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Introduction to Data Communication Lecture o2 Advanced Computer Networks (ACN) 545

Mr. Thilak d e Silva. BSc . Eng., MSc , CEng , FIE(SL), FIET(UK), CITP(UK), MBCS(UK), MIEEE (USA). Introduction to Data Communication Lecture o2 Advanced Computer Networks (ACN) 545 . Today's Agenda. Analog and Digital Signals. Periodic and Non-periodic signals.

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Introduction to Data Communication Lecture o2 Advanced Computer Networks (ACN) 545

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  1. Mr. Thilakde Silva. BSc. Eng., MSc, CEng, FIE(SL), FIET(UK), CITP(UK), MBCS(UK), MIEEE (USA) Introduction to Data CommunicationLecture o2Advanced Computer Networks (ACN) 545 M.Sc. in IT - Year 1 Semester II - 2012

  2. Today's Agenda • Analog and Digital Signals. • Periodic and Non-periodic signals. • Time domain and Frequency domain representation. • Fourier Analysis • Nyquest theorem. M.Sc. in IT - Year 1 Semester II - 2012

  3. Session Outcomes • At the end of this session you will have a broad understanding of Analog and Digital signals, Fourier Analysis and Nyquest theorem. M.Sc. in IT - Year 1 Semester II - 2012

  4. Data and Signals • Data is in memory. • It is converted in to Signals When transmitting • Need a transmission media to transmit signals. • Signals can be divided as, • Analog Signals, Digital Signals • Periodic Signals, Non Periodic Signals M.Sc. in IT - Year 1 Semester II - 2012

  5. Analog Signals and Digital Signals • Analog signals are continuous and has infinitely many levels of intensity over a period of time. • Digital signals are discrete and has limited number of levels of intensity over a period of time. M.Sc. in IT - Year 1 Semester II - 2012

  6. Periodic and Non periodic Signals • Can be analog or digital. • Periodic signals – has a pattern which repeats over identical periods. (Cycle) • Practically we do not have periodic signals. • Non periodic signals – changes without exhibiting a pattern or cycle that repeats over time. Non Periodic analog signal Periodic analog signal M.Sc. in IT - Year 1 Semester II - 2012

  7. Periodic Analog Signal • Has 3 parameters, • Amplitude • Frequency • Phase

  8. Time domain and Frequency domin representation • Time Domain Representation shows changes in signal amplitude with respect to time • Frequency domain representation show the relationship between amplitude and frequency  M.Sc. in IT - Year 1 Semester II - 2012

  9. Composite signals • A composite signal is made of many sine waves. • Fourier showed that any composite signal is actually a combination of simple sine waves with different frequencies, amplitudes and phases. • These are known as harmonics M.Sc. in IT - Year 1 Semester II - 2012

  10. Composite signals A composite periodic Signal Source - http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image01617.jpg M.Sc. in IT - Year 1 Semester II - 2012

  11. Fourier Analysis • Use to transform a time domain signal in to frequency components. • Only applicable for periodic signals. • According to Fourier analysis any signal is composed with several frequencies called harmonics. M.Sc. in IT - Year 1 Semester II - 2012

  12. Fundamental and harmonics Fundamental frequency – f (first harmonic) Third harmonic – 3f Fifth harmonic – 5f … Source - http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image01814.jpg M.Sc. in IT - Year 1 Semester II - 2012

  13. Bandwidth • Range of frequencies / Difference between the highest and lowest frequencies Source - http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image02014.jpg M.Sc. in IT - Year 1 Semester II - 2012

  14. Signal strength • When adding two signals the strength of the resulting signal depends on the phase differences, amplitudes, frequencies etc. • Eg:- In phase (add voltages) Out phase (deduct voltages) M.Sc. in IT - Year 1 Semester II - 2012

  15. Bandwidth of a composite signal • A digital signal has infinite number of frequency components. (Bit rate)Speed = 1kb per second Bit Pattern = 101010 F=1/T F=1/2*10 F=5ooHz F=0.5Khz -3 T 2 ms Required Bandwidth (Fundamental frequency)= ½*Bit Rate M.Sc. in IT - Year 1 Semester II - 2012

  16. If the bit pattern changes, Bit rate = 1kb per second Bit Pattern = 11001100 T F=1/T F=1/4*10 F=25oHz F=0.25Khz 4 ms -3 Required Bandwidth = 0.25Khz M.Sc. in IT - Year 1 Semester II - 2012

  17. Regenerating the signal • At the receiving end the signal is regenerated by looking at the amplitude, • IF amplitude is high 1 is generated • IF amplitude is low 0 is generated • Therefore we must at least send the fundamental frequency. • That’s why we say that the bandwidth should be at least half of the bit rate. M.Sc. in IT - Year 1 Semester II - 2012

  18. Regenerating the signal - impacts • When frequency getting high the amplitude gets low. • Sending more and more harmonics makes the signal regeneration easy. • But this is expensive due to high bandwidth. • Deciding the number of harmonics we send should be done based on the characteristics of the media. M.Sc. in IT - Year 1 Semester II - 2012

  19. Fourier Analysis and Transform • Periodic Signal Fourier Analysis • Non Periodic Signal Fourier Transform A Discrete Frequency Spectrum A Continuous Frequency Spectrum M.Sc. in IT - Year 1 Semester II - 2012

  20. Digital signals • Can have two or more discrete level. • Bit Rate – number of bits sent per second. • Baud rate – signal changing rate per second • Required bandwidth depends on the baud rate. M.Sc. in IT - Year 1 Semester II - 2012

  21. Digital signal having two levels and four levels Two Levels One signal element represents one bit Therefore bit rate= baud rate Four Levels One signal representation has two bits Therefore bit rate= baud rate Source : http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image02214.jpg M.Sc. in IT - Year 1 Semester II - 2012

  22. Increasing Levels, • We can increase the Bit Rate without increasing the Bandwidth. • But, • The error probability is high, • Circuit component cost is high, • Effect of transmission impairments is high, • There for we do not use 4 levels practically. M.Sc. in IT - Year 1 Semester II - 2012

  23. Digital Impairments • Atténuation • Delay • Noise • Jitter M.Sc. in IT - Year 1 Semester II - 2012

  24. Nyquist Theorem BitRate = 2 x bandwidth x log2L • Assumptions • One signal element carry only one bit • No noise, attanuation etc in the transmission media • If there are noise and attanuation (Shannon Capacity) Capacity = bandwidth x log2(1 + SNR) M.Sc. in IT - Year 1 Semester II - 2012

  25. Number of Bits…? • If Capacity = 20 Kbp/s & • Bit Rate = 3 Kbp/s • Can represent maximum 6 bits per element. • 2 = 64 combinations of amplitude or phase differences. (64 QAM) 6 M.Sc. in IT - Year 1 Semester II - 2012

  26. References • Data Communications and Networking, Forouzan, Chapter 03, 4th Edition M.Sc. in IT - Year 1 Semester II - 2012

  27. Thank You… M.Sc. in IT - Year 1 Semester II - 2012

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