Design and Analysis of Bit Error Rate Perfornance of Simulink based DSSS-OFDM Model for Wireless Communication

DOI : 10.17577/IJERTV1IS3008

Download Full-Text PDF Cite this Publication

Text Only Version

Design and Analysis of Bit Error Rate Perfornance of Simulink based DSSS-OFDM Model for Wireless Communication

Rakesh D. Koringa

Electronics and Communication Government Engineering College Surat, India

Abstract Because of the rap id gro wth of Digita l Co mmunicat ion in recent years, the need for high speed data transmission is increased. Orthogonal frequency division mult iple xing (OFDM) technique is suitable for high speed communication because of its resistance to ISI (inter symbol interfe rence) and it utilizes the bandwidth efficiently. DSSS-OFDM is a co mb ination of OFDM and DSSS techniques suitable for design of mult i-user system and robust against channel impairments. This paper compares bit error rate (BER) performance of simu lin k based DSSS-OFDM mode l for diffe rent modulation technique. Here we have used BPSK, QPSK and M -PSK, M-QAM modulation techniques.

Keywords OFDM, DSSS-OFDM, MPSK, Spread Spectrum


    For modern wireless communication high data rate is a most important parameter. The principles of orthogonal frequency division multip le xing (OFDM) modulation have been in existence for several decades. These techniques are extensively used now in modern communications systems. Some of the applications of OFDM are Wire less networking, data transmission over the phone line, digital radio and television. OFDM is one of the applications of a parallel-data-transmission scheme, wh ich reduces the influence of mu ltipath fading and ma kes comple x equalize rs unnecessary. One of the ma in reasons to use OFDM is to increase robustness against frequency-selective fading or narrowband interference. OFDM has been combined with spread spectrum (SS) techniques to provide reliable communications on frequency selective channels. For low symbol rates, this combination is robust enough against radio channel impa irments. For high data rate applications the technique would highly suffer fro m interferences. There are number of methods of spreading frequency spectrum in spread spectrum communication systems. Basically, these methods include Direct Sequence Spread Spectrum (DSSS), Frequency Hopping Spread Spectrum (FHSS), Time Hopping Spread Spectrum (THSS), and combinations of these methods. Multiband Orthogonal Frequency Division

    Prof. Tejas S. Patel

    Electronics and Communication Government Engineering College Surat, India

    Multiple xing (M B-OFDM ) is a scheme of multica rrier transmission for ultra-wideband (UWB) commun ication which e mploys the frequency hopping technique to spread its signal spectrum [3]. Both DS and FH systems reduce the average power spectral density of a signal and affects by broadband noise. Performance of both systems depends on the particular application, the space available, power, and comple xity of the receiver. Narrowband interference impacts severely on an FH signal than a DS signal on the same channel. Usually DS systems uses power effic ient PSK modulation and FH systems uses less power effic ient FSK. The probability of error, for a g iven SNR, is better for PSK. DS is self synchronizing but receiver synchronization in frequency hopping is more difficult. In DSSS, higher the chip rate of PN code, the smalle r will be the degradation due to multipath and in FHSS if the carrie r frequency of t he transmitted signal hops fast enough then only multipath effect will be diminished. We have designed simulink based DSSS-OFDM and OFDM model and tested it with BPSK, QPSK and 8-PSK modulation technique. We have obtained simulated results and compared BER performance of the model.



    OFDM is a special mu lti-carrie r transmission technology in which h igh-speed serial data are converted into N channel parallel data and certain frequency band is divided into N orthogonal sub-channels. N way different sub-carriers are used to modulate the N-channel data separately, and then transmit the sub-carrier paralle l [1]. The traditional frequency division multiple xing method needs a lot of filters in receiver and transmitter for the spectrum of each sub- carrier is non overlapping and the sub-carrier must maintain sufficient frequency separation to reduce the mutual interference between the sub-carrier. So the system comple xity and cost increase greatly and the frequency utilization is reduced. The OFDM system uses digital signal processing technology. Digita l signal processing algorithm is adopted in the process of sub-carrier generation and reception and then the structure of the system is simp lified greatly. Meanwhile, in order to imp rove frequency spectrum utilization, each sub-carrier spectrum which meet the orthogonally throughout the symbol period to ensure the

    receiving end recover the signal without distortion is overlapped. The OFDM signal spectrum is shown in Figure

    1. Two key points of an OFDM system are the Inverse

      Discrete Fourier Transform at the transmitter side and the Discrete Fourier Transform at the receiver side. By these the robustness of the sent data over a fading mult ipath channel is preserved [6].

      Figure 1. OFDM signal spectrum

      OFDM techniques are quickly becoming a popular method for advanced communications networks. Advances in VLSI technology have made it possible to efficiently imple ment an FFT block in hardwa re. The N-point DFT and IDFT are defined as



      Where N is the nu mber of subchannels and W is the bandwidth in the OFDM system. One can think of the above expression as comple x data symbols mapped to comple x OFDM symbols, wh ich make up the data sy mbols being sent on different subchannels. In this way the available spectrum is divided into several subchannels which are narrowband and therefore e xperience almo st flat fading during transmission. The use of FFT technique ma kes OFDM co mputationally more fast and effic ient too. Cyclic pre fix is used to reduce the inter-symbol- interference (ISI) as we ll as inter-channel-interference (ICI) which is introduced by the multi-path channel.


    There are nu mber of methods of spreading frequency spectrum in spread spectrum (SS) co mmunicat ion systems. Basically, these methods include Direct Sequence Spread Spectrum (DSSS), Frequency Hopping Spread Spectrum (FHSS), Time Hopping Spread Spectru m (THSS), and combinations of these methods. Multiband Orthogonal Frequency Div ision Multiple xing (M B-OFDM) is a scheme of mult icarrie r trans mission for u ltra-wideband (UWB) communicat ion which e mp loys the frequency hopping technique to spread its signal spectrum. Here we will discuss about Direct Sequence Spread Spectrum. The basic form of the output signal of DSSS is given by equation;

    Where a(t) is a sequence of pulses to spread the data, and d(t) is a sequence of pulses of duration T of the digital data [4]. If the sequence d(t) is narrowband and a(t) is wideband, the product signal will have a spectrum nearly equal to that of a(t) [7].Direct sequence spread spectrum use a spreading sequence of positive and negative pulses at a very high chip rate. In this scheme the data signal is mu ltip lied by the spreading sequence, and then modulated by the required carrier frequency as shown in (1). Fro m Fourier Transform, we know that multip lication of two unrelated signals produces a product signal whose spectrum equals the convolution of the spectra of two individual signals. The spread signal is to be recovered by applying a despreading sequence at the receiver. The de-spreading sequence is just identical to the spreading sequence used at te transmitter. The type of PN sequence used its length, and its chip rate, set limits on the capability of the system. The capability can only be changed by modifying the PN sequence on above said parameters.


    The combination of Orthogonal Frequency Division Multiple xing (OFDM ) with Direct Sequence Spread Spectrum (DSSS) is favorable for mu lti-user system. The combination na med DSSS-OFDM is found robust against channel impairments and its power spectrum density re mains constant. This system can a lso effectively reduce the peak-to-average power rat io of the transmitted signal. The DSSS-OFDM signal characterizes by much wider bandwidth than that of the conventional OFDM signal. It has also the characteristics of a white noise therefore it can realize effective ultra-wideband communication. Wideband communicat ion effic iently reduces the interference problems. We can use the wide bandwidth characteristics of the DSSS-OFDM signal to control the received signal bandwidth by designing matched filte rs. The transmitted bandwidth can be selected fle xibly to suit for different communicat ion systems under different circu mstances [3].

    Many current efforts to develop broadband wireless capability are now concentrating towards developing systems, technologies, protocols, and even programming languages. OFDM has been combined with Direct Sequence Spread spectrum (DSSS) techniques to provid e reliable co mmunicat ions on frequency selective channel. Multipath fading is very much influencing the performance of wireless communication link. Basic layout of DSSS – OFDM model is shown in figure 2.


    Figure 2. B asic layout of DSSS-OFDM model

    Let see how spreading help us to improve the performance over noisy channel. The Shannons capacity theorem is


    Shannon's channel capacity formula describes the principle of spread spectrum system, shown in equation 4. Where C is the channel capacity, B is the signal bandwidth, PS is the signal power and PN is the noise power [3]. The amount of informat ion that can be transmitted over a given channel is proportional to the product of the channel bandwidth and the time of operation. Th is indicates that when the signal to noise ratio of the transmission system drops in a Gaussian channel, the channel capacity can re main unchanged by increasing the transmission bandwidth. Shannon's theory also indicates that with the presence of Gaussian noise interference, the optimu m signal for re liable co mmun ication is the signal with the statistical characteristics of a white noise. The power spectral density of (both sided signal) a white noise is


    where N0 is the single-sided power spectral density. Its autocorrelation function is




    Autocorrelation function of a white noise is an impulse function. The signal transmitted on the AW GN channel should be designed so that its autocorrelation function is an impulse function, it has been also proved theoretically that to overcome mu lt ipath interference the optimu m

    transmitted signal is a lso a signal with the statistical characteristics of a white noise.


      1. Simulink based DSSS-OFDM model with MPSK modulation

        We have imp le mented DSSS-OFDM model using simu lin k as shown in Fig. 3. Random binary data is generated by Random Integer b lock. Th is randomly transmitted data is then modulated by MPSK modulator (Here we have used M=2, 4, 8 for BPSK, QPSK, 8-PSK respectively). This MPSK modulated data is again modulated by OFDM modulator. Ins ide the OFDM modulator we have used zero padding, IFFT b locks and cyclic prefix bloc ks in sequence. Zero padding blocks append zeros to the specified dimension if it is not available at the input of IFFT bloc k. Ultimately it decides the number of subcarriers to be used. Now OFDM signal is spreaded using PN sequence and transmitted and after passing through the AWGN channel is first despreaded using same PN sequence which was used at transmitter side and then demodulated by the OFDM de modulator which is co nsist of Re move Cyclic Pre fix, FFT, Re move Ze ro Pad blocks in sequence. Cyclic prefix which is attached to OFDM signal before transmission is to be removed by Re move Cyclic Prefix b lock. Then FFT will process the data to get the data same as that of input given to the IFFT bloc k. Afte r this one has to remove the zero padding. No w M PSK de modulator is used to demodulate this data to obtain random integer data transmitted by the random integer generator block.

        Figure 3. Si mulink based DSSS -OFDM model using MPS K modul ati on

        In MATLB 7.8 fo llo wing toolbo xes are required to imple ment above simulink model (1) Signal Processing Toolbox (2) Co mmunication Toolbo x. Following shows the blocks and parameter used in above simu lin k model.

        1. Random integer generator: He re we have set samp le time to 1/10 and sa mple per fra me to 10. So that we can get the fra me output of vector matrix with dimension 10×1.

        2. Modulator baseband: Here we have used M-PSK baseband modulatator.

        3. OFDM modulator: This blocks includes zero padding, IFFT bloc k, cyclic prefix bloc k in sequence. Zero padding is done at the end of data to match with required FFT length i.e. 16 (wh ich we have used). IFFT is performed to convert frequency domain signal into time domain. Cyclic p refix is added to combat inter carrie r interferences (ISI). Here we have added last 7 bits of each symbol as cyclic pre fix.

        4. AWGN channel: Here we have used AWGN channel for co mmunicat ion mediu m.

        5. OFDM demodulator: In this block we first remove

          cyclic pre fix then 16 point-FFT is used to convert time domain data into frequency doma in and then ze ro padding is re moved which we have added before transmitting

        6. Demodulator baseband: Here we have used M-PSK baseband demodulatator.

        7. Error rate calculation : This block is used to caculate numbrer of b it co mpared, nu mber of bit in error and bit error rate.

        8. PN sequence generator: In this b lock we have set sample t ime to 1/100.

        9. Unipolar to bipolar convertor: Here we have set M- arynumber to 2.

      2. Simulink based DSSS-OFDM model with M-QAM modulation

    Figure 4. Si mulink based DSSS-OFDM model using M-QAM modulati on

    Simu link mode l shown in figure 4 is same as shown in figure 3 only the diffe rence is here we have used rectangular M-QAM modulator and de modulator.


    Figure 3 shows the imple mentation of DSSS-OFDM using M-PSK modulation. Any number of phases may be used to construct a PSK constellation but 8-PSK is usually the highest order PSK constellation deployed. With more than 8 phases, the error-rate becomes too high and there are better, though more comple x, modulations available such as quadrature amplitude modulation (QAM). Although any number of phases may be used, the fact that the constellation must usually deal with binary data means that the number of symbols is usually a power of 2; this allo ws an equal number of bits-per- symbol. Figure 3 shows the imple mentation of the OFDM model with the higher order PSK modulation. We have simulated the DSSS-OFDM model with selected BPSK, QPSK, 8-PSK, 16-PSK, 64-PSK modulation Techniques. Simu lation results for OFDM with 8-PSK is found suitable for long distance communication link. BER for 8-PSK found rapidly falls above 40 d B SNR for DSSS-OFDM. Fro m the simulated results we can observe that spreading makes system able to handle at more SNR levels for higher order modulation used, meaning that higher order modulation cannot be handle at smaller distances. As shown in simulated results one can recommend DSSS-OFDM with BPSK and QPSK modulation for short distance communication. We may select specific higher order PSK modulation over the long distance keeping the limit of affordable SNR levels. Fro m the smulated results we can easily observe that as we go on selecting the higher order PSK modulation scheme, the poorer BER we have to bear.

    Figure 5. B ER per for mance of DSSS -OFDM using 2, 4, 8, 16, 64-PSK modulation

    Figure 6 Comparati ve B ER perfor mance of DSSS – OFDM using PSK and QAM modulati on

    Fro m overall co mparison it is proved that DSSS-OFDM with QAM modulation have better BER performance than that of DSSS-OFDM with M-PSK. It increases comple xity. To have perfect comparison over the range of PSK we have simulated our model on M-PSK range. Simulated results are shown in Figure 5. One can easily view fro m the comparative study that spreading requires to be handled on the increased level of SNR for getting lower value of BER. But it would give us re markable improve ment in mu ltipath environment. This is the point where we can choose DSSS- OFDM for wireless broad band Application.

    We have also tested our DSSS-OFDM model shown in figure 4 with M-QAM modulation. The simu lated results are shown in figure 6 which shows the tremendous improvement in BER performance compared with M -PSK modulation used where 16, 64 QAM is compared with the 16, 64 PSK modulation used for testing BER performance of DSSS-OFDM model after comb ing OFDM with DSSS. We have found that system can be effectively handle communication on short as well as long distances using M- QAM modulation with the efficiently reduced interference, that too with imp roved BER rate. DSSS-OFDM model has another advantage of inherent security due to use of DSSS.


A concept of OFDM modulation co mb ined with DSSS results in DSSS-OFDM. The resulted signal characterizes by wide bandwidth spectrum. It has statistical characteristics of a white noise. In a proposed method, each carrie r is itself spread by means of the pseudo -noise sequence. We have simulated the DSSS-OFDM mode l with selected BPSK, QPSK, 8-PSK, 16-PSK, 64-PSK and 16-

QAM, 64-QAM modulation techniques. Simu lation results for DSSS-OFDM with BPSK, QPSK modulation is found suitable for short distance commun ication whereas 8-PSK modulation can be used for long distance communication. Fro m overa ll co mparison it is proved that DSSS-OFDM

with M-QAM modulation has comparat ively better BER performance than of DSSS -OFDM with M -PSK. We conclude that the use of M-QAM instead of M -PSK is recommended for better BER performance of DSSS- OFDM simulink based model. all the above analysis is done for AWGN channel only. If the channel is not gaussian, we need to estimate the channel first and then use a different co mb ining process. For future work, we can consider practical mu ltipath channel and research on effective co mbin ing and equalizat ion techniques.


  1. LIAN Hua, ZhAO ruimei, HU boning, PANG Huawei,Simulation and Analysis of OFDM Communication System, International Conference on Industrial Mechatronics and Automation, 2010, pp. 677-680.

  2. Alan C. Brook, Stephen J. Hoelzer, Final Report,Design and Simulation of Orthogonal frequency Division Multiplexing (OFDM) Signaling 15 may, pp. 1-4, 2001Electronic Publication: Digital Object Identifiers (DOIs):

  3. Pingzhou T u, Xiaojing Huang, Eryk Dutkiewicz, A Novel Approach of Spreading Spectrum in OFDM Systems International Symposium on communication and Information technology, 2006, pp. 487-491.

  4. Guillermo Fernandez S., Adolfo Espinoza P., Direct Sequence and Frequency Hopping Spread Spectrum Systems, understanding differences between both schemes pp. 1-7, Available at Internet/Articulos Tecnicos de Consulta/Instalaciones Electricas Industriales/ID008.pdf.

  5. Raymond L. Pickholtz, Fellow, IEEE, Laurence B. Milstein, Fellow, IEEE, Donald L. Schilling, Fellow, IEEE, Spread Spectrum for Mobile Communication IEEE Transaction on Vehicular Technology, vol 40, No. 2, May 1991, pp. 313-322.

  6. Ramjee Prasad, OFDM for Wireless Communication Systems, Artech House Publishers, 2004,pp. 11-15.

  7. Simon Haykin, Digital communication Edition:2006,pp. 451-452.

  8. Yong Soo Cho, Jaekwon Kim, Won Young Yang, Chung G. Kang, MIMO-OFDM Wireless Communication With MATLAB, John Willey and Sons (Asia) Pte Ltd, 2010.

Leave a Reply