reduction of papr performance in alamouti coded...

International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)

Volume 3 Issue 7, July 2014

ISSN: 2278 – 1323 All Rights Reserved © 2014 IJARCET 2341

Reduction of PAPR Performance in Alamouti Coded

MIMO-OFDM System using Selected Mapping

Techniques with BPSK Modulation

Tincy Mary Mathew

ME Scholar, Electronics and Telecommunication

Department

Shri Shankaracharya Technical Campus

Bhilai, Chhattisgarh, India.

Ekant Sharma

Assistant Professor, Electronics and

Telecommunication Department

Shri Shankaracharya Technical Campus

Bhilai, Chhattisgarh, India.

.

Abstract—Orthogonal frequency division Multiplexing

(OFDM) is one of the most popular multicarrier or

multiplexing modulation techniques in high speed

wireless communication. The main principle of OFDM

system is to transmit multiple numbers of signals

simultaneously over a single transmission path. OFDM

convert high data rate stream in to smaller data rate

stream. Due to this high data rate and ability to combat

frequency selective fading, OFDM has a strong

candidate for 4G wireless networks. OFDM combined

with multiple-input multiple-output (MIMO) to increase

system capacity over the time variant frequency-selective

channels and the diversity gain. The main idea of MIMO

system is to use multiple antennas at both the

transmitter and receiver end in order to improve

communication performance. MIMO-OFDM system has

a major drawback that might exhibit high peak-to-

average power ratio (PAPR). In this paper, we present

Selected Mapping scheme (SLM) based on alamouti

coded MIMO OFDM system with reduced PAPR using

BPSK modulation schemes for N=128, 256 and 512.

Simulation results show that MIMO OFDM system

using SLM in alamouti code has low PAPR when

compared to conventional MIMO OFDM system.

MATLAB simulations show that our proposed SLM

modification significantly improves the PAPR reduction.

Index Terms— Alamoutic code, MIMO, OFDM, PAPR,

SLM.

I. INTRODUCTION

Orthogonal Frequency Division multiplexing is also

known as Multicarrier modulation (MCM) techniques or

Multiplexing technique because of its increasing demand of

high speed data rates, robustness to channel fading, flexibility and easy equalization. MCM will transmit signals

through multiple carriers where these carriers (subcarriers)

will have different frequencies and they are orthogonal to

each other. As an effective technique OFDM have been

widely adopted by many wireless communication systems,

such as Digital Audio Broadcasting (DAB), Digital Video

Broadcasting (DVB) and Wireless Metropolitan Area

Networks (WMAN) for IEEE 802.16a standard and Wireless Local Area Networks (WLAN), for IEEE 802.11a

standard.

In high-speed wireless communication, an arrangement of

using multiple antennas at transmitter and receiver of

OFDM system is called as (MIMO-OFDM) multiple input

multiple output OFDM. OFDM combined with MIMO

technology using alamouti code of space time block coding

(STBC) for mobile communication systems due to its ability

to achieve high data rate robust transmission. Therefore,

MIMO-OFDM systems achieve coding gain and diversity

gain by space-time coding (STBC). MIMO-OFDM System takes advantages of multipath interference effect to increase

user and data capacity. Like single-input-single-output

OFDM (SISO OFDM), one of the major drawbacks of

MIMO-OFDM is the high peak to average power ratio

(PAPR) of the signal transmitted to different antenna. In

order to reduced the high PAPR in alamouti MIMO-OFDM

system we would have to apply the PAPR reduction scheme

[2-6].

However, there is one major problem associated with

OFDM signals that is its inherent drawback of high peak-to-

average power ratio (PAPR). High PAPR causes signal distortions such as the in-band distortion and out-of-band

radiation and induces the degradation of bit error rate

performance due to the nonlinearity effects [1]. There are

several reduction technique that have been proposed to

reduce the PAPR problem such as Clipping And

Filtering[2], Partial Transmit Sequences (PTS)[3], Selected

Mapping Technique[4], tone reservation (TR) and

tone injection (TI)[5], Zadoff-Chu matrix Transform

(ZCT)[6].




In this paper, we proposed to use the property of space-

time block coded (STBC) coding technique (Alamouti) in

MIMO-OFDM system, with reduction techniques by which

better PAPR performance is achieved by the most widely

used methods are selective mapping (SLM) and the

modulation techniques used is BPSK for different number of

subcarriers. And we proved that by using the Alamouti

scheme, the conjugate symbols transmitted on two antennas

has same PAPR property .Section II explains MIMO

system. Section III explains Alamouti MIMO OFDM

system and their PAPR. The proposed system model for PAPR reduction of SLM Alamouti MIMO OFDM system is

explained in section IV. Section V presents the simulation

result and section VI describes the conclusion.

II. MIMO SYSTEM

MIMO stands for Multiple Input Multiple Output system

that means MIMO system has two antennas at both the

transmitter and receiver side. Multiple transmitting and

receiving antennas will achieve antenna diversity without

reducing the spectral efficiency. MIMO system has

disadvantages like complexity, power consumption and size

of the mobile device.

A. System Model

MIMO system consists of basically three components

transmitter (TX), channel (H) and the receiver (RX). Let us

consider 𝑛𝑡 be the no. of transmitter antenna, 𝑛𝑟 be the no.

of receiving antennas and ℎ𝑖 ,𝑗 represent the complex value

of the channel for transmitter antenna i and receiver antenna

j respectively. Let 𝑥𝑖 = {𝑥1 ,𝑥2 ,…… .𝑥𝑛𝑡 } be the complex

signals transmitted via 𝑛𝑡 antennas. Then the receiving

antenna can be expressed as:

𝑦𝑗 = ℎ𝑖 ,𝑗 𝑥𝑖 + 𝑛𝑖𝑛𝑡𝑖=1 (1)

𝑛𝑖 = noise term

Fig.1 MIMO System with 𝑛𝑡 x 𝑛𝑟 antennas.

The received signal of Eq (1) can be written as:

𝑦 = 𝐻𝑥 + 𝑛 (2)

Where 𝐻 =

ℎ1,1 … ℎ1,𝑛𝑡

⋮ ⋱ ⋮ℎ𝑛𝑡 ,1 ⋯ ℎ𝑛𝑡 ,𝑛𝑟

(3)

y is the received vector of size 𝑁𝑟 ∗ 1, 𝑥 is the transmitted

vector of size 𝑁𝑡 ∗ 1, H is channel matrix of size 𝑁𝑟 ∗ 𝑁𝑡 and n is the noise vector.

B. Alamouti Space-Time Block Code (STBC)

The first space time block code (STBC) is the alamouti

code that provides full diversity to data rate for the two

transmit antennas. Fig.2 represents the block diagram of

alamouti code.

Fig.2 Block diagram of Alamouti code

Firstly the input data source X is passed through the

modulator using a digital modulation schemes in this case

BPSK modulation is used. After the process of modulation it

is passed through the STBC encoder which generate two

modulated symbols 𝑥1 and 𝑥2 in each precoding operation.

𝑋 = 𝑥1 −𝑥2

∗

𝑥2 𝑥1∗ (4)

The first row represents the first transmission period and

the second row represents the second transmission period.

During the first time slot, the symbols 𝑥1 and 𝑥2 are

transmitted simultaneously from 1st and 2nd antenna

respectively. In the second time slot, the symbol −𝑥2∗ and

𝑥1∗ are transmitted from 1st and 2nd antenna respectively.

III. ALAMOUTI MIMO OFDM SYSTEM AND THEIR

PAPR

Fig.3 shows the general block diagram of a STBC

Alamouti MIMO-OFDM system. Let us consider the MIMO-OFDM systems with M transmit antennas that use N

subcarriers. The complex vector of size N can be expressed

as 𝑋 = [𝑋1 ,𝑋2 ,…… . ,𝑋𝑁]. These modulated baseband signal

are passed through serial to parallel converter such that each

modulated signal has different subcarrier and form a set of 𝑓𝑛 , 𝑛 = 0,1,… . ,𝑁 − 1 . The N subcarriers are orthogonal

to each other i.e. 𝑓𝑛 = 𝑛∆𝑓 where ∆f =1

𝑁𝑇 and T is the

symbol period. The complex vector, X is the passed through

space time encoder which generate two sequences.




Fig.3 Block diagram of STBC Alamouti MIMO-OFDM system

From the 1st antenna 𝑋1 is generated

𝑋1 = [𝑥1 ,−𝑥2∗,𝑥3 ,−𝑥4

∗,………… , 𝑥𝑁−1 ,−𝑥𝑁∗] (5)

And for 2nd antenna 𝑋2 is generated

𝑋2 = [𝑥2 ,𝑥1∗,𝑥4 ,𝑥3

∗,………… , 𝑥𝑁 ,𝑥𝑁−1∗] (6)

Eq (5) and (6) means that in the 1st time slot signal 𝑥1 and

𝑥2 are transmitted from the 1st and 2nd antennas respectively,

in 2nd time slot signal −𝑥2∗ and 𝑥1

∗ are transmitted from the

two antennas, in the 3rd time slot signal 𝑥3 and 𝑥4 are

transmitted from the two antennas and in the 4th time slot

signal −𝑥4∗ and 𝑥3

∗ are transmitted respectively from the

two antennas and so on. Both of these sequences are then

passed through each IFFT block for antenna 1 and antenna 2

respectively. After the process of IFFT it is then passed

through cyclic prefix where the last part of an MIMO

OFDM symbol is inserted into the front of an MIMO

OFDM symbol. The resulting baseband STBC MIMO-

OFDM signal for antenna i with N subcarriers can be written as:-

𝑥𝑖(𝑘) =1

𝑁 𝑋𝑖(𝑘)𝑒 𝑗2𝜋

𝑛

𝑁𝑘 𝑁

𝑛=1 (7)

Where 𝑘 = 1,2,… .𝑁, 𝑖 = 1,2 and 𝑗 = −1 .PAPR of the STBC MIMO-OFDM signal for antenna i can be written as:

𝑃𝐴𝑃𝑅 =max 1≤n≤N | 𝑥𝑖 𝑘 |²

𝐸[ 𝑥𝑖(𝑘) 2] (8)

E[.] denotes expectation value. Complementary

cumulative distribution function (CCDF), define the

probability that the PAPR of an OFDM symbol exceeds the

given threshold 𝑃𝐴𝑃𝑅0 can be written as:

𝐶𝐶𝐷𝐹 = 𝑃𝑟(𝑃𝐴𝑃𝑅 > 𝑃𝐴𝑃𝑅0) (9)

For MIMO OFDM, the CCDF of PAPR can be written as:

𝐶𝐶𝐷𝐹 = 1 − (1 − 𝑒−𝑃𝐴𝑃𝑅0 )𝑀𝑁 (10)

IV. SLM ALAMOUTI MIMO OFDM SYSTEM

Selected Mapping (SLM) technique is one of the most

promising reduction techniques to reduce Peak to Average

Power Ratio (PAPR) in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO

OFDM). The main principle of SLM technique is to

generate a number of MIMO OFDM symbols as candidates

and then select the one with the lowest PAPR for actual

transmission that have the same information the main idea

of SLM technique is based on the phase rotation. Fig.4

shows the block diagram of SLM STBC Alamouti MIMO-

OFDM system.

The input sequence X are mapped with BPSK modulation

and passed through serial to parallel converter which

generate complex vector of size N is 𝑋 = [𝑋1 ,𝑋2 , . . ,𝑋𝑁]. The modulated data are then passed through the space time

encoder (2x2) which generates two sequences 𝑋1 =[𝑋1 ,−𝑋2

∗,… .𝑋𝑁−1 ,−𝑋𝑁∗] for antenna 1 and 𝑋2 =

[𝑋2 ,𝑋1∗,… .𝑋𝑁 ,𝑋𝑁−1

∗] for antenna 2. Both of these

sequence is then multiplied by the U different phase

sequence vector 𝑃𝑚𝑢 = [𝑃1

𝑢 ,𝑃2𝑢 ,… . .𝑃𝑁

𝑢 ] where m=1,2

and u=1,2,....,U. The output of phase sequence vector is

written as:

𝑋𝑚𝑢 = 𝑋𝑚𝑃𝑚

𝑢 (11)

Fig.4 Block diagram of SLM STBC Alamouti MIMO-OFDM system.




For antenna 1 and 2 𝑋1𝑢 and 𝑋2

𝑢 can be written as:

𝑋1𝑢 = [𝑋1𝑃1

𝑢 ,−𝑋2∗𝑃2

𝑢∗. . . . ,𝑋𝑁−1𝑃𝑁−1𝑢 ,−𝑋𝑁

∗𝑃𝑁𝑢∗ ] (12)

𝑋2𝑢 = [𝑋2𝑃2

𝑢 ,𝑋1∗𝑃1

𝑢∗. . . . ,𝑋𝑁𝑃𝑁𝑢 ,𝑋𝑁−1

∗𝑃𝑁−1𝑢∗] (13)

These frequency domain signals 𝑋𝑚𝑢 are transformed into

time domain signals 𝑥𝑚𝑢 via the IFFT operation.

𝑥𝑚𝑢 = 𝐼𝐹𝐹𝑇 (𝑋𝑚

𝑢 ) (14)

𝑥𝑚𝑢 =

1

𝑁 𝑋𝑚

𝑢 (𝑘)𝑒 𝑗2𝜋𝑚𝑘

𝑁𝑁𝑘=1 (15)

The PAPR of an SLM MIMO OFDM signal of Eq(15)

can be written as:

𝑃𝐴𝑃𝑅 =max |𝑥𝑚

𝑢 |²

𝐸[ 𝑥𝑚𝑢 2]

(16)

The optimal set with the minimum PAPR of the two

signals is chosen as.

𝑢 = arg min1≤𝑢≤𝑈(max𝑚=1,2 max1≤𝑛≤𝑁 | 𝑥𝑚𝑢 |) (17)

The U phase rotation sequences 𝑃𝑚𝑢 should be transmitted

to the receiver as the SI with log2 𝑈 bits.

V. SIMULATION RESULT

In this section, we present some simulation results

showing the PAPR performance of the proposed SLM

Alamouti MIMO OFDM system. To show the effect of our

proposed SLM Alamouti MIMO OFDM system we use two

transmitting antenna M= 2 using BPSK modulations. We

also compared our results with Alamouti MIMO OFDM

system with and without adding cyclic prefix for N = 128,

256 and 512

Fig.5. CCDF Vs PAPR for Alamouti MIMO OFDM System with System

subcarriers N=128 using BPSK Modulation.


subcarriers N=256 using BPSK Modulation.

Fig.5 shows the CCDF comparisons of PAPR of Alamouti

MIMO OFDM systems with N = 128 using BPSK

modulation. At clip rate of 10−3, the PAPR is to 10 dB for

Original MIMO OFDM systems and 10 dB for MIMO

OFDM CP.



modulation. At clip rate of 10−3, the PAPR is to 10.6 dB for Original MIMO OFDM systems and 10.6 dB for MIMO

OFDM CP.



modulation. At clip rate of 10−3, the PAPR is to 11 dB for Original MIMO OFDM systems and 11 dB for MIMO

OFDM CP.

\


subcarriers N=512 using BPSK Modulation




Fig.8. CCDF Vs PAPR for SLM Alamouti MIMO OFDM System with

System subcarriers N=128 using BPSK Modulation.

Fig.8 shows the CCDF comparisons of PAPR of SLM

Alamouti MIMO OFDM systems with N = 128 using BPSK

modulation. At clip rate of 10−3 , the PAPR is to 9.7 dB for Alamouti MIMO OFDM systems, 9.7 dB for Alamouti

MIMO OFDM CP and 8.5 dB for SLM Alamouti MIMO OFDM.



modulation. At clip rate of 10−3, the PAPR is to 9.9 dB for Alamouti MIMO OFDM systems, 9.9 dB for Alamouti

MIMO OFDM CP and 8.8 dB for SLM Alamouti MIMO

OFDM.

Fig.9 CCDF Vs PAPR for SLM Alamouti MIMO OFDM System with

System subcarriers N=256 using BPSK Modulation

Fig.10 CCDF Vs PAPR for SLM Alamouti MIMO OFDM System with

System subcarriers N=512 using BPSK Modulation



modulation. At clip rate of 10−3, the PAPR is to 10.6 dB for Alamouti MIMO OFDM systems, 10.6 dB for Alamouti

MIMO OFDM CP and 9 dB for SLM Alamouti MIMO

OFDM.

TABLE I PAPR ANALYSIS

Systems

PAPR in dB

(BPSK)

Number of

subcarriers (N) 128 256 512

Original MIMO

OFDM

10 10.6 11

MIMO OFDM CP 10 a. 10.6 11

Alamouti MIMO

OFDM

9.7 9.9 10.6

Alamouti MIMO

OFDM CP

9.7 9.9 10.6

Alamouti SLM

MIMO OFDM

8.5 8.8 9




VI. CONCLUSIONS

In this paper, we present an analysis of the PAPR for the

SLM Alamouti MIMO OFDM system especially space time

block encoder alamouti schemes has been used. In the

proposed method we multiply the space time encoder value

with the phase rotation vector. Therefore it reduce the PAPR

more than the conventional SLM OFDM and have higher data rate And compare this SLM Alamouti MIMO OFDM

system with the original Alamouti MIMO OFDM system.

Simulation results have shown that the SLM Alamouti

MIMO OFDM system has much lower PAPR than original

MIMO OFDM system. Thus the proposed system does not

require any complex optimization, side information and

power increase.

REFERENCES

[1] J. Jinwei and G. Ren.,”A Modified SLM Scheme with Low

Complexity for Reducing the PAPR of OFDM Systems Without Side

Information” IEEE Trans. on Wireless communication, pp. 1-6,

October 2012.

[2] S.KYusof and N.Fisal,” Correlative Coding with Clipping and

Filtering Technique in OFDM Systems”, IEEE Trans. on Information,

Communication and Signal processing, vol.3, pp. 1456 – 1459,

December 2003

[3] S. H. Han and J.H.Lee,“PAPR Reduction of OFDM Signals using a

Reduced Complexity PTS Technique”, IEEE Trans. on Signal

Processing Letters, vol.11, no.11 pp. 887-890, November 2004.

[4] C.L.Wang and Y. Ouyang, “A Low-Complexity selected mapping

schemes for Peak-to- Average Power Ratio Reduction Technique for

OFDM systems”, IEEE Trans. on Signal Processing, vol. 53 , no.12,

pp. 4652 – 4660, December 2005.

[5] D. Guel and J. Palicot, “FFT/IFFT Pair based Digital Filtering for the

Transformation of Adding Signal PAPR Reduction Techniques in

Tone Reservation Techniques”, Fifth International Conference on

Wireless and Mobile communications, pp. 200-204, August 2009.

[6] I. Baig and V.Jeoti,” PAPR Reduction in OFDM Systems: Zadoff-

Chu Matrix Transform Based Pre/Post-Coding Techniques”, IEEE

Trans. on Communication Systems and Networks, pp. 373-377, July

2010.

[7] S. H. Han and J. H. Lee, “An Overview of Peak –to- Average Power

Ratio Reduction Techniques for Multicarrier Transmission”, IEEE

Transaction on Wireless Communication, vol. 12, no.2, pp. 56-65,

April 2005.

[8] W. Yi and G. Linfeng,” An Investigation of Peak-to-Average Power

Reduction in MIMO- OFDM Systems”, Blekinge Institute of

Technology, October 2009.

[9] L.J. Cimini, and N.R. Sollenberger”, Peak-to-Average Power Ratio

Reduction of a Signal Using Partial Transmit Sequences”, IEEE

Trans. on Communication Letters, vol. 4, no. 3, pp. 86–88, Mar. 2000.

[10] R.W. Bäuml, R. F. H. Fischer, and J.B. Huber, “Reducing the Peak-

to Average Power Ratio of Multicarrier Modulation by Selective

Mapping”, IEEE Trans. on Electronics Letters., vol. 32, no. 22, pp.

2056–2057, October 1996.

[11] L. Sahraoui, D. Messadeg and N. Doghmane,” Analyses and

Performance of Techniques PAPR reduction for STBC MIMO-

OFDM System in (4G) Wireless Communication”, International

Journal of Wireless & Mobile Networks, vol. 5, no. 5, pp. 35-48,

October 2013.

[12] S. Singh, J. Malhotra and M. Singh,” A Novel SLM based PAPR

reduction Technique in OFDM-MIMO System”, International Journal

of Computers & Technology, vol. 2, no. 3, pp. 41-46, June, 2012.

[13] J. Gao, J. Wang and Z. Xie.” A Novel Concurrent PAPR Reduction

Algorithm for STBC MIMO-OFDM Systems”, International Journal

of Science Information and Systems Sciences, vol. 4, no 3, pp. 449-

461, December 2007.

[14] V. B. Malode1 and Dr. B. P. Patil, “PAPR Reduction Using Modified

Selective Mapping Technique”, International Journal of Advanced

Networking and Applications, vol.02, no.2, pp. 626-630, August

2010.

[15] Y. L. Lee, Y. H. You, W. G. Jeon, J. H. Paik and H. K. Song,” Peak-

to-Average Power Ratio in MIMO-OFDM Systems Using Selective

Mapping”, IEEE Trans. on Communications Letters, vol. 7, no. 12,

pp.575-577, December 2003.

[16] T. Jiang, C. Ni, and L. Guan,” A Novel Phase Offset SLM Scheme for

PAPR Reduction in Alamouti MIMO-OFDM Systems Without Side

Information”, IEEE Trans. on Signal Processing Letters, vol. 20, no.

4, pp. 383-386, April 2013.

[17] S.D Santumon and B.R. Sujatha,” Space-Time Block Coding (STBC)

for Wireless Networks”, International Journal of Distributed and

Parallel Systems, vol.3, no.4, pp. 183-195, July 2012.

[18] P. Choudhury and A. Deshmukh.,” Comparison and analysis of PAPR

reduction techniques in OFDM”, IOSR Journal of Electronics and

Communication Engineering, vol. 4, no.5, pp 01-06, January 2013.

[19] L. Zheng and N.C David, “Diversity and Multiplexing: A

Fundamental Trade-off in Multiple-Antenna Channels”, IEEE Trans.

on Information Theory, vol. 49, no. 5, pp 1073-1096, MAY 2003.

[20] T.C. Hsueh, P.Y. Lin and J.S. Lin,” PAPR reduction techniques with

cross SLM schemes FOR MIMO-OFDM systems”, IEEE Trans. on

Signal Processing Communication and Computing, pp.197-202,

August 2012.

http://ieeexplore.ieee.org/search/searchresult.jsp?searchWithin=p_Authors:.QT.Seung%20Hee%20Han.QT.&searchWithin=p_Author_Ids:37278482000&newsearch=true

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