Docstoc

COSINE MODULATED FILTER-BANK TRANSMULTIPLEXER USING KAISER WINDOW

Document Sample
COSINE MODULATED FILTER-BANK TRANSMULTIPLEXER USING KAISER WINDOW Powered By Docstoc
					   INTERNATIONAL JOURNAL OF ELECTRONICS AND
   International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
   0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME
COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET)
ISSN 0976 – 6464(Print)
ISSN 0976 – 6472(Online)
Volume 4, Issue 2, March – April, 2013, pp. 225-228
                                                                            IJECET
© IAEME: www.iaeme.com/ijecet.asp
Journal Impact Factor (2013): 5.8896 (Calculated by GISI)
                                                                          ©IAEME
www.jifactor.com




   COSINE MODULATED FILTER-BANK TRANSMULTIPLEXER USING
                      KAISER WINDOW

        Saurabh Khandelwal, Narendra Singh, Hemdutt Joshi, Sandeep Kumar arya
         Electronics and communication, Jaypee University of engineering & technology
                               Guna - 473226 (M.P), INDIA.


   ABSTRACT

           This paper presents the design of near perfect reconstruction (NPR) cosine modulated
   filter-bank (CMFB) transmultiplexer using Kaiser Window approach. Cosine modulation is
   used to design the synthesis an analysis sections of the transmultiplexer. The prototype filter
   is designed by using high side-lobe fall off rate (SLFOR) Kaiser window functions. A
   bisection optimization algorithm has been used, and without optimization algorithm used.
   The use of optimization algorithm is reduce the effect of ISI (inter symbol interference) and
   ICI (inter carrier interference).

   Keywords -OFDM, ICI, ISI, Kaiser Window SLFOR

   I.   INTRODUCTION

          Orthogonal frequency division multiplexing (OFDM) and discrete multitone
   transmission (DMT) are the widely use technologies in multicarrier communication. Both use
   IFFT or DFT for the modulation and demodulation of signals. Due to multipath fading over
   wireless communication, the consecutive OFDM symbols overlap at the receiver and gives
   rise to ISI and ICI .To minimize the ISI in OFDM system the guard band is used, which may
   loss of spectral efficiency. The DFT based modulation filter has side lobes of -13 dB .it
   provides better stop band performance with less complexity. The main contribution of this
   paper can summarize as below;
   1 The fixed Kaiser Window functions have certain limitations in selecting input parameters.
   Therefore, popular variable window functions with high side lobe falloff rate (SLFOR) are
   used for the design of prototype filters.
   2. A iteration method and without optimization is discussed.



                                                225
 International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME

 II.   CONVOLUTION CODES

       Convolution codes are specified on the basis of three parameters (n, k, L), where n, k, L
 are length of the codeword, number of input bits and constraint length respectively. The
 constraint length L, defines the past number of input bits in the memory register that affect
 the output code word. The rate of Convolution code is defined as the ratio of number of
 output bits to the input bits and is denoted by ‘r’. Therefore code rate r = k/n. [2]

III.   DFT MULTICARRIER TRANSMISSION TECHNIQUE

         To generate OFDM successfully the orthogonality principle between the carriers must
 be maintained. For this reason, OFDM is generated by first choosing the spectrum required,
 based on the input data, and modulation scheme used. Each carrier to be produced is assigned
 some data to transmit. The required amplitude and phase of the carrier is then calculated
 based on the modulation scheme (typically differential BPSK, QPSK, or QAM). The required
 spectrum is then converted back to its time domain signal using an Inverse Fourier
 Transform. In most applications, an Inverse Fast Fourier Transform (IFFT) is used. The IFFT
 performs the transformation very efficiently, and provides a simple way of ensuring the
 carrier signals produced are orthogonal.
         The Fast Fourier Transform (FFT) transforms a cyclic time domain signal into its
 equivalent frequency spectrum. The IFFT performs the reverse process, transforming a
 spectrum (amplitude and phase of each component) into a time domain signal. An IFFT
 converts a number of complex data points, into the time domain signal of the same number of
 points. Each data point in frequency spectrum used for an FFT or IFFT is called a bin. The
 orthogonal carriers required for the OFDM signal can be easily generated by setting the
 amplitude and phase of each frequency bin, then performing the IFFT. Since each bin of an
 IFFT corresponds to the amplitude and phase of a set of orthogonal sinusoids, the reverse
 process guarantees that the carriers generated are orthogonal. Figure 1 below shows the bock
 diagram of basic OFDM transmitter and receiver. The signal generated is at base-band and so
 to generate an RF signal the signal must be filtered and mixed to the desired transmission
 frequency.




                   Fig.1 Block Diagram of OFDM Transmitter and Receiver

IV.    TRANSMULTIPLEXER SYSTEM:

       The M-channel maximally decimated transmultiplexer is shown in Fig.2. Basically it is a
   TDM-FDM-TDM converter. It consists of synthesis block at transmitter end and precedes the
   analysis block at receiver end. At the transmitter end, M-input signals are first interpolated by


                                               226
International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME

                                                                                       bank,
 the factor of M and synthesized into one composite signal using synthesis filter bank Fk (z)
                                                                  composite
 for k = 0, 1, . . ., M − 1. Conversely, at the receiver end, the composite signal is split out into
    output                                                            )
 M-output signals with the help of the analysis filter bank Hk (z) and then decimated by a
             .
 factor of M. the equation of the transmultiplexer is given as;
                                        n −1
         ˆ
        X k (Z ) =                      ∑      S km ( Z ) X       (Z )                                                          (1)
                                                              m
                                        m =0




           ˆ                                                                                                                    (2)
           X ( z ) = s( z ) x( z )

If, s (z) is diagonal then it is free from cross talk.
       z)

          ˆ
          X k ( z ) = S kk ( z ) xk ( z )                                                                                       (3)




                                                     Fig: 2 M-channel transmultiplexer

V.    SIMULATION RESULT

                               0                                                            0

                              -50
                                                                                          -50
                             -100
             B




                                                                                 B
            d




                                                                                d




                             -150
                                                                                         -100
                             -200

                             -250                                                        -150
                                    0              0.5                   1                       0            0.5           1
                                          Normalized Frequency                                       Normalized Frequency

                               1                                                          -61

                                                                                         -61.5
                 M g itu e




                                                                             M n itu e




                              0.9
                  an d




                                                                              ag d




                                                                                          -62

                                                                                         -62.5
                              0.8
                                                                                          -63

                              0.7                                                        -63.5
                                    0              0.5                   1                       0            0.5           1
                                          Normalized Frequency                                       Normalized Frequency




                       Fig.3: With optimization algorithm using Kaiser Window approach



                                                                             227
 International Journal of Electronics and Communication Engineering & Technology (IJECET), ISSN
 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME

 Without optimization the cosine modulated filter bank results are:
 For M=8:




 For M=16:




VI.   CONCLUSION
       In this paper, the performance of TMUX-OFDM systems and cosine modulated filter
 bank systems is discussed. The cosine modulated transmultiplexer using Kaiser Window
 approach is give better result as Blackman window. The optimization algorithm gives less
 error as compared to without optimization.

 REFERENCES
 [1]M.G.Bellanger, J.L.Daguet,"TDM–FDM transmultiplexer: Digital polyphase and FFT", IEEE
 Transaction on Communication Vol.22, no.9, pp.1199–1205, 1974.
 [2] R.K.Soni A.Jain, R.Saxena, “An improved and simplified design of pseudo
 Transmultiplexer using Blackman window family," Digital Signal Processing Vol.20, no.3,
 pp.743–749, 2010.
 [3]M.Vetterli,"Perfect Transmultiplexer," Proceedings of IEEE ICASSP, pp. 2567- 2570, Tokyo,
 1986
 [4] R.Prasad, N.R.Van, "OFDM for wireless multimedia communications,"Artech House
 Publishers (2000).
 [5] F. Cruz-Roldan and M. Monteagudo, “Efficient implementation of nearly-perfect
 reconstruction cosine-modulated filter banks,” IEEE Transactions on Signal Processing, vol. 52,
 no. 9, pp. 2661-2664, Sep. 2004.
 [6] R.K.Soni, A.Jain, R.Saxena, “An optimized transmultiplexer using combinational window
 functions," Signal, Image and Video Processing Online, April 2010.
 [7] K.Muralibabu, Dr.K.Ramanaidu, Dr.S.Padmanabhan and Dr.T.K.Shanthi, “A Novel PAPR
 Reduction Scheme Using Discrete Cosine Transform Based on Subcarrier Grouping in OFDM
 System”, International journal of Electronics and Communication Engineering &Technology
 (IJECET), Volume 3, Issue 3, 2012, pp. 251 - 257, ISSN Print: 0976- 6464, ISSN Online: 0976 –
 6472

                                              228

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:1
posted:4/18/2013
language:
pages:4