International Journal of Scientific and Research Publications, Volume 2, Issue 5, May 2012 1 ISSN 2250-3153 www.ijsrp.org Comparison of Exponential Companding Transform and Adaptive-ACE Algorithm for PAPR Reduction in OFDM Signal Neelam Dewangan, Mangal Singh Chhatrapati Shivaji Institute of Technology, Durg, India Email- neelamdewangan@csitdurg.in, mangalsingh@csitdurg.in Abstract- One of the main disadvantages of Orthogonal Frequency Division Multiplexing (OFDM) is its high peak-to- average power ratio (PAPR). As the simplest approach to reducing the PAPR, Clipping based Active Contellation Extension (CB-ACE) exhibits good practicability, and the repeated clipping-and-filtering (RCF) algorithm proposed by Jean Armstrong provides a good performance in PAPR reduction and out-of-band power’s filtering. However, its way of filtering in frequency-domain requires RCF operations to control the peak regrowth, which degrades the bit error rate (BER) performance and greatly increases the computational complexity. Therefore, this paper put forward comparison of two existing techniques namely Exponential Companding Transform and Adaptive-ACE Algorithm. The simulation results show that, exponential Companding Transform gives better result for PAPR Reduction and provides low complexity in Algorithm. Index Terms- ACE, Exponential Companding Transform, OFDM, PAPR, RCF I. INTRODUCTION s a promising technique, OFDM has been widely used in many new and emerging broadband communication systems, such as digital audio broadcasting (DAB), high- definition television (HDTV), wireless local area network (IEEE 802.11a and HIPERLAN/2). However, as the OFDM signals are the sum of signals with random amplitude and phase, they are likely to have large PAPR that requires a linear high-power- amplifier (HPA) with an extremely high dynamic range, which is expensive and inefficient. Furthermore, any amplifier nonlinearity causes inter modulation products resulting in unwanted out-of-band power. A number of approaches have been proposed to deal with the PAPR problem, including clipping, clipping-and-filtering (CF), coding, companding transform, active constellation extension (ACE), selected mapping (SLM), partial transmit sequence (PTS), and so on [1]. Compared with other methods, clipping is the simplest and of good practicality. In particular, Jean Armstrong has proposed a RCF Algorithm which is also called Clipping Based Active Constellation Extension, which dramatically reduces the PAPR and limits the out-of band power to a low level , but excessively increases the computational complexity as well. Based on Jean Armstrong’s method, this paper describes an improved approach which can provide good performance and lower complexity. II. DEFINITION OF OFDM SIGNALS AND PAPR In OFDM, a block of N symbols, {Xk, k=0, 1, … , N-1}, is formed with each symbol modulating one of a set of subcarriers, {fn ,n=0, 1, ….., N-1} with equal frequency separation 1/T, where T is the original symbol period. An inverse discrete Fourier transform (IDFT) can efficiently generate the multicarrier symbols. The IDFT of vector Xk=[X0, X1,…..XN-1] results in T/N spaced discrete time signal xn=[x0, x1,…..xN-1]T. Thus, the transmitted signal is The PAPR of the transmitted signal can be written as The complementary cumulative distribution function (CCDF) is one of the most frequently used performance measures for PAPR reduction techniques, which denotes the probability that the PAPR of a data block exceeds a given threshold z. The CCDF of the PAPR of a data block of N symbols with Nyquist rate sampling is derived as P( PAPRz)1P( PAPR z)1(1e z ) N  III. THE ADAPTIVE -ACEALGORITHM The main objective of the Adaptive Active Constellation Extension (Adaptive ACE) algorithm for reducing the Peak-to- Average Power Ratio (PAPR) is to control both the clipping level and the convergence factor at each step and thereby minimize the peak power signal whichever is greater than the initial target clipping level [3]. A