Abstract Orthogonal Frequency Division Multiplexing (OFDM) technique has been proposed a

Madhvi Jangalwa

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Research Article 
International Journal of Current Engineering and Technology    
ISSN 2277 - 4106  
 © 2013 INPRESSCO. All Rights Reserved. 
Available at http://inpressco.com/category/ijcet  
Performance Analysis of MIMO-OFDM System using MMSE Receiver 
 
Madhvi Jangalwa
#*
 
   
#Institute of Engineering and Technology, Devi Ahilya University Indore, India 
   
Accepted 10 May 2013, Available online 21 June 2013, Vol.5, No.3 (June 2013 
 
 
Abstract 
  
Orthogonal Frequency Division Multiplexing (OFDM) technique has been proposed as a standard for the next 
generation wireless communication system.  Next generation wireless communication technologies require multimedia 
service such as internet services, audio, video and mainly high data rate with high mobility. OFDM fulfills these 
requirements. It provides high data rates and high spectral efficiency. Also high data rate can be achieved by the 
Multiple Input and Multiple Output (MIMO) technique. MIMO technique increases the diversity gain. This improves the 
Bit Error Rate (BER) performance of the system. These two technique bring together resulting MIMO-OFDM system to 
get the benefit of both the techniques. In this paper performance of MIMO-OFDM system is analyzed by using Minimum 
Mean Square Error (MMSE) technique. Simulation results show that improved BER is obtained with MIMO system than 
the without MIMO system. In addition BER performance is also investigated for different number of transmitting and 
receiving antennas and different modulation techniques. 
 
Keywords: OFDM, MIMO, BER, MIMO-OFDM, MMSE.  
 
 
1. Introduction 
 
1
 Orthogonal Frequency Division Multiplexing (OFDM) 
technique has been proposed as a standard for the next 
generation wireless communication system. The next 
generation wireless communications systems demand 
higher data rates transmission in order to meet the high 
quality services [R. V. Nee et al.]. Also there is need to 
provide high data rate in a mobile environment for new 
services like multimedia, internet, audio and video. OFDM 
fulfills these requirements. It provides high data rates and 
high spectral efficiency. OFDM is multicarrier 
transmission scheme [S. Shrikanthet al. and Y. 
Rahmatallah et al.]. In which these multicarrier are 
orthogonal and overlapping.  By using overlapping carrier 
OFDM can save fifty percent of bandwidth. Therefore in 
OFDM spectrum is efficiently utilized. For wireless 
communication OFDM provides greater immunity against 
multipath fading and impulse noise [S. Hara et al.]. Also 
high data rate can be achieved by the Multiple Input and 
Multiple Output (MIMO) technique. MIMO technique can 
be used for diversity combining or spatial multiplexing. In 
spatial multiplexing multiple data streams transmit on 
multiple antennas in parallel leading to a substantial 
increase in capacity [T. Hwang et al.]. Therefore MIMO 
technique promises a significant increase in capacity. 
MIMO system has the ability to exploit multipath 
propagation rather than combat  
                                                          
*Corresponding author: Madhvi Jangalwa 
Most of MIMO techniques are developed for flat fading 
channels. However, multipath will cause frequency 
selectivity of broadband wireless channels. Therefore, 
MIMO-OFDM, which has originally been proposed to 
exploit OFDM to mitigate Inter Symbol Interference (ISI) 
in MIMO systems, turns out to be a very promising choice 
for future high-data-rate transmission over broadband 
wireless channels. These two technique bring together 
resulting MIMO-OFDM system to get the benefit of both 
the techniques [S. Catreux et al.]. 
 In this paper, performance of MIMO-OFDM system is 
analyzed by using Minimum Mean Square Error (MMSE) 
technique. Simulation results show that improvement in 
BER is obtained with the MIMO technique than the 
without MIMO technique. The comparative study of BER 
over different modulation techniques show that minimum 
BER can be achieved by lower order modulation 
technique having lower coding rate.  
 The rest of the paper is organized as follows: Section 2 
describes of the transmitter and receiver model for MIMO-
OFDM system. Simulation results are shown in section 3 
and paper is concluded in section 4. 
 
2. System Model 
 
MIMO-OFDM is considered for the system model. This 
combines MIMO technique and OFDM technique. 
MIMO-OFDM transmitter and receiver are described in 
next section. 
Madhvi Jangalwa                                                                       International Journal of Current Engineering and Technology, Vol.3, No.2 (June 2013) 
 
718 
 
2.1 MIMO-OFDM Transmitter  
 
MIMO-OFDM transmitter consists of OFDM and MIMO 
system. Orthogonal Frequency Division Multiplexing 
(OFDM) technique has been proposed as a standard for the 
next generation wireless communication system as it 
offers high data rate. Further MIMO technique is used for 
high data rate. There are different MIMO techniques 
which make possible to transmit data through multiple 
antenna and receive data through multiple antenna. For 
MIMO technique Space Time Block code is used. MIMO-
OFDM transmitter is shown in Fig-1.  
 
 
 
Fig.1 MIMO-OFDM transmitter 
 
Randomly generated data are encoded by forward error 
correcting code, in which Reed Solomon and 
convolutional coding are used. This coded data are 
interleaved and modulated. The multicarrier modulated 
signal is obtained after IFFT processing. The OFDM 
modulated signal is given by [T. Hwang, et al.] 
 
 ( )   ∑   
 
    
                                              (1) 
 
Where Ts, ∆f and M are the symbol duration, the subcarrier 
space, and number of subcarriers of the OFDM signals, 
respectively. These multicarrier modulated signals are 
encoded by STBC encoding technique.  Finally, these 
signals are transmitted through multiple transmitting 
antennas. 
 
2.2 MIMO-OFDM Receiver 
 
Receiver model of MIMO-OFDM with NT transmit 
antennas and NR receive antennas is shown in Fig-2. The 
transmitted symbol or data stream {xn}  converts into NT 
substreams {xk
(m)
} by Space–time processing and 
transmitted through different antennas. The signal at 
receiving antennas is given by [T. Hwang, et al.] 
 
  
   ∑   
(  )  
     
    
                                              (2) 
 
for i = 1, . . . , NR,  where   
(  )
 denotes the frequency 
response at the kth subchannel corresponding to the mth 
transmit and the ith receive antenna and   
  is the channel 
noise at the kth subchannel of the ith receive antenna. 
Received signal is decoded by STBC decoder. For STBC 
decoder MMSE is used. The received signal can be 
expressed as 
r= Hs + η                                                                          (3)   
 
For perfect channel state information (CSI) estimated  
 
re=G(Hs +η)                                                                     (4) 
 
Where G = (H
H
H + σ
2
I)
-1
H
H
.  σ
2 
is the variance of the 
noise. This output is passes through the every block of the 
receiver model. Finally after channel decoding we get the 
data. 
 
 
 
Fig.2 MIMO-OFDM Receiver 
 
3. Simulation Results 
 
Physical layer of fixed WiMAX is simulated using OFDM 
with MIMO. Each block of MIMO-OFDM transmitter and 
receiver is individually coded in MATLAB. The 
simulation parameters are given in Table 1. For FEC,  RS 
and convolution channel coding is used. In channel 
coding, overall coding rate is taken as ½, and ¾.  
 
Table 1 OFDM parameters of fixed WiMAX 
 
S.No Parameters Values 
1 FFT size 256 
2 Number of used data subcarrier 192 
3 Number of pilot subcarrier 8 
4 Number of null/guardband subcarrier 56 
5 Cyclic prefix 1/4 
6 Coding rate ½, ¾ 
 
 
 
Fig.3 BER versus SNR at NT = 2, NR = 2 
0 5 10 15 20 25 30
10
-2
10
-1
10
0
SNR (dB)
B
it
 E
rr
o
r 
R
a
te
 Bit Error Rate vs. SNR
 
 
 QPSK, r = 3/4
16QAM, r = 1/2
16QAM, r = 3/4
Madhvi Jangalwa                                                                       International Journal of Current Engineering and Technology, Vol.3, No.2 (June 2013) 
 
719 
 
 
 
Fig.4 BER versus SNR for QPSK, overall rate r =¾ and 
NT = 2, NR = 2. 
 
 
 
Fig.5 BER versus SNR for QPSK, overall rate  r = ½ and 
NT = 2, NR = 2. 
 
 
 
Fig.6 BER versus SNR  for 64QAM, overall rate r = 2/3 
and NT = 2, NR = 2 
 
 
 
Fig.7 BER versus SNR for 64QAM, overall rate r = ¾ and 
NT = 2, NR = 2 
 
 
 
Fig.8 BER versus SNR at 16QAM, overall rate r = ½ and 
NT = 2, NR = 2 
 
In Fig-3 comparison is shown among the different 
modulation techniques. Among all modulation techniques 
for QPSK bit error rate is low. 
 BER of MIMO-OFDM system with MIMO cannel and 
without MIMO channel is shown in Fig-4 and 5 for QPSK 
modulation at NT = NR = 2. Without MIMO channel bit 
error rate is more as compared to with MIMO channel.      
With cyclic prefix CP = 1/4 and 1/8 comparison for 
64QAM is shown in Fig.6 and 7. If cyclic prefix fraction 
value is more bit error rate is less because of less ISI. 
From Fig-8 it is observed that bit error rate depends on 
channel coding technique. Without channel coding 
technique bit error rate is more as compared to with 
channel coding.    
 
Conclusions 
 
In this paper MIMO-OFDM with MMSE receiver is 
investigated. Simulation results show that improved bit 
error rate is obtained with MIMO system than the without 
0 5 10 15 20 25 30
10
-2
10
-1
10
0
SNR (dB)
B
it
 E
rr
o
r 
R
a
te
 Bit Error Rate vs. SNR
 
 
with MIMO
without MIMO
-10 -5 0 5 10 15 20 25 30
10
-4
10
-3
10
-2
10
-1
10
0
SNR (dB)
B
it
 E
rr
o
r 
R
a
te
 Bit Error Rate vs. SNR
 
 
with MIMO
without MIMO
0 5 10 15 20 25 30
10
-2
10
-1
10
0
SNR (dB)
B
it
 E
rr
o
r 
R
a
te
 Bit Error Rate vs. SNR
 
 
CP = 1/4
CP = 1/8
0 5 10 15 20 25 30
10
-2
10
-1
10
0
SNR (dB)
B
it
 E
rr
o
r 
R
a
te
 Bit Error Rate vs. SNR
 
 
CP =1/4
CP =1/8
5 10 15 20 25 30
10
-2
10
-1
10
0
SNR (dB)
B
it
 E
rr
o
r 
R
a
te
 Bit Error Rate vs. SNR
 
 
with coding
without coding
Madhvi Jangalwa                                                                       International Journal of Current Engineering and Technology, Vol.3, No.2 (June 2013) 
 
720 
 
MIMO system by exploiting diversity gain. In addition bit 
error rate performance is also investigated for different 
modulation techniques. Among all modulation techniques 
for QPSK modulation bit error rate is low. For higher 
order modulation and higher coding rate bit error rate is 
also higher. On comparing the performance among the 
different cyclic prefix, it is shown that minimum bit error 
rate can be achieved with the higher fraction valued cyclic 
prefix. Bit error rate for MIMO-OFDM system with 
channel coding is less as compared to without channel 
coding. 
 
References 
 
R. V. Nee and Ramjeeprasad (2000), OFDM Wireless 
Multimedia Communications, Artech House Publishers. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
S. Shrikanth, P. A. M. Pandiyan and X. Farnando (2012), 
Orthogonal Frequency Division Multiple Access in WiMAX 
and LTE: A Comparison, IEEE Communication Magazine, pp. 
153-161.  
Y. Rahmatallah, S. Mohan (2013) Peak to Average Power Ratio 
Reduction in OFDM Systems: A Survey and Taxonomy, IEEE 
Communications Surveys & Tutorials, vol. 15, no.4, pp. 1567–
1592, Fourth Quarter. 
S. Hara and R. Prasad. (Dec. 1997.), Overview of Multicarrier 
CDMA, IEEE Communications Magazine, vol. 35, pp. 126–
133 
T. Hwang, C. Yang, G. Wu, S. Li and G. Y. Li. (May 2009), 
OFDM and Its Wireless Applications: A Survey, IEEE 
Transactions on Vehicular Technology, vol. 58, no.4, pp. 
1673–1694. 
S. Catreux, V. Erceg, D. Gesbert, and R. Heath (2002), Adaptive 
Modulation and MIMO Coding for Broadband Wireless Data 
Networks, IEEE Communications Magazine, pp.108-115 
 


Performance Analysis of MIMO-OFDM System using MMSE Receiver

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Performance Analysis of MIMO-OFDM System using MMSE Receiver

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