Hindawi Publishing CorporationJournal of Electrical and Computer EngineeringVolume 2012, Article ID 571985, 10 pagesdoi:10.1155/2012/571985

Research Article

Interference Cancellation Using Replica Signal forHTRCI-MIMO/OFDM in Time-Variant Large Delay SpreadLonger Than Guard Interval

Yuta Ida,1 Chang-Jun Ahn,2 Takeshi Kamio,1 Hisato Fujisaka,1 and Kazuhisa Haeiwa1

1 Graduate School of Information Sciences, Hiroshima City University, 3-4-1 Ozukahigashi, Asaminami-ku,Hiroshima 731-3194, Japan

2 Graduate School of Engineering, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan

Correspondence should be addressed to Yuta Ida, y.ida@chiba-u.jp

Received 15 July 2011; Revised 22 February 2012; Accepted 12 March 2012

Academic Editor: Hanho Lee

Copyright © 2012 Yuta Ida et al. This is an open access article distributed under the Creative Commons Attribution License, whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Orthogonal frequency division multiplexing (OFDM) and multiple-input multiple-output (MIMO) are generally known as theeffective techniques for high data rate services. In MIMO/OFDM systems, the channel estimation (CE) is very important toobtain an accurate channel state information (CSI). However, since the orthogonal pilot-based CE requires the large numberof pilot symbols, the total transmission rate is degraded. To mitigate this problem, a high time resolution carrier interferometry(HTRCI) for MIMO/OFDM has been proposed. In wireless communication systems, if the maximum delay spread is longer thanthe guard interval (GI), the system performance is significantly degraded due to the intersymbol interference (ISI) and intercarrierinterference (ICI). However, the conventional HTRCI-MIMO/OFDM does not consider the case with the time-variant large delayspread longer than the GI. In this paper, we propose the ISI and ICI compensation methods for a HTRCI-MIMO/OFDM in thetime-variant large delay spread longer than the GI.

1. Introduction

Recently, the sophisticated terminal as a smart phone be-comes widely used and many multimedia services are pro-vided [1, 2]. High speed packet access (HSPA) using a wide-band code division multiplexing access (W-CDMA) is usedin the mobile communications and provides the data serviceswith the maximum transmission rate of about 14 Mbps [3].However, since the available frequency band is limited, aHSPA cannot improve the transmission rate more than now[4]. To solve this problem, orthogonal frequency divisionmultiplexing (OFDM) and multiple-input multiple-output(MIMO) are actively used [5–9]. OFDM is a multicarrierdigital modulation. The OFDM signal can be transmittedin parallel by using the many subcarriers that are mutuallyorthogonal. In MIMO systems, the signal of the severaltransmit antennas is transmitted in the same frequency band.Moreover, since each transmitted signal is sent over the

independent channel, the space diversity can be obtained inthe receiver. Therefore, a long term evolution (LTE) has beenstandardized as 3.9 G system using MIMO/OFDM systems[10, 11]. An LTE provides the maximum transmissionrate of about 50–100 Mbps. Moreover, an LTE Advancedwill support broadband data services with the maximumtransmission rate of about 100 M–1 Gbps as 4 G systems.

Since the received signal is changed due to the amplitudeand phase variations for a frequency selective fading, thechannel estimation (CE) is important to compensate thechannel variance. In the conventional MIMO/OFDM, theorthogonal pilot symbols-based CE is used to identify anaccurate channel state information (CSI) [7]. However, sincethe orthogonal pilot-based CE requires the large number ofpilot symbols and large transmission power, the transmissionrate is degraded. To mitigate these problems, a high time res-olution carrier interferometry (HTRCI) for MIMO/OFDMhas been proposed [12].

2 Journal of Electrical and Computer Engineering

I

I

I

I

I

I

Q

Q Q

Q

Q

Q

I

I

Q

QData Mapper

MuxPilot

generation

Scrambling

ScramblingPhaseoffsetting

...

...

...

...

......

......

......

...

IFFT

IFFT

S/P

Shifted pilotsignal

Shifted pilotsignal

+GI

+GI

D/A

D/A

D/A

D/A

Quadmod.

Quadmod.

U/C

U/C

(a) Transmitter

I

I

I I

I IQ

Q

Q

Q

Q

Q

I

I

Q

Q

I

I

Q

Q

...

... ......

......

......

...

...

...

...

...

......

......

......Data P/S

S/P

MLD-Pilotsignal

Descrambling

Descrambling

FFT

FFT

−GI

−GI

A/DA/D

A/DA/D

Quaddemod.

Quaddemod.

D/C

D/C

IFFT

IFFT

· · · · · · · · ·

· · ·· · · · · ·

· · ·Interferencecancellation

Interferencecancellation

FFT

FFT

FFT

IFFTHm,n(k)

Timewindows Subtraction GI of pilot

signal

τm,n,L > Tg

(b) Receiver

Figure 1: Proposed system.

In wireless communications, intersymbol interference(ISI) and intercarrier interference (ICI) are serious problemsto mitigate the system performance. To prevent these prob-lems, a guard interval (GI) is generally inserted. In general,GI is usually designed to be longer than the delay spreadof the channel. However, if the maximum delay spread islonger than the GI, the system performance is significantlydegraded due to the ISI and ICI. However, the conventionalHTRCI-MIMO/OFDM does not consider the case withthe time-variant large delay spread longer than the GI.In this paper, we propose the ISI and ICI compensationmethods for a HTRCI-MIMO/OFDM in the time-variantlarge delay spread longer than the GI. Until this time,several schemes have proposed the ISI and ICI compensationmethods due to the large delay spread channel. For example,[13] has proposed the ISI reduction method by extendingthe GI. However, since [13] has extended the GI length,the maximum throughput is degraded and the transmis-sion power is also increased. Reference [14] has proposedthe ISI and ICI compensation methods using the turboequalization. However, [14] has large complexity by theiterative processing for the turbo equalizer. Reference [15]has proposed the ISI and ICI compensation methods usingthe estimated channel coefficients and the CSI to reproducethe interference components. However, the packet lengthbecomes longer by using the training symbol. To mitigate theabove-mentioned problems, we propose the time domain ISIcompensation method with the replica signal based on theICI compensation for a HTRCI-MIMO/OFDM in this paper.This paper is organized as follows. In Section 2, we presentthe system model. Then, we describe the proposed systemin Section 3. In Section 4, we show the computer simulationresults. Finally, the conclusion is given in Section 5.

2. System Model

This section describes the system model, which employs thetime-division multiplexing (TDM) transmission for multipleusers. This system is illustrated in Figure 1.

2.1. Channel Model. We assume that a propagation channelconsists of L discrete paths with different time delays. Theimpulse response between the mth transmit and nth receiveantenna hm,n(τ, t) is represented as follows:

hm,n(τ, t) =L−1∑l=0

hm,n,l(t)δ(τ − τm,n,l

), (1)

where hm,n,l, τm,n,l are the complex channel gain and the timedelay of the lth propagation path, and

∑L−1l=0 E|h2

m,n,l| = 1,where E| · | denotes the ensemble average operation. Thechannel transfer function Hm,n( f , t) is the Fourier transformof hm,n(τ, t) and is given by

Hm,n(f , t

) = ∫∞0hm,n(τ, t) exp

(− j2π f τ)dτ

=L−1∑l=0

hm,n,l(t) exp(− j2π f τm,n,l

).

(2)

2.2. HTRCI-MIMO/OFDM. The transmission block dia-gram of the proposed system is shown in Figure 1(a). Firstly,the coded binary information data sequence is modulated,and Np pilot symbols are appended at the beginning of thesequence. The HTRCI-MIMO/OFDM transmitted signal for

Journal of Electrical and Computer Engineering 3

the mth transmit antenna can be expressed in its equivalentbaseband representation as follows:

sm(t) =Np+Nd−1∑

i=0

g(t − iT) ·⎧⎨⎩√

2SNc

Nc−1∑k=0

um(k, i)

· exp

[j2π(t − iT)k

Ts

]⎫⎬⎭,

(3)

where Nd and Np are the number of data and pilot sym-bols, Nc is the number of subcarriers, Ts is the effectivesymbol length, S is the average transmission power, andT is the OFDM symbol length, respectively. The frequencyseparation between adjacent orthogonal subcarriers is 1/Ts

and can be expressed by using the kth subcarrier of the ithmodulation symbol dm(k, i) with |dm(k, i)| = 1 for Np ≤ i ≤Np + Nd − 1 as follows:

um(k, i) = cPN(k) · dm(k, i), (4)

where cPN is a long pseudonoise (PN) sequence as a scram-bling code to reduce the peak-to-average power ratio(PAPR). GI is inserted in order to eliminate the ISI due toa multipath fading, and hence, we have

T = Ts + Tg , (5)

where Tg is the GI length. In communication systems, ε isgenerally considered as 4 or 5, where ε = Ts/Tg . In this paper,we assume ε = 4. In (3), the transmission pulse g(t) is givenby

g(t) ={

1 for− Tg ≤ t ≤ Ts

0 otherwise.(6)

For 0 ≤ i ≤ Np − 1, the transmitted pilot signal of the kthsubcarrier for the mth transmit antenna element is given by

dm(k, i) =

⎧⎪⎪⎨⎪⎪⎩ζ−1∑μ=0

exp

(− j2π(m + 2μ

)Tgk

Ts

)for i =

⌊m

ζ

⌋0 otherwise,

(7)

where ζ = �ε/2�, m = mod (m, ζ), and �x� stands forthe integer lower and closer to x, respectively. In this case,the HTRCI-MIMO/OFDM pilot signal can multiplex thesame impulse responses from the transmit antenna elementsin each receive antenna element in ζ times on the timedomain without overlapping to each other. For example, ifwe consider ε = 4 and 2 transmit antenna elements, weobtain

∑Nc−1k=0 d0(k, 0) = {1, 0, . . . , 1, 0} and

∑Nc−1k=0 d1(k, 0) =

{1, 0,−1, 0, . . . , 1, 0,−1, 0} as the pilot signal of the first andsecond transmit antenna elements from (7) as shown inFigure 2(a). In this case, since each pilot signal contains“0” components, we can identify the half of transmissionpower compared with the conventional MIMO/OFDM sys-tem using the orthogonal pilot. However, if τm,n,L > Tg ,the conventional HTRCI-MIMO/OFDM can not obtain an

accurate CSI, where τm,n,L is the maximum delay spreadfor the mth transmit and nth receive antenna. To solve thisproblem, we propose the new channel estimation using aHTRCI-MIMO/OFDM. Firstly, in the transmitter, we shiftthe channel impulse responses of (7) as follows:

dm(k, i) =

⎧⎪⎪⎨⎪⎪⎩ζ−1∑μ=0

exp

(− j2π(2m + μ

)Tgk

Ts

)for i =

⌊m

ζ

⌋0 otherwise.

(8)

In (8), the channel impulse responses are shifted as shown inFigure 2(a). This operation enables estimating the maximumdelay spread longer than the GI and to obtain an accurate CSIin the receiver.

The received structure is illustrated in Figure 1(b). Byapplying the FFT operation, the received signal rn(t) isresolved into Nc subcarriers. The received signal for the nthreceive antenna rn(t) in the equivalent baseband representa-tion can be expressed as follows:

rn(t) =M−1∑m=0

∫∞−∞

hm,n(τ, t)sm(t − τ)dτ + nn(t), (9)

where M is the number of transmit antennas and nn(t) isadditive white Gaussian noise (AWGN) with a single-sidedpower spectral density of N0 for the nth receive antenna,respectively. The kth subcarrier rn(k, i) is given by

rn(k, i) = 1Ts

∫ iT+Ts

iTrn(t) exp

[− j2π(t − iT)kTs

]dt

=√

2SNc

M−1∑m=0

Nc−1∑e=0

um(e, i)

· 1Ts

∫ Ts

0exp

[j2π · (e − k)t

Ts

]

·{∫∞

−∞hm,n(τ, t + iT)g(t − τ)

· exp(− j2πeτ

Ts

)dτ

}dt + nn(k, i),

(10)

where nn(k, i) is AWGN noise with zero mean and a varianceof 2N0/Ts. After abbreviating, (10) can be rewritten asfollows:

rn(k, i) ≈ 1Ts

√2SNc

M−1∑m=0

Nc−1∑e=0

um(e, i)

·∫ Ts

0exp

[j2π · (e − k)t

Ts

]

·{∫∞

−∞hm,n(τ, t + iT)g(t − τ)

· exp(− j2πeτ

Ts

)dτ

}dt + nn(k, i)

=√

2SNc

M−1∑m=0

Hm,n

(k

Ts, iT

)um(k, i) + nn(k, i).

(11)

4 Journal of Electrical and Computer Engineering

Pilotgeneration

Phaseoffsetting

IFFT

IFFT

Tx1

Tx2

0

Without shiftWith shift

Shift

ShiftTx1

Tx2

S/P

...

...

...

...

+GI

+GI

Tg 2Tg 3Tg 0 Tg 2Tg 3Tgt

t t

t

Ts/4 = Tg

(a) Transmitter

...

...

0

0

0

0

0

From Tx1 From Tx2From Tx2(GI part)

From Tx1From Tx2

From Tx2(GI part)

· · ·

· · · · · · · · · · · · · · ·· · · · · ·

· · · · · · · · · · · ·

· · · · · ·

−Tg Tg

Tg Tg

2Tg 3Tg 4Tgt

0−Tg Tg

Tg Tg

2Tg 3Tg 4Tgt

t t

t t

−GI IFFT

Without shift

Averaging

Averaging

Subtraction

Subtraction

FFT

FFT

CSI from Tx1

CSI from Tx2

Time windows[0, Tg + τm,n,L−1]

[Tg , 2Tg + τm,n,L−1]

Time windows[2Tg , 3Tg + τm,n,L−1]

[3Tg , 4Tg + τm,n,L−1]

With shift

(b) Receiver

Figure 2: The concept of a HTRCI-MIMO/OFDM to apply the maximum delay spread longer than the GI for 2 transmit antenna elementsand ε = 4.

After descrambling, the output signal rn(k, i) for the nthreceive antenna element is given by

rn(k, i) = c∗PN(k)

|cPN(k)|2 rn(k, i)

=√

2SNc

M−1∑m=0

Hm,n

(k

Ts, iT

)dm(k, i) + nn(k, i),

(12)

where (·)∗ is a complex conjugate and c∗PN(k)/|cPN(k)|2 isthe descrambling operation, respectively. Observing (11) and(12), the noise components are the same notation. In thispaper, the descrambling operation is to rotate the phaseof each subcarrier by using a PN code. Since ε = Ts/Tg ,a HTRCI-MIMO/OFDM can multiplex the same impulseresponses in ζ times on the time domain. After the pilot

signal separation, the pilot signal is converted to the timedomain signal rn(t) again as

rn(t) =Np−1∑i=0

√2PNc

Nc−1∑k=0

rn(k, i) exp

[j2π(t − iT)k

Ts

]

=Np−1∑i=0

√2PNc

M−1∑m=0

hm,n(τ, t + iT)Nc−1∑k=0

dm(k, i)

· exp

[j2π(t − iT)k

Ts

]+ nn(t)

=Np−1∑i=0

√2PNc

M−1∑m=0

L−1∑l=0

hm,n,l(t + iT)

· 1√ζ

⎧⎨⎩ζ−1∑μ=0

δ(τ − τm,n,l − τ(2m+μ)Tg

)⎫⎬⎭ + nn(t),

(13)

where P is the transmission pilot signal power and nn(t) isthe noise component, respectively. Here, if τm,n,L > Tg , since

Journal of Electrical and Computer Engineering 5

the channel impulse responses of the different time windowoverlap the desired channel impulse responses, the accurateCSI can not be obtained. Therefore, we process as follows. Atthe receiver, in Figure 2(b), the overlapped channel impulseresponses show the same amplitude for the transmitted pilotsignal without the shift in the different time window. In thiscase, we can not estimate the maximum delay spread. Onthe other hand, the overlapped channel impulse responsesshow the different amplitude for the transmitted pilot signalwith the shift in the different time window. Therefore, wecan estimate the maximum delay spread from the differentamplitude in the different time windows. Next, we eliminatethe channel impulse responses of the different time window.The channel impulse responses of the different time windowcan be eliminated by using the channel impulse responsesof the GI. These channel impulse responses do not containthe channel impulse responses of the different time window.This is because the pilot signal of the GI is the head ofpacket and it does not contain the channel impulse responsesof the different time window. Therefore, we can eliminatethe channel impulse responses of the different time window.From the above process, the frequency response of the kthsubcarrier between the mth transmit and nth receive antennaHm,n(k) for τm,n,L > Tg is obtained by

Hm,n(k)

=√

Ncζ

2P

M−1∑m=0

Nc−1∑e=0

1Ts

·∫ Ts

0

⎧⎨⎩L−1∑l=0

L−1∑l′=L′−1

hm,n,l(t + ρT

)

·∫∞−∞

⎧⎨⎩ζ−1∑μ=0

δ(τ − τm,n,l − τ(2m+μ)Tg

)

−δ(τ − τm,n,l′)⎫⎬⎭ · exp

(− j2πeτTs

)dτ

⎫⎬⎭dt+ ηm,n(k) for L′ ≤ Tg , ρ =

⌊m

ζ

⌋,

(14)

where ηm,n(k) is AWGN component with E[|ηm,n(k)|]2 =E[|nn(k, i)/ζ|]2 = σ2/ζ .

3. Proposed System

3.1. Rewritten Matrix Form. After the pilot signal separation,(13) for τm,n,L ≤ Tg can be rewritten in the matrix form asfollows:

Ri,n =M−1∑m=0

λi,m,nFDi,m + Ni,n, (15)

where λi,m,n is the Nc × Nc time-domain channel matrix forthe ith symbol between the mth transmit and nth receive

antenna, Ni,n is the Nc × 1 noise matrix, and F is the IFFToperation, respectively. However, (15) for τm,n,L > Tg isrewritten as follows:

Ri,n =M−1∑m=0

(λisi,i−1,m,nFDi−1,m + λici,i,m,nFDi,m

)+ Ni,n, (16)

where λisi,i−1,m,n, λici,i,m,n denote the ISI and ICI channelmatrices for the (i − 1)th and ith symbols between the mthtransmit and nth receive antenna, respectively. Observing(16), since the received signal Ri,n contains the ISI and ICIterms, these equalization processing are necessary.

3.2. ISI and ICI Equalization. In τm,n,L > Tg , since the firstdata symbol of Ri,n does not contain the ISI [16], (16) fori = 0 is obtained as

R0,n =M−1∑m=0

λici,0,m,nFD0,m + N0,n. (17)

However, the data symbols for i > 0 have the ISI. Here, theISI equalization is performed by using the previous detected

symbol Di−1,m,n and the estimated ISI channel matrix λisi,m,n.

The estimated ISI channel matrix λisi,m,n consists of theestimated channel impulse response. The estimated channel

impulse response hm,n,l′(t)δ(τ − τm,n,l′) is obtained by thechannel response Hm,n(k) after the IFFT operation, whereL′ ≤ l′ ≤ L − 1. Therefore, the ISI equalized signal Ri,n isgiven by

Ri,n = Ri,n −M−1∑m=0

λisi,m,nFDi−1,m

=M−1∑m=0

λici,i,m,nFDi,m + Ni,n,

(18)

where Ni,n is the noise term with the residual ISI. Afterthe FFT operation, by using maximum likelihood detection

(MLD), the detected signal Di = [Di,0, . . . , Di,m, . . . , Di,M−1]T

is obtained as follows:

Di = arg minD

N−1∑n=0

M−1∑m=0

∥∥∥F−1Ri,n − Hm,nDi,m

∥∥∥2, (19)

where (·)T is the transpose operation, N is the numberof receive antennas, Di,m is the constellation of the symbolreplica candidates as

∑M−1m=0

∑C−1c=0 Di,m,c, C is the modulation

level, and Hm,n is the matrix form of Hm,n(k), respectively.From (19), ISI is eliminated from the received signal. How-ever, the orthogonality is destroyed by the detected signal dueto the ISI compensation. If ICI is eliminated from (19), thedetected signal Di,m can be more accurately detected.

3.3. Replica Signal Insertion Based on ICI Equalization. Toeliminate the ICI, we consider the orthogonality recon-struction with inserting the detected signal after the ISI

6 Journal of Electrical and Computer Engineering

compensation. The ICI equalized signal Ri,n with insertingeliminated the part of signal using the previous detectedsymbol Di,m is given by

Ri,n = Ri,n +M−1∑m=0

λici,m,nFDi,m

=M−1∑m=0

λi,m,nFDi,m + Ni,n,

(20)

where λici,m,n is the estimated ICI channel matrix and Ni,n isthe noise term with the residual ISI and residual ICI, respec-tively. λici,m,n consists of the estimated channel impulse

responses hm,n,l′(t)δ(τ − τm,n,l′). After the FFT operation, the

detected signal Di = [Di,0, . . . , Di,m, . . . , Di,M−1]T

is obtainedas follows:

Di = arg minD

N−1∑n=0

M−1∑m=0

∥∥∥F−1Ri,n − Hm,nDi,m

∥∥∥2. (21)

Observing (19) and (21), since ICI is eliminated, Di,m is themore accurately detected signal compared with Di,m.

3.4. Complexity Comparison. Here, we compare the com-plexity of the conventional and proposed methods. Firstly,we show the complexity of [14]. The authors of [14] haveproposed the ISI and ICI compensations using the turboequalization. From Table 1 of [14], the complexity of [14]is given by

C[14] ={NNsMNc + 4NcNM2 + 3NcNM

+NNclog2Nc + 6N(Ns + L)MNc

}Nd

= NNcNd

{M(7Ns + 4M + 6L + 3) + log2Nc

},

(22)

where Ns is the number of sampling points for GI andeffective symbol. Next, we show the complexity of ourproposed method. Firstly, the complexity of (18) is obtainedby

Cisi = NNc(Nd − 1)CM + {MNc(Nd − 1)} logNc. (23)

For (23), the first term is the complexity of MLD and thesecond term is the complexity of IFFT. Next, the complexityof (20) is obtained by

Cici = NNcNdCM + MNNcNd logNc

= {NNc(Nd − 1) + NNc}CM

+ [{MNc(Nd − 1)} + MNc] logNc.

(24)

For (24), the first and second terms are the complexity ofMLD and IFFT of (23). Finally, the complexity of (21) is

CMLD = NNcNdCM = {NNc(Nd − 1) + NNc}CM. (25)

Therefore, the complexity of the proposed method is obtain-ed by

Cpro = Cisi + Cici + CMLD

= Nc

{N(3Nd − 1)CM + M(Nd − 1) logNc

}.

(26)

For example, when M = N = 2, Nc = 64, Nd = 20, Ns =80, L = 2, and C = 4, the complexities of [14] and theproposed method are 3000320 and 130560 from (22) and(26). Therefore, the proposed method is small comparedwith [14].

4. Computer Simulated Results

In this section, we show the performance of the proposedmethod. Figure 1 shows the simulation model of the pro-posed system. In this simulation, we assumed that 2 × 2 and4 × 4 MIMO systems. On the transmitter, the pilot signalis assigned for each transmitter using (8). In this case, theproposed system can multiplex the same impulse responsesfrom the transmit antenna elements in each receive antennaelement in ζ times on the time domain. These have beenfound to be efficient for the transmission of the OFDM signalover the frequency selective fading channel. After serial toparallel (S/P) converted, the coded bits are QPSK modulated,and then the pilot signal and data signal are multiplexed withthe scrambling using a PN code to reduce the PAPR. TheOFDM time signal is generated by the IFFT operation andis transmitted to the frequency-selective and time-variantradio channel after the cyclic extension has been inserted.The transmitted signal is subject to the broadband channelpropagation. In this simulation, we assume that OFDMsymbol period is 5 μs and guard interval is 1 μs for ε = 4,and L = 2, 3 path Rayleigh fadings. The maximum Dopplerfrequency is 10 Hz. In the receiver, guard interval is erasedfrom the received signal and the received signal is convertedS/P. The parallel sequences are passed to the FFT operatorand convert the signal back to the frequency domain. Afterthe descrambling and IFFT operation, each impulse responsefor all combination of the transmit and receive antennaelements can be estimated by extracting and averages ζ timesimpulse responses using the time windows with (14). Inτm,n,L > Tg , the HTRCI-MIMO/OFDM pilot signal containsthe overlapped channel impulse responses from the differenttime window. However, the pilot signal of the GI does notcontain the overlapped channel impulse responses. By usingthis signal, the channel impulse responses of the differenttime window are eliminated from the overlapped channelimpulse responses as shown in Figure 2(b). The frequencydomain data signal is detected and demodulated by usingthe MLD algorithm. Since the detected data signal containsthe ISI and ICI, these equalization processing are necessary.The ISI equalization is performed with the previous detectedsymbol and estimated ISI channel matrix as (18). From (18),ISI is eliminated. However, the orthogonality is destroyed bythe detected signal due to the ISI compensation. To recon-struct the orthogonality, the ICI equalization is performedby using the replica signal insertion as (20). Finally, the data

Journal of Electrical and Computer Engineering 7

0 5 10 15 20 25

Not ISI and ICI

10−5

10−4

10−3

10−2

10−1

100B

ER

−5

Eb/N0 per received antenna (dB)

Not compensation (2 path)Conventional method (2 path)Proposed method (2 path)Not compensation (3 path)Conventional method (3 path)Proposed method (3 path)

Figure 3: The BER of the conventional and proposed methods for2 × 2 MIMO system at Doppler frequency of 10 Hz.

Table 1: Simulation parameters.

Data modulation QPSK

Data detection MLD

Symbol duration 5 μs

Frame size Np = 1, 2, Nd = 20

FFT size 64

Number of carriers 64

Guard interval 16 sample times

Fading 2, 3 path Rayleigh fading

Doppler frequency 10 Hz

Antennas (M, N) = (2, 2), (4, 4)

signal is detected as (21). The packet consists of Np = 1, 2pilot symbols and Nd = 20 data symbols. Table 1 shows thesimulation parameters.

Figures 3 and 4 show the BER of the conventional andproposed methods for 2 × 2 and 4 × 4 MIMO systems atDoppler frequency of 10 Hz. The number of maximumdelay spread is 4 and 16 in 2 × 2 and 4 × 4 MIMOsystems, respectively. From the simulation results, the BERperformance for no ISI and ICI compensation is increasedabout 22 and 300 times compared with no ISI and ICI casein 2 × 2 and 4 × 4 MIMO systems, respectively. For theconventional method, the BER performance shows the errorfloor in high Eb/N0. This is because the residual ISI and ICIare remained. The proposed method shows approximatelythe same BER performance compared with no ISI and ICIcase. Therefore, the proposed method can eliminate the

−10 −5 0 5 10 15 20

Not ISI and ICI

Eb/N0 per received antenna (dB)

Not compensation (2 path)Conventional method (2 path)Proposed method (2 path)Not compensation (3 path)Conventional method (3 path)Proposed method (3 path)

10−5

10−6

10−7

10−4

10−3

10−2

10−1

100

BE

R

Figure 4: The BER of the conventional and proposed methods for4 × 4 MIMO system at Doppler frequency of 10 Hz.

ISI and ICI. Next, we compare the 2- and 3-path models.The 2-path model contains the channel impulse responsesof the different time window in the time domain HTRCI-MIMO/OFDM pilot signal. However, they do not overlap thedesired channel impulse responses. On the other hand, the 3-path model overlaps the desired channel impulse responses.Therefore, the channel impulse responses of the differenttime window are eliminated by using the channel impulseresponses of the GI. From the simulation results, the 2-pathmodel shows the better BER performance than that of the 3-path model in low Eb/N0. It means that CSI degrades due tothe eliminated processing of the overlapped channel impulseresponses in the 3-path model.

Figures 5 and 6 show the BER of the proposed methodfor 2 × 2 and 4 × 4 MIMO systems at Doppler frequency of10 Hz. The number of maximum delay spread is 4 and 16 in 2× 2 and 4 × 4 MIMO systems, respectively. For the proposedmethod without the noise, the noise is not added in thechannel impulse responses of the GI. From the simulationresults, the 2- and 3-path models without the noise show theapproximately same BER performance. Therefore, the 3-pathmodel with the noise degrades due to the noise of the GI.

Figures 7 and 8 show the BER versus the number ofmaximum delay spread for the conventional and proposedmethods with 2 × 2 and 4 × 4 MIMO systems at Dopplerfrequency of 10 Hz. Here, Eb/N0 per received antenna is 20and 15 dBs in 2 × 2 and 4 × 4 MIMO systems, respectively.In 2 × 2 MIMO system, the BER performances of no ISI andICI compensation and conventional method are increased

8 Journal of Electrical and Computer Engineering

0 5 10 15 20 25

2 path3 path

3 path (w/o)

Eb/N0 per received antenna (dB)

−510−5

10−4

10−3

10−2

10−1

100B

ER

Figure 5: The BER of the proposed method for 2× 2 MIMO systemat Doppler frequency of 10 Hz.

10−5

10−6

10−7

10−4

10−3

10−2

10−1

100

BE

R

0 5 10 15 20

2 path3 path

3 path (w/o)

Eb/N0 per received antenna (dB)

−5−10

Figure 6: The BER of the proposed method for 4× 4 MIMO systemat Doppler frequency of 10 Hz.

about 5 times. On the other hand, the BER performance ofthe proposed method is increased about 2 times. Therefore,the proposed method can suppress the ISI and ICI dueto the changing of the number of maximum delay spread.In 4 × 4 MIMO system, the BER performance of no ISIand ICI compensation and the conventional method areincreased about 170 and 80 times. On the other hand, theBER performance of the proposed method is increased about4 times and the proposed method can suppress the ISI andICI as 2 × 2 MIMO system. However, the BER performance

0.5 1 1.5 2 2.5 3 3.5 4 4.5

Not compensation (2 path)Conventional method (2 path)Proposed method (2 path)Not compensation (3 path)Conventional method (3 path)Proposed method (3 path)

Number of maximum delay spread

10−5

10−4

10−3

10−2

BE

R

Figure 7: The BER versus the number of maximum delay spread forthe conventional and proposed methods with 2 × 2 MIMO systemat Doppler frequency of 10 Hz.

0 2 4 6 8 10 12 14 16Number of maximum delay spread

10−5

10−6

10−7

10−4

10−3

BE

R

Not compensation (2 path)Conventional method (2 path)Proposed method (2 path)Not compensation (3 path)Conventional method (3 path)Proposed method (3 path)

Figure 8: The BER versus the number of maximum delay spread forthe conventional and proposed methods with 4 × 4 MIMO systemat Doppler frequency of 10 Hz.

Journal of Electrical and Computer Engineering 9

0

20

40

60

80

100

0 5 10 15 20

Th

rou

ghpu

t (M

bps)

Eb/N0 per received antenna (dB)

−5

Conventional method (2× 2)Proposed method (2× 2)

Conventional method (4× 4)Proposed method (4× 4)

Tg = 32 (2 × 2)

Tg = 32 (4 × 4)

Figure 9: The throughput of the conventional and proposedmethods for 2 × 2 and 4 × 4 MIMO systems at Doppler frequencyof 10 Hz.

of the proposed method with the 2-path model is increasedabout 36 times compared with 3-path model. This is becausethe channel impulse responses of the GI for the second timedomain HTRCI-MIMO/OFDM pilot symbol are overlappedfrom the first pilot symbol in 4 × 4 MIMO system.

Figure 9 shows the throughput performance of theconventional and proposed methods for 2 × 2 and 4 × 4MIMO systems at Doppler frequency of 10 Hz. The numberof maximum delay spread is 4 and 16 in 2 × 2 and 4 × 4MIMO systems, respectively. The throughput Ttp is given by

Ttp = Nd ·Nc · C · R ·M(Np + Nd

)T

·(

1− Pper

), (27)

where R is the coding rate and Pper is the packet error rate(PER), respectively. The extension of the GI length is thesimple method to prevent the problem of the maximumdelay spread [13]. However, the throughput performance isdegrade with this method. This is because the number ofcarriers Nc decreases for (27) when the OFDM symbol lengthT is the same as no ISI and ICI case. In this simulation,Nc decreases from 64 to 48, and the GI length Tg increasesfrom 16 to 32. On the other hand, the proposed methodcan maintain the number of carriers Nc. From (27), themaximum throughout for no ISI and ICI case is about48.8 and 93.1 Mbps in 2 × 2 and 4 × 4 MIMO systems,respectively. Therefore, the proposed method shows the bestthroughput performance and can achieve the maximumthroughput performance as the same no ISI and ICI case.

5. Conclusion

In this paper, we have focused on the large delay spread chan-nel and proposed the ISI and ICI compensation methods fora HTRCI-MIMO/OFDM. In the proposed method, we haveperformed the time domain ISI compensation method withthe replica signal based on the ICI compensation. From thesimulation results, the proposed method has achieved theapproximately same BER performance like the case with noISI and ICI. Moreover, the proposed method can suppressthe ISI and ICI due to the changing of the number ofmaximum delay spread. Finally, the proposed method hasshown the best throughput performance and can achieve thesame maximum throughput performance compared with noISI and ICI case.

References

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[2] H. Shoki and Y. Tanabe, “How fast will be required, how fastcan be realized in future wireless communications ?” IEICEB∗Pluse, no. 11, pp. 12–22, 2009.

[3] F. Adachi, H. Tomeba, and K. Takeda, “Introduction of freq-uency-domain signal processing to broadband single-carriertransmissions in a wireless channel,” IEICE Transactions onCommunications, vol. E92-B, no. 9, pp. 2789–2808, 2009.

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[8] I. Koffman and V. Roman, “Broadband wireless access sol-utions based on OFDM access in IEEE 802.16,” IEEE Commu-nications Magazine, vol. 40, no. 4, pp. 96–103, 2002.

[9] Y. Ogawa, T. Ohgane, and T. Nishimura, “MIMO technologiesfor ultra high-speed wireless transmission,” IEICE B∗Plus, no.11, pp. 32–38, 2009.

[10] A. Ghosh, R. Ratasuk, B. Mondal, N. Mangalvedhe, and T.Thomas, “LTE-advanced: next-generation wireless broadbandtechnology,” IEEE Wireless Communications, vol. 17, no. 3, pp.10–22, 2010.

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[13] N. Gejoh and Y. Karasawa, “OFDM transmission character-istic in multipath environment where the delay spreading

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[14] S. Suyama, H. Suzuki, and K. Fukawa, “A MIMO-OFDMreceiver employing the low-complexity turbo equalization inmultipath environments with delay difference greater than theguard interval,” IEICE Transactions on Communications, vol.E88-B, no. 1, pp. 39–46, 2005.

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