univer-

sity. His current research interests include mobile communica-tions and wireless LAN systems.

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