INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)

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1 INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET) International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 ISSN (Print) ISSN (Online) Volume 5, Issue 5, May (2014), pp IAEME: Journal Impact Factor (2014): (Calculated by GISI) IJECET I A E M E PERFORMANCE COMPARISION OF SLM WITH NCT FOR PAPR REDUCTION IN OFDM SYSTEM V. SRIDHAR 1, ARUNKUMAR. R 2, S. DINESH REDDY 3, CH. SREEDHAR 4 1 Assistant Professor, 2 Assistant Professor, 3 B.Tech student-ece, 4 Assistant professor 1 ECE Department, Vidya Jyothi Institute of Engineering &Technology, Aziz Nagar, AP, INDIA. 2 CSE Department, Vidya Jyothi Institute of Engineering &Technology, Aziz Nagar, AP, INDIA. 3 B.Tech Student-ECE, Vidya Jyothi Institute of Engineering &Technology, Aziz Nagar, AP, INDIA 4 ECE Department, Global Institute of Technology, Moinabad, AP, INDIA ABSTRACT High peak-to-average power ratio (PAPR) of the transmitted signal is one of the limitations to employing orthogonal frequency division multiplexing (OFDM) system. In this paper, we propose a new nonlinear companding algorithm that transforms the OFDM signals into the desirable statistics form defined by a linear piecewise function. By introducing the variable slopes and an inflexion point in the target probability density function, more flexibility in the companding form and an effective trade-off between the PAPR and bit error rate performances can be achieved. In this paper one more algorithm proposes a SLM technique using hadamard transform to reduce the PAPR of OFDM systems. The two methods effectively reduce the PAPR by compressing the peak signal and expanding the small signal. Simulation results show the performance analyses of both techniques are more efficient than the conventional OFDM systems. Keywords: Nonlinear Companding Transform (NCT), Orthogonal Frequency Division Multiplexing (OFDM), Peak-To-Average Power Ratio (PAPR). Selected Mapping (SLM), Phase Shift Keying (PSK) I. INTRODUCTION In the recent trends, orthogonal frequency division multiplexing (OFDM) has been widely applied in modern wireless communications due to its high spectral efficiency and low susceptibility to the multipath propagation [1]. However, a major drawback of OFDM-based transmission systems is its high instantaneous peak-to-average power ratio (PAPR), which leads to undesired in-band distortion and out-of-band radiation if the linear range of the high power amplifier (HPA) is not 48

2 sufficient [2], [3]. In an OFDM system with subcarriers, the complex baseband representation of OFDM signal is given by x t 1 N X. e, 0 t T Where J 1 and the vector denotes the frequency-domain OFDM symbols and is the symbol duration. Based on the central limit theorem, when is large, can be approximated as a complex Gaussian process; thus, it is possible that the maximum amplitude of OFDM signal may well exceed its average amplitude. The OFDM has many advantage such as high bandwidth efficiency, robustness to the selective fading problem, use of small guard interval, and its ability to combat the ISI problem [4]. The main disadvantages of the OFDM systems is that it exhibits a high peak to average power ratio, namely the peak value of some of the transmitted signals could be much larger than the typical values. PAPR makes the amplifiers to work in non-linear regions. This will cause inter modulation between the A New SLM Technique for PAPR Reduction in OFDM Systems 222 different sub carriers and introduce additional interference to the system. Additional interference leads to an increase in Bit Error Rate (BER).Large PAPR leads to in band distortion and spectral spreading. There are number of techniques to deal with the problem of PAPR. Some of them are amplitude clipping, filtering, coding, partial transmit sequence and selected mapping (SLM) [5], [6]. The selected mapping method (SLM) provides good performance for PAPR reduction [7], and this requirement usually results in high computational complexity. Several techniques have been proposed based on low-complexity selected mapping schemes for Peak-to-Average Power Ratio reduction in OFDM Systems[8],[9].There are techniques based on combining the SLM with various transforms for reducing the PAPR of OFDM systems. SLM requires the transmission of several side information bits for each data block, which results in some data rate loss. To overcome this issue, various methods have been developed [10], among which, nonlinear companding transform (NCT) is an efficient solution in reducing the PAPR of OFDM signal. The concept of NCT was first introduced in [11], which used the -law companding and could significantly outperform the traditional clipping. Earlier NCT methods have primarily focused on designing the nonlinearity of the transfer curve [12]. Later, the work of [13] first indicated the importance of exploiting the statistical characteristics of the OFDM signal. Up to now, several such NCT methods have been proposed, e.g. the exponential companding (EC) in [14], the uniform companding (UC) in [15], the piecewise companding (PC) in [16], and the trapezium or trapezoidal companding (TC) in [7] and [8], etc. The analytical expressions regarding the achievable reduction in PAPR, signal attenuation factor, and the selection criteria of transform parameters are derived and verified through MATLAB simulations. II. SYSTEM DESIGN MODEL A. Peak To Average Power Ratio(PAPR) Generally, an OFDM signal is the sum of independent data symbols modulated by phase-shift keying (PSK) or quadrature amplitude modulation (QAM). In discrete-time domain, since the Nyquist rate samples might not represent the peaks of the continuous-time signal, it is preferable to approximate the true PAPR on an oversampled signal. As we discussed some of the advantages of OFDM which makes it a strong contender for OFDM systems. But OFDM has a disadvantage also which is PAPR (peak to average power ratio). PAPR is the ratio between the maximum power and the average power of the complex pass band signal, 49

3 PAPR P P 10 log max f t s E s Where, is the peak output power, is the average output power, E. denotes the expected value, represents the transmitted OFDM signals which are obtained by taking IFFT operation on modulated input symbols. can be expressed as s 1 N S W The PAPR puts a stringent requirement on the power amplifier and reduces the efficiency in the sense that a higher input back off factor is needed before the peaks in the signal experience significant distortion due to power amplifier nonlinearity. B. PAPR Problem An OFDM signal consists of a number of independently modulated Sub carriers, which can give a large peak-to-average power (PAP) ratio when added up coherently. When N signals are added with the same phase, they produce a peak power that is N times the average power. High PAPR of the transmitted signals results in Clipping noise (Limited quantization levels, rounding and truncation during IDFT and FFT computation), non linear distortions of power amplifiers, BER performance degradation, energy spilling into adjacent channels, inter-modulation effects on the sub carriers, warping of the signal constellation in each sub channel, increased complexity in the analog to digital and digital to analog converter. Let the data block of length N be represented by a vector X=[ X0, X1, X2,.., XN-1]T. Duration of any symbol X k in the set X is T and represents one of the subcarriers {fn,n=0,1,..,n- 1} set. As the N sub carriers chosen to transmit the signal are orthogonal to each other, so we can have f n = n f, where n f =1/NT and NT is the duration of the OFDM data block X. The PAPR of the transmitted signal is defined as PAPR NT max x t 1 x t dt 0 t NT PAPR is defined as a ratio of peak instantaneous power to the average power. Reducing the max x(t) is the principle goal of PAPR technique. C. SLM technique with Hadamard Transform The block diagram of the transmitter is shown in the Fig 1.The sequence of data bits are mapped to constellation points by PSK to produce the sequence symbols X0, X1, X2,.. Then these symbols are divided into block of length N,where N is the number of sub carriers.then each block X=[ X0, X1, X2,.. XN-1] is multiplied by Hadamard matrix and each output block is multiplied by M different phase sequences. Note that the parameter _i which depends on the constellation at the transmitter does not affect the PAPR.For the first branch b1 is the unit vector.the element of phase sequence of the other branch are (i.e. b2, b3,. bm).after computing the IDFT of the each branch there are M different OFDM signals with the same information. The transmitter selects the branch with minimum PAPR SLM takes advantage of the fact that the PAPR of an OFDM signal is very sensitive to phase shifts in the frequency-domain data. PAPR reduction is achieved by multiplying independent phase sequences to the original data and determining the PAPR of each phase sequence/data combination. The combination with the lowest PAPR is transmitted. 50

4 Figure 1: A block diagram of the SLM technique with Hadamard Transform D. Non Linear Companding Transform: We propose a new NCT algorithm which transforms the Gaussian distributed signal into a desirable distribution form defined by a linear piecewise function with an inflexion point. Compared to the previous methods, this algorithm can significantly reduce the impact of companding distortion on the BER performance by choosing proper transform parameters. In addition, it also allows more flexibility and freedom in the companding form to satisfy various design requirements. The basic idea of the proposed algorithm is to transform the statistics of the amplitude into the desirable PDF defined by a piecewise function, which consists of two linear functions with an inflexion point. Assume the inflexion point and cutoff point of the PDF of are and, respectively. Thus, the desirable target PDF can be expressed as where two slopes k 1 > 0 and k 2 < 0 are variable parameters that determine the desired companding form i.e. the ultimate PAPR, while controlling the average output power in this transform. We can see that the transform can achieve more reduction in the PAPR with k 2 or c increasing. Especially, it is noteworthy that the EC and TC are two special cases of the proposed algorithm. In practice, since actual signal processed at the transmitter and receiver are the quantized signal with finite set of values, the functions can be numerically pre-computed and performed via the look-up tables. III. SIMULATION RESULTS To evaluate the overall system performance of the proposed algorithm, computer simulations were performed based on an OFDM system with subcarriers. In the results which follow, random OFDM frames modulated by QPSK or 16QAM were generated to obtain the CCDFs, which have been computed with an oversampling ratio to offer a better PAPR estimation. In order to investigate the performance degradation and spectral re-growth, we also consider passing the companded signal through AWGN channel. 51

5 Figure 2: theoretical result of papr and G (vs) k2 of proposed algorithm In this section, the theoretical performances of the proposed algorithms are characterized with two main evaluation criteria: the achievable reduction in PAPR and the impact of companding distortion on the BER performance at the receiver. Figure 3: papr reduction using new technique for N=256 SLM technique is applied to the OFDM systems. This technique is adopted for all kind of OFDM systems. Simulations have been carried out for all the N values.for all the N values the new technique achieves a good PAPR reduction. NCT is an extra nonlinear operation applied to the transmitted signal. For this reason, how to minimize the impact of companding distortion on the BER performance is the key in choosing the optimal companding form and parameters. 52

6 IV. CONCLUSION In this paper SLM technique and NCT are applied to the OFDM systems. These techniques are adopted for all kind of OFDM systems. Simulations have been carried out for all the N values.for all the N values the new technique achieves a good PAPR reduction. Figure 4: papr reduction using n=256 NCT and SLM technique For PSK OFDM system with N=128 data subcarriers there is an 4.31 db reduction in PAPR value was achieved when compared with the conventional OFDM system. Due to its simplicity and effectiveness, NCT is an attractive solution to reduce the PAPR of OFDM signal. Figure 5: ORGINAL (vs) SLM (vs) NCT (vs) Method Comparision In this paper, we investigate NCT algorithm which changes the statistics of original signal from the complex Gaussian to a desirable PDF defined as a linear piecewise function. Thus, an effective and flexible trade-off between the PAPR and BER performance can be achieved to satisfy various system requirements. 53

7 V. REFERENCES [1] T. Hwang, C. Yang, G. Wu, S. Li, and G. Y. Lee, OFDM and its wireless application: A survey, IEEE Trans. Veh. Technol., vol. 58, no. 4, pp , May [2] W. Y. Zou and Y. Wu, COFDM: An overview, IEEE Trans. Broadcast., vol. 41, no. 1, pp. 1 8, Mar [3] D. Brillinger, Time Series Data Analysis and Theory. Philadelphia, PA: SIAM, [4] P.Foomooljareon and W.A.C. Fernando PAPR Reduction in OFDM Systems ThammasaItn t. J. Sc.T ech.,vol.7, No.3, September-December 2002 [5] Anil Singh Rathore and Dr. Neelam Srivastava Analysis of Selected Mapping and Partial Transmit Sequence for PAPR Reduction Journal Of Telecommunications, Volume 5, Issue 1, October 2010 [6] N.V. Irukulapati, V.K. Chakka and A. Jain SLM based PAPR reduction of OFDM signal using new phase sequence ELECTRONICS LETTERS 19th November 2009 Vol. 45 No.24. [7] Alireza Zolghadrasli, M.H. Ghamat Papr Reduction In OFDM System by using Hadamard Transform in BSLM Techniques 2007 IEEE [8] Chin-Liang Wang, Senior Member, IEEE, and Yuan Ouyang, Student Member, IEEE Low- Complexity Selected Mapping Schemes for Peak-to-Average Power Ratio Reduction in OFDM Systems IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 53, NO. 12, DECEMBER 2005 [9] Hyunseuk Yoo, Associate Member, IEEE Frederic Guilloud, Member, IEEE, and Ramesh Pyndiah, Senior Member, IEEE Low Complexity Partial Selected Mapping for PAPR Reduction of OFDM System published in "IEEE SCVT 2010: 7th Annual Symposium on Communications and Vehicular Technology, Enschede : Netherlands (2010)" [10] T. Jiang and Y. Wu, An overview: Peak-to-average power ratio reduction techniques for OFDM signals, IEEE Trans. Broadcast., vol. 54, no. 2, pp , Jun [11] X. B.Wang, T. T. Tjhung, and C. S. Ng, Reduction of peak-to-average power ratio of OFDM system using a companding technique, IEEE Trans. Broadcast., vol. 45, no. 3, pp , Sep [12] X. Huang, J. Lu, J. Zheng, J. Chuang, and J. Gu, Reduction of peaktoaverage power ratio of OFDM signals with companding transform, IEE Elec. Lett., vol. 37, pp , Apr [13] X. Huang, J. Lu, J.Zheng,K.B.Letaief, and J. Gu, Companding transform for reduction in peak-to-average power ratio of OFDM signals, IEEE Trans. Wireless Commun., vol. 3, no. 6, pp , Nov [14] T. Jiang, Y. Yang, and Y. Song, Exponential companding transform for PAPR reduction in OFDM systems, IEEE Trans. Broadcast., vol. 51, no. 2, pp , June [15] T. Jaing, W. Xiang, P. C. Richardson, D. Qu, and G. Zhu, On the nonlinear companding transform for reduction in PAPR of MCM, IEEE Trans. Wireless Commun., vol. 6, no. 6, pp , Jun [16] Ms. Shraddha R. Waghmare and Prof. Dr. Shripad P. Mohani, Energy a New Approach in Distortionless Techniques for PAPR Reduction in Multicarrier Transmission Systems International journal of Electronics and Communication Engineering &Technology (IJECET), Volume 4, Issue 5, 2013, pp , ISSN Print: , ISSN Online: [17] Ashok Kumar Kajla, Rupesh Sharma, Yash Walia, and Sukoon Mishra, Improve Peak To Average Power Ratio (PAPR) Reduction Techniques in OFDM Systems, International journal of Electronics and Communication Engineering &Technology (IJECET), Volume 4, Issue 7, 2013, pp , ISSN Print: , ISSN Online:

8 AUTHORS BIOGRAPHY VARADALA SRIDHAR is from Hyderabad, Andhrapradesh. Completed M.TECH in ECE with specialization (Wireless and Mobile Communication Systems) from JNTUH in 2011.he has completed M.Sc (IT) from Nagarjuna University, guntur, Andhra Pradesh. And B.TECH in ECE from vidyajyothi institute of technology affiliated by JNTUH in Currently he is working as an Assistant professor in ECE department at vidya Jyothi Institute of Technology, Hyderabad from he is having more than 4 years experience as an assistant professor. His areas of research interests include Wireless and Mobile communication systems, Digital signal processing, Image processing, Telecommunications, communication systems, Signal processing, embedded systems. ARUN KUMAR.R Completed M.TECH in CSE with specialization (Computer Science Engineering) from CVSR College of engineering affiliated by JNTUH in Currently he is working as an Assistant professor in CSE department at Vidya Jyothi Institute of Technology, Hyderabad. he is having 4 years experience as an assistant professor. He published 3 international journals. His areas of research interests include Networks, Analysis of Algorithm, Compiler and Language Processing. S.DINESH REDDY is from Hyderabad, Andhra Pradesh. Completed B.Tech in Electronics and Communications with 67.4% from Vidya Jyothi Institute Of Technology Affiliated To JNTUH in Completed Intermediate with 76%. Has done a project in Image Processing. Currently working with a few NGOs namely WWF-India, Andhra Pradesh State Office, Swecha (FSMI) and avashah - hands that help. Has good technical hold in Signal Processing, Communications and Control systems. Areas of interests in research include Digital signal Processing, Image Processing, Telecommunications, Communication Systems. Ch. SREEDHAR is from Hyderabad, Andhrapradesh. Completed M.TECH in ECE with specialization (VLSI Systems Design) from Kshatriya College of engineering affiliated by JNTUH in 2011and B.TECH in ECE from Aizza College of Engineering & technology affiliated by JNTUH in Currently he is working as an Assistant professor in ECE department at Global Institute of Engineering & Technology, Hyderabad from His areas of research interests include Wireless & Mobile communications, Digital signal processing, Image processing, Telecommunications, communication systems, Signal processing, embedded systems, network security. 55