A NUMERICAL SIMULATION OF SYMBOLS FOR CPFSK MODULATION

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1 International Journal of Electronics and Communication Engineering and Technology (IJECET) Volume 7, Issue 6, November-December 2016, pp , Article ID: IJECET_07_06_016 Available online at ISSN Print: and ISSN Online: IAEME Publication A NUMERICAL SIMULATION OF SYMBOLS FOR CPFSK MODULATION M.S.V. Vara Prasad and K. Krishna Murthy Department of Electronics, P.G. Center, P. B. Siddhartha College of Arts & Science, Vijayawada, ANU, A.P, India Ch. Nagabhushanam Department of Physics, U.G Courses, K. B. N. College, Vijayawada, KU, A.P, India ABSTRACT Capacity analysis of CPFSK is used between error probability and signal to noise ratio. Previous research has considered the spectral efficiency of several modulation schemes. This present work imposed to improve the channel capacity of the CPFSK modulation scheme in fiber optic communication, for this purpose an attempt is made by implementing the MatLab coding for CPFSK Modulation Scheme. This numerical simulation gives the Higher Symbols transfer rate in the CPFSK Modulation. The performance is useful to improve Spectral efficiency of optical channels. Key words: Continues Phase Frequency Shift Keying (CPFSK), Signal to Noise Ratio (SNR), Bit Error Rate (BER), Channel Capacity, Spectral Efficiency, Error Probability (EP), Symbols, Inter Symbol Interference (ISI), Power Spectral Density (PSD). Cite this Article: M.S.V. Vara Prasad, Ch. Nagabhushanam and K. Krishna Murthy, A Numerical Simulation of Symbols for CPFSK Modulation. International Journal of Electronics and Communication Engineering and Technology, 7(6), 2016, pp INTRODUCTION Telecommunications and computer networks, multiplexing (sometimes contracted to mixing) is a method by which multiple analog message signals or digital data streams are combined in to one signal over a shared medium. CPFSK modulation is similar to FSK modulation except that the condition of phase continuity is imposed at symbol transitions. This result in memory inherent in CPFSK signals in the form of phase information carried from previous symbol to current symbol. The modulation can be performed in several ways. The most basic method of generation of CPFSK signals is through construction of phase tree. Another method is through Implementation of a state machine these two modulation schemes, respectively. Depending on the pre-modulating filter used (filtered data impulse) we consider the following classes of CPFSK modulated signals: integral response CPFSK modulated signals [1-13] defined by modulating impulses extending over one symbol editor@iaeme.com

2 M.S.V. Vara Prasad, Ch. Nagabhushanam and K. Krishna Murthy In optical fiber communication system, the source provides information in the form of electrical signal to the transmitter. The electrical stage of the transmitter drives an optical source to produce modulated light wave carrier. Semiconductor LASERs (or) LEDs are usually used as optical source here. The information carrying light wave then passes through the transmission medium i.e. optical fiber cables in this communication system. Now it reaches to the receiver stage where the optical detector demodulates the optical carrier and gives an electrical output signal to the electrical stage. The common types of optical detectors used are photodiodes, p-i-n, avalanche, phototransistors, photoconductors etc. Finally the electrical stage gets the real information back and given it to the concerned destination.[7-18] The optical carrier may be modulated by either analog or digital information signal. 2. CPFSK The available channel bandwidth is limited in many digital communication systems. Consequently, the system designer has to consider the constraints imposed by the channel bandwidth limitations in selecting the modulation technique used to transmit the information. Thus, it is important to know the spectral content of digitally modulated signals. The spectral distribution is very important in furnishing bandwidth requirements and in evaluating mutual interference between neighbouring channels. Also, power spectral density (PSD) is critically important in optimizing procedures. In many applications it is essential to know the frequencies and the extent to which sharp spectral peaks occur. These peaks under certain conditions can become delta functions causing several cross talk. Thus, estimation of Power Spectral Density (PSD) of a signal is one of the frequently used post-processing operations. This necessitated the need for PSD computation of CPFSK signals simulation [1-14] 3. CONTINUOUS PHASE MODULATION (CPM) Continuous Phase Modulation (CPM) is a memory-type, constant-envelope, nonlinear Modulation [1], which allows the use of power efficient low cost, nonlinear power amplifiers without introducing distortion. Digital transmission using constant-envelope CPM has become important because of its attractive properties. The constant-envelope designs are fairly immune to nonlinear channel effects. Although constructions of CPM are diverse in their properties and applications, they all really upon the use of inherent memory introduced by the continuous phase. This constraint of continuous phase not only provides faster spectral roll-off, but also permits multiple symbol detection rather than the more conventional symbol-by-symbol detection. In this, two subclasses of CPM called Continuous Phase Frequency Shift Keying (CPFSK) and Continuous Phase Chirp Keying (CPCK) are described, although the treatment provided applies, in general, to any CPM. Concepts, mathematical descriptions and properties of CPM signals are presented with primary focus on CPFSK and CPCK signaling techniques [6-8, 15-18]. 4. FSM-BASED CPFSK MODULATION In FSK, a digital input sequence u selects one of m frequencies (if u k is m-ary) in each signaling interval of length T; that is, the transmitted signal η(t) is η (t) = Cos [ω(u k ) t + θ k ], KT t (K ) (1) where, ω(u k ) is the frequency selected by u k, and θ k is some phase angle. It is desirable for reasons both of spectral shaping and of modulator simplicity that the phase be continuous at the transition interval; that is, that ω (u k 1 ) KT + θ k-1 = ω (u k ) KT + θ k mod 2 (2) This is called continuous-phase FSK. The continuity of the phase introduces memory into the modulation process; i.e., it makes the signal actually transmitted in the k th interval dependent on previous signals. To take the simplest possible case (deviation ratio =1/2, i.e. modulation index =1/2), let the input sequence u be binary and let ω(0) and ω(1) be chosen so that ω(0) goes through an integer number of cycles in T seconds and ω(1) through an odd half-integer number; i.e. ω(0)t 0 and ω(1)t π modulo 2π editor@iaeme.com

3 A Numerical Simulation of Symbols for CPFSK Modulation Then if θ0=0, θ1= 0 or π, according to whether u0 equals zero or one, and similarly θ k = 0 or π, according to whether an even or odd number of ones have been transmitted. Here we have a two-state process, with X={0, π}. The transmitted signal yk is a function of both the current input u k and the state x k : Y K = Cos [ω (UK) t + χ K ] = Cos χ K cos ω (U K KT t < (K + 1) T (3) Since transitions ξk = (xk+1, xk) are one-to-one functions of the current state xk and input uk, we may alternately regard yk as being determined by ξk. If we take h0(t)= cos ω(0)t and h1(t)= cos ω(1)t as bases of the signal space, we may write Y K = Y OK η 0 (t) + Y 1K η 1 (t) (4) where the coordinates y0k and y1k are given by (1,0)if UK = 0,XK = 0 ( 1,0)if UK = 0,XK = h (Y OK, Y 1K ) = (5) (0,1)if UK = 1, XK = 0 (0, 1)if UK = 1, XK = π Thus, the state machine of MSK generation is described by the following diagram Figure 1 MSK State Transition Diagram 5. GENERAL SCHEMATIC OF CPM MODULATOR a Pulse shaping Filter f(t) FM Modulates S(t,a) 2πh 2πf C Figure 2 Basic structure of single-h CPM modulator Figure 2 represents a conceptual block diagram of the single-h CPM, which is the focus of this thesis. Data sequence passes through the pulse shaping filter and the multiplier to form frequency pulse sequence a, which is then FM modulated to generate the CPM signal editor@iaeme.com

4 M.S.V. Vara Prasad, Ch. Nagabhushanam and K. Krishna Murthy 6. RESULTS In the CPFSK Binary System with respect to a Mat Lab Simulation with identical parameters results shown in Mat Lab Environment. To analyse the performance of the symbols in CPFSK modulation at various samples observed the error probability and SNR are drawn in the graphical patterns at Constant Samples. Graph 5.8 (b): At Samples Consolidated Graph Graph 5.16 (b): At Samples (Consolidated Graph) 6.1. Analysis In graph (1) shows the signal to Noise ratio with respect to Error Probability for low sample rates. It shows Non Linearity at lower sample rates. On the other hand In the graph (2) shows the higher symbols of transmission with respect to Error Probability occurrence at higher sample rates and also more linear when Compared to lower sample rates. Graph (3) shows that the SNR is low i.e 0 to 4dB the ER is high whereas for higher SNR i.e. 6dB to 10dB the EP is low in the CPFSK modulation scheme editor@iaeme.com

5 A Numerical Simulation of Symbols for CPFSK Modulation 7. CONCLUSION The spectral efficiency of channel will improve with CPFSK modulation in optical communications. In CPFSK modulation and demodulation, at lowest data rate of transmission, the SNR increases and received signal error probability of occurrence decreased unevenly up to 5000 samples. At highest sample rate of symbol transmission will improves the error probability linearly at low SNR then increase in SNR at low error probability by varying the number of samples we observed that at lowest sample rate of transmission for a particular SNR, the error probability is more when compared with the highest sample rate of transmission. SNR and error probability results of the system were reliable with respect to the theory and higher data rates are possible in CPFSK modulation. The modulation parameters are adjusted to provide a desired error Probability with respect to SNR performance without interrupting the (symbol) data transmission. Symbol rate and modulation level can provide performance of the channel condition. We can conclude from the Mat lab Simulation of CPFSK Modulation Scheme, it improves the channel capacity at higher symbol transmission. CPFSK modulation gives the analysis of inter symbol interference (ISI) in the channel of optical fibre communication network. In that aspect the spectral efficiency of channel will improve in multipath optical Communication networks. Comparatively CPFSK modulation gives more channel capacity in optical networks than the earlier modulation techniques, CPFSK modulation is useful to improve spectral efficiency of optical channel in future designed Multiplexing optical networks of multipath fading and higher order implementation for further research i.e. 4 th and 5 th Generation Mobile Communications. REFERENCE [1] Fonseka, J.P. Non Linear Continuous Phase Frequency Shift Keying, IEEE Trans.on Communications, 1991 COM 39, PP [2] M. Alnuaimi, K.Shuaib and I. Jawhar, performance evaluation of IEEE physical layer using Mat Lab / Simulink [3] J.B.Anderson, W.Sundberg Advances In Constant Envelope Coded Modulation, IEEE Communications Magazine, Dec PP [4] M.G.Pelchat, The Auto Currelation Function and Power Spectrum of Pcm/Fm with Random Binary Modulating Wave Forms. IEEE Trans Space Electron Telem, PP 39-44, Mar [5] A.J.Gold Smith And S.G.Chua, Variable Rate Variable-Power M-Qam for Fading Channels, IEEE Trans. Communi., Vol.45, PP , Oct [6] Vara Prasad MSV, Krishna Murthy K, Kranthi K, QPSK UWB Based Modulator For Reusable Simulink Modeled PON, IJECET ( ), Sep. Oct., 2013; Vol 4, Issue 5.PP [7] M.S.V. Vara Prasad, T.Sireesha, K. Krishna Murthy A. NUMERICAL SIMULATION OF OPTICAL RECEIVER PERFORMANCE OF WDM SIGNALS IN A PON Recent Trends in Electronics and Communication Sytsems (2014) Vol. 1, Issue Stm Journals. [8] Yafeng, Z., Zhengxin, M., Zhigang, C.A. Novel Carrier Recovery Method for Cpfsk Demodulation. IEEE Article, 2000, [9] Chi-H Siao Yih, E-Geraniotis, Adaptive Modulation, Power Allocation And Control For Ofdm Wireless Networks, Pimrc 2000 Vol.2, PP , 2000 [10] M.R.Souryal, R.L.Pickholtz, Adaptive Modulation with Imperfect Channel Information in Ofdm, Icc 2001, Vol.6, PP , [11] Simon, M.K. And Divsilar, D., Maximum Likelihood Block Detection of Non-Coherent Continuous Phasemodulation, IEEE Transactions on Communications, Jan., [12] Yu, Z., Zhao, M., Liu, L., Qiu,P A Timing Recovery Scheme for Pulse Shaped 4-Cpfsk With h0.25. In 10 th Asia-Pacific Conf. On Commun., September 2004, IEEE, PP editor@iaeme.com

6 M.S.V. Vara Prasad, Ch. Nagabhushanam and K. Krishna Murthy [13] Yu, Z., Zhao, M., Liu, L. Joint Frequency And Timing Recovery For Pulse Shaped4-Cpfsk With h = IEEE Article, April [14] Yafeng, Z., Zhigang, C., Zhengxin, M.Modulation Index Estimation for Cpfsk Signals and Its Application To Timing Synchronization in 10 th Asia-Pacific Conf. On Commun., September 2004 IEEE, PP [15] Vara Prasad M.S.V, Kiranmayi.S, Krishna Murthy, K. Performance of Optical Filter over M-Ary Adaptive Modulation Scheme. IJEECT ( ) May August, 2013, Vol-9. [16] Fonseka, J. Base Band Pulse Shapping To Reduce Inter Symbol Interference in Narrowband M-Ary Cpfsk Signaling. IEEE Article, 1991, Ch /91/0000/0393. [17] VaraPrasad.M.S.V, Krishna Murthy.K,Sireesha.T, Optical Receiver Performance of a Wdm Pon Using Pso For The Decision Threshold Control Method. IJEA ( ). 2013; Vol.-2. [18] M.S.V. Vara Prasad, K. Krishna Murthy Performance Analysis of Signal Reconstruction Rate In The Narrow Tunable Optical Filter IJECERD Volume 4, Number 2, April-June (2014), PP [19] Satish Kumar Garg, Arun Gaur and S. P. Gupta. Information Security Using Modulation Technique. International Journal of Electronics and Communication Engineering & Technology (IJECET), 7 (1), 2016, pp [20] Yashwant Kumar and Ramanpreet Kaur. CRLH Performance Parameter Calculation for Wavelet Based Hadamard Coded Modulation. International Journal of Electronics and Communication Engineering & Technology (IJECET), 6 (1 2), 2015, pp editor@iaeme.com

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