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ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, No 5, May 2013
1825
www.ijarcet.org

Abstract— In this paper we propose Weight Rotation
Technique for peak to- average power ratio (PAPR) reduction in
OFDM systems. It is based on selected mapping (SLM)
algorithm. The main drawback of the conventional SLM
technique is their high signal processing complexities due to the
use of multiple inverse fast Fourier transform (IFFT) operations
per OFDM block. In the proposed PAPR reduction is based on a
preset threshold value and the phase sequence is modified
accordingly. Simulation results show that this technique gives a
performance close to SLM technique with considerable
reduction in complexity.
Index Terms— PAPR reduction, Weight rotation technique,
SLM.
I. INTRODUCTION
Orthogonal Frequency Division Multiplexing (OFDM) has
been widely used for high data rate transmission applications.
The major advantages are its high spectral efficiency and
robustness to narrowband interference and multipath fading
channels [6]. One major drawback of OFDM is the high peak
to- average power ratio (PAPR) of the output signal. The
occurrence of high peak to average power causes the High
Power Amplifier (HPA) to work in the nonlinear region.
This introduces nonlinearities in the HPA output. The
resulting spectrum will have severe in-band distortion and
out-of-band radiation. The increase in BER results in
performance degradation. Hence there is a mandatory
requirement of going in for expensive High Power Amplifier
designs.
Several PAPR reduction techniques have been proposed in
the literature [1]. Some of the PAPR reduction schemes are
clipping [4], coding, SLM, tone injection, tone reservation
and partial transmit sequence [5]. The simplest of these is the
clipping technique, but it is found to cause both in-band and
Out-of-band distortion. Among them, SLM scheme is
relatively significant since it can obtain better PAPR by
modifying the OFDM signal without distortion [2]. Selecting
Manuscript received May, 2013.
Shakthivel, EEE, Bharath University,
S.P.Vijayaragavan, Assistant professor, EEE, Bharath University,
Chennai, India, Mobile No. 9003304814,
B.Karthik, Assistant professor, ECE, Bharath University, Chennai,
India, Mobile No.9842580740.
of proper phase sequences to achieve good PAPR
reduction is very important in SLM technique. The Phase
sequence can be random sequence or Hadamard sequence.
But it has a high signal processing complexity due to the use
of multiple inverse fast Fourier transform (IFFT) operations
per OFDM block. Similar to the SLM technique, the PTS
technique requires several IFFT operations per OFDM
symbol. To optimize both complexity and PAPR reduction
ability, we provide a novel PAPR reduction technique called
Weight Rotation Technique that operates based on setting a
threshold PAPR value and manipulation of phase sequence
accordingly.
II. WEIGHT ROTATION TECHNIQUE
SLM technique has a high complexity due to the use of
multiple inverse fast Fourier transform (IFFT) operations per
OFDM block. The main objective of the Weight Rotation
Technique is to reduce the number of IFFT operations
performed and to obtain a good PAPR performance.
A. Transmitter
The Block diagram of the transmitter is shown in Figure
1.The input data stream is modulated and converted into
time domain by taking IFFT operation. The PAPR
value is calculated and compared with the predefined
threshold value. If it is less than the threshold the OFDM
symbol is transmitted, else the phase sequence is rotated to the
left once and the process is repeated again till the threshold
condition is satisfied. The side information contains details
about the number of times the phase sequence was rotated.
WEIGHT ROTATION TECHNIQUE FOR
PAPR REDUCTION IN OFDM
1
S.P.Vijayaragavan, Assistant Professor, EEE Department, Bharath University, Chennai, India.
2
R.Sakthivel, PG Student, EEE Department, Bharath University, Chennai, India.
3
B.Karthik, Assistant Professor, ECE Department, Bharath University, Chennai, India.
ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, No 5, May 2013
www.ijarcet.org
1826
Figure 1. Transmitter Block Diagram
B. Phase Sequence
The phase sequence B is initially selected using the
formula, B= ejѲ ,where Ѳ ϵ { -П to + П}.The angle Ѳ
is chosen randomly. . If 64 point IFFT is used there are 64
symbols in each block. Therefore 64 random angles are
chosen to generate the initial phase sequence.
C. Algorithm
The algorithm is as follows:
1) The sequence of data bits are mapped to constellation
points MQAM or BPSK to produce sequence symbols X0, X1,
X2…
2) These symbol sequences are divided into blocks of
length N. N is the number of subcarriers.
3) Each block X=[X0, X1, X2….XN-1] is multiplied
(Point wise multiplication) by phase sequence.
B = [B (0), B (1) …B (N-1)].
4) Transform the OFDM data block obtained into time
domain by taking IFFT.
5) Calculate the PAPR and If PAPR < = Threshold,
transmit the modified OFDM symbol else rotate B once to left
and repeat from step 3.
D. Receiver
The block diagram of the Receiver is shown in Figure 2.
Based on the side information transmitted the corresponding
phase sequence used at transmitting end is generated by
rotating the initial phase sequence in the opposite
direction. The Received OFDM symbol is multiplied by the
rotated phase sequence. Then FFT operation is performed
and demodulated to get the transmitted bits.
Figure 2. Receiver Block Diagram
III. RESULTS AND DISCUSSION
OFDM with 64 subcarriers and BPSK modulations is used
for analysis. The CCDF plot obtained by setting different
levels of threshold value is shown in Figure 3.
Figure 3.CCDF Plot
Thus by decreasing the threshold value the PAPR value
obtained can be reduced. The CCDF plot in Figure 4 and
BER plot in Figure 5 compares the performance of
Weight Rotation Technique with SLM technique.
ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, No 5, May 2013
1827
www.ijarcet.org
Figure 4. PAPR Comparison of SLM and Weight
Rotation Technique.
Figure 5. BER Comparison of SLM and Weight Rotation
Technique
PAPR Value in dB
Without
any PAPR
reduction
technique
Weight Rotation Technique
Threshold PAPR in dB SLM
Th=7 Th=6 Th=5 Th=4
Mean 6.7492 6.0757 5.5426 4.8012 4.7324 4.7299
Variance 1.1034 0.3070 0.1090 0.0436 0.0588 0.0920
Max 9.3368 6.9978 5.9989 5.2553 5.2553 5.3226
No. of IFFT
operations
(count)
- 96 348 3110 6400 6400
(U)
Table 1. Comparison between Weight Rotation Technique and SLM
Thus the performance of Weight Rotation technique is
close to that of SLM technique. Table 1 shows the comparison
of PAPR value obtained and the number of IFFT operations
required in Weight Rotation technique with those of SLM
technique.
From Table 1 it can be inferred that the number of IFFT
operations performed in Weight Rotation Technique is less
when compared to that of SLM technique. By increasing the
Threshold PAPR value the number of IFFT operations can be
decreased.
IV. COMPLEXITY COMPARISON
The minimum number of multiplications MIFFT and
additions AIFFT required for an IFFT operation is
Given by
If SLM requires U IFFT operations then the number of
multiplications MSLM and additions ASLM are
Weight Rotation Technique requires fewer IFFT operations
when compared to the SLM technique as indicated in Table 1
as count. The number of multiplications and additions are
given by
When 64 point IFFT is taken SLM requires 819200
multiplications and 2457600 additions .On the other hand
Weight Rotation technique with threshold value of 6 dB
(count=348) requires 66816 multiplications and 133632
additions. Thus there is a considerable reduction in number of
arithmetic operations required. Thus Weight Rotation
Technique is less complex.
ISSN: 2278 – 1323
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
Volume 2, No 5, May 2013
www.ijarcet.org
1828
V. CONCLUSION
Thus the Weight Rotation Technique provides PAPR
reduction close to that of SLM technique. It involves lesser
number of arithmetic operations when compared to SLM.
Hence it is less complex with good performance.
REFERENCES
[1] S. H. Han and J. H. Lee, “An overview of peak- to-average power ratio
reduction techniques for multicarrier transmission,” IEEE Wireless
Commn., vol. 12, no. 2, pp. 56–65, Apr. 2005.
[2] R. W. Bäuml, R. F. H. Fischer, and J. B. Huber, “Reducing the
peak-to-average power ratio of multicarrier modulation by selected
mapping,” Electron. Lett., vol. 32, no. 22, pp. 2056–57, Oct.
1996.
[3] P. Van Eetvelt, G. Wade, and M. Tomlinson, "Peak to Average
Power Reduction for OFDM Schemes by Selective Scrambling," Elect.
Letter, vol. 32, no. 21, pp. 1963-1964, Oct. 1996.
[4] X. Li and L. J. Cimini, Jr., "Effect of Clipping and filtering on the
Performance of OFDM,” Elect. Letter, vol. 2, no. 5, pp. 131-133, May
1998.
[5] G. Lu, P. Wu, and C. Carlemalm-Logothetis, “Peak-to-average power
ratio reduction in OFDM based on transformation of partial
transmit sequences,” E l e c t r o n . Lett, vol. 42, pp. 105–106,
2006.
[6] Book: OFDM for Wireless multimedia communication, Richard Van
Nee & Ramjee Prasad.
[7] Book: Wireless Communications Principles and Practice, Theodore S.
Rappaport.
Mr. R.Shakthivel is doing M.Tech(Power Electronics) in Department of
Electrical and Electronics Engg at Bharath University, Chennai., Tamil
Nadu, India.
Mr.S.P.Vijayaragavan is an Assistant professor in the department of
Electrical and Electronics Engineering, Bharath University, Chennai, India.
He received his Master of Engineering in Applied Electronics in 2012. He is
doing his research work in Communication Networks at Bharath University,
Chennai, India.
Mr.B.Karthik is an Assistant professor in the department of Electronics
and Communication Engineering, Bharath University, Chennai, India.. He
received his Master of Engineering in Applied Electronics in 2011. He is
doing his research work in Image Processing at Bharath University, Chennai,
India. His area of interests includes Image Processing, Network Security
System Techniques.

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1825 1828

  • 1. ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 2, No 5, May 2013 1825 www.ijarcet.org  Abstract— In this paper we propose Weight Rotation Technique for peak to- average power ratio (PAPR) reduction in OFDM systems. It is based on selected mapping (SLM) algorithm. The main drawback of the conventional SLM technique is their high signal processing complexities due to the use of multiple inverse fast Fourier transform (IFFT) operations per OFDM block. In the proposed PAPR reduction is based on a preset threshold value and the phase sequence is modified accordingly. Simulation results show that this technique gives a performance close to SLM technique with considerable reduction in complexity. Index Terms— PAPR reduction, Weight rotation technique, SLM. I. INTRODUCTION Orthogonal Frequency Division Multiplexing (OFDM) has been widely used for high data rate transmission applications. The major advantages are its high spectral efficiency and robustness to narrowband interference and multipath fading channels [6]. One major drawback of OFDM is the high peak to- average power ratio (PAPR) of the output signal. The occurrence of high peak to average power causes the High Power Amplifier (HPA) to work in the nonlinear region. This introduces nonlinearities in the HPA output. The resulting spectrum will have severe in-band distortion and out-of-band radiation. The increase in BER results in performance degradation. Hence there is a mandatory requirement of going in for expensive High Power Amplifier designs. Several PAPR reduction techniques have been proposed in the literature [1]. Some of the PAPR reduction schemes are clipping [4], coding, SLM, tone injection, tone reservation and partial transmit sequence [5]. The simplest of these is the clipping technique, but it is found to cause both in-band and Out-of-band distortion. Among them, SLM scheme is relatively significant since it can obtain better PAPR by modifying the OFDM signal without distortion [2]. Selecting Manuscript received May, 2013. Shakthivel, EEE, Bharath University, S.P.Vijayaragavan, Assistant professor, EEE, Bharath University, Chennai, India, Mobile No. 9003304814, B.Karthik, Assistant professor, ECE, Bharath University, Chennai, India, Mobile No.9842580740. of proper phase sequences to achieve good PAPR reduction is very important in SLM technique. The Phase sequence can be random sequence or Hadamard sequence. But it has a high signal processing complexity due to the use of multiple inverse fast Fourier transform (IFFT) operations per OFDM block. Similar to the SLM technique, the PTS technique requires several IFFT operations per OFDM symbol. To optimize both complexity and PAPR reduction ability, we provide a novel PAPR reduction technique called Weight Rotation Technique that operates based on setting a threshold PAPR value and manipulation of phase sequence accordingly. II. WEIGHT ROTATION TECHNIQUE SLM technique has a high complexity due to the use of multiple inverse fast Fourier transform (IFFT) operations per OFDM block. The main objective of the Weight Rotation Technique is to reduce the number of IFFT operations performed and to obtain a good PAPR performance. A. Transmitter The Block diagram of the transmitter is shown in Figure 1.The input data stream is modulated and converted into time domain by taking IFFT operation. The PAPR value is calculated and compared with the predefined threshold value. If it is less than the threshold the OFDM symbol is transmitted, else the phase sequence is rotated to the left once and the process is repeated again till the threshold condition is satisfied. The side information contains details about the number of times the phase sequence was rotated. WEIGHT ROTATION TECHNIQUE FOR PAPR REDUCTION IN OFDM 1 S.P.Vijayaragavan, Assistant Professor, EEE Department, Bharath University, Chennai, India. 2 R.Sakthivel, PG Student, EEE Department, Bharath University, Chennai, India. 3 B.Karthik, Assistant Professor, ECE Department, Bharath University, Chennai, India.
  • 2. ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 2, No 5, May 2013 www.ijarcet.org 1826 Figure 1. Transmitter Block Diagram B. Phase Sequence The phase sequence B is initially selected using the formula, B= ejѲ ,where Ѳ ϵ { -П to + П}.The angle Ѳ is chosen randomly. . If 64 point IFFT is used there are 64 symbols in each block. Therefore 64 random angles are chosen to generate the initial phase sequence. C. Algorithm The algorithm is as follows: 1) The sequence of data bits are mapped to constellation points MQAM or BPSK to produce sequence symbols X0, X1, X2… 2) These symbol sequences are divided into blocks of length N. N is the number of subcarriers. 3) Each block X=[X0, X1, X2….XN-1] is multiplied (Point wise multiplication) by phase sequence. B = [B (0), B (1) …B (N-1)]. 4) Transform the OFDM data block obtained into time domain by taking IFFT. 5) Calculate the PAPR and If PAPR < = Threshold, transmit the modified OFDM symbol else rotate B once to left and repeat from step 3. D. Receiver The block diagram of the Receiver is shown in Figure 2. Based on the side information transmitted the corresponding phase sequence used at transmitting end is generated by rotating the initial phase sequence in the opposite direction. The Received OFDM symbol is multiplied by the rotated phase sequence. Then FFT operation is performed and demodulated to get the transmitted bits. Figure 2. Receiver Block Diagram III. RESULTS AND DISCUSSION OFDM with 64 subcarriers and BPSK modulations is used for analysis. The CCDF plot obtained by setting different levels of threshold value is shown in Figure 3. Figure 3.CCDF Plot Thus by decreasing the threshold value the PAPR value obtained can be reduced. The CCDF plot in Figure 4 and BER plot in Figure 5 compares the performance of Weight Rotation Technique with SLM technique.
  • 3. ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 2, No 5, May 2013 1827 www.ijarcet.org Figure 4. PAPR Comparison of SLM and Weight Rotation Technique. Figure 5. BER Comparison of SLM and Weight Rotation Technique PAPR Value in dB Without any PAPR reduction technique Weight Rotation Technique Threshold PAPR in dB SLM Th=7 Th=6 Th=5 Th=4 Mean 6.7492 6.0757 5.5426 4.8012 4.7324 4.7299 Variance 1.1034 0.3070 0.1090 0.0436 0.0588 0.0920 Max 9.3368 6.9978 5.9989 5.2553 5.2553 5.3226 No. of IFFT operations (count) - 96 348 3110 6400 6400 (U) Table 1. Comparison between Weight Rotation Technique and SLM Thus the performance of Weight Rotation technique is close to that of SLM technique. Table 1 shows the comparison of PAPR value obtained and the number of IFFT operations required in Weight Rotation technique with those of SLM technique. From Table 1 it can be inferred that the number of IFFT operations performed in Weight Rotation Technique is less when compared to that of SLM technique. By increasing the Threshold PAPR value the number of IFFT operations can be decreased. IV. COMPLEXITY COMPARISON The minimum number of multiplications MIFFT and additions AIFFT required for an IFFT operation is Given by If SLM requires U IFFT operations then the number of multiplications MSLM and additions ASLM are Weight Rotation Technique requires fewer IFFT operations when compared to the SLM technique as indicated in Table 1 as count. The number of multiplications and additions are given by When 64 point IFFT is taken SLM requires 819200 multiplications and 2457600 additions .On the other hand Weight Rotation technique with threshold value of 6 dB (count=348) requires 66816 multiplications and 133632 additions. Thus there is a considerable reduction in number of arithmetic operations required. Thus Weight Rotation Technique is less complex.
  • 4. ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 2, No 5, May 2013 www.ijarcet.org 1828 V. CONCLUSION Thus the Weight Rotation Technique provides PAPR reduction close to that of SLM technique. It involves lesser number of arithmetic operations when compared to SLM. Hence it is less complex with good performance. REFERENCES [1] S. H. Han and J. H. Lee, “An overview of peak- to-average power ratio reduction techniques for multicarrier transmission,” IEEE Wireless Commn., vol. 12, no. 2, pp. 56–65, Apr. 2005. [2] R. W. Bäuml, R. F. H. Fischer, and J. B. Huber, “Reducing the peak-to-average power ratio of multicarrier modulation by selected mapping,” Electron. Lett., vol. 32, no. 22, pp. 2056–57, Oct. 1996. [3] P. Van Eetvelt, G. Wade, and M. Tomlinson, "Peak to Average Power Reduction for OFDM Schemes by Selective Scrambling," Elect. Letter, vol. 32, no. 21, pp. 1963-1964, Oct. 1996. [4] X. Li and L. J. Cimini, Jr., "Effect of Clipping and filtering on the Performance of OFDM,” Elect. Letter, vol. 2, no. 5, pp. 131-133, May 1998. [5] G. Lu, P. Wu, and C. Carlemalm-Logothetis, “Peak-to-average power ratio reduction in OFDM based on transformation of partial transmit sequences,” E l e c t r o n . Lett, vol. 42, pp. 105–106, 2006. [6] Book: OFDM for Wireless multimedia communication, Richard Van Nee & Ramjee Prasad. [7] Book: Wireless Communications Principles and Practice, Theodore S. Rappaport. Mr. R.Shakthivel is doing M.Tech(Power Electronics) in Department of Electrical and Electronics Engg at Bharath University, Chennai., Tamil Nadu, India. Mr.S.P.Vijayaragavan is an Assistant professor in the department of Electrical and Electronics Engineering, Bharath University, Chennai, India. He received his Master of Engineering in Applied Electronics in 2012. He is doing his research work in Communication Networks at Bharath University, Chennai, India. Mr.B.Karthik is an Assistant professor in the department of Electronics and Communication Engineering, Bharath University, Chennai, India.. He received his Master of Engineering in Applied Electronics in 2011. He is doing his research work in Image Processing at Bharath University, Chennai, India. His area of interests includes Image Processing, Network Security System Techniques.