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Dr. Uri Mahlab

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Dr. Uri Mahlab

## Dr. Uri Mahlab

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1. DIGITAL CARRIER MODULATION SCHEMES Dr.Uri Mahlab 1 Dr. Uri Mahlab

2. INTRODUCTION In order to transmit digital information over * bandpass channels, we have to transfer the information to a carrier wave of .appropriate frequency We will study some of the most commonly * used digital modulation techniques wherein the digital information modifies the amplitude the phase, or the frequency of the carrier in .discrete steps 2 Dr. Uri Mahlab

3. The modulation waveforms fortransmitting :binary information over bandpass channels ASK FSK PSK DSB 3 Dr. Uri Mahlab

4. OPTIMUM RECEIVER FOR BINARY :DIGITAL MODULATION SCHEMS The function of a receiver in a binary communication system is to distinguish between two transmitted signals S1(t) and S2(t) in the presence of noise The performance of the receiver is usually measured in terms of the probability of error and the receiver is said to be optimum if it yields the minimum probability of error In this section, we will derive the structure of an optimum receiver that can be used for demodulating binary ASK,PSK,and FSK signals 4 Dr. Uri Mahlab

5. Description of binary ASK,PSK, and : FSK schemes -Bandpass binary data transmission system Transmit carrier Local carrier Noise n(t) Clock pulses Clock pulses + Input Modulator Channel Hc(f) Demodulator (receiver) ּ+ Binary data + V(t) Z(t) {bk} Binary data output {bk} 5 Dr. Uri Mahlab

6. :ExplanationThe input of the system is a binary bit sequence {bk} with a .bit rate r b and bit duration Tb The output of the modulator during the Kth bit interval .depends on the Kth input bit bk The modulator output Z(t) during the Kth bit interval is a shifted version of one of two basic waveforms S1(t) or S2(t) and :Z(t) is a random process defined by 6 Dr. Uri Mahlab

7. The waveforms S1(t) and S2(t) have a duration * of Tb and have finite energy,that is, S1(t) and S2(t) =0 if and Energy :Term 7 Dr. Uri Mahlab

8. :The received signal + noise 8 Dr. Uri Mahlab

9. Choice of signaling waveforms for various types of digital* modulation schemes S1(t),S2(t)=0 for .The frequency of the carrier fc is assumed to be a multiple of rb Type of modulation ASK PSK FSK 0 9 Dr. Uri Mahlab

10. :Receiver structure V0(t) Threshold device or A/D converter Filter Hr(f) output Sample every Tb seconds 10 Dr. Uri Mahlab

11. :{Probability of Error-Pe*} The measure of performance used for comparing !!!digital modulation schemes is the probability of error The receiver makes errors in the decoding process !!! due to the noise present at its input The receiver parameters as H(f) and threshold setting are !!!chosen to minimize the probability of error 11 Dr. Uri Mahlab

12. :The output of the filter at t=kTb can be written as * 12 Dr. Uri Mahlab

13. :The signal component in the output at t=kTb h( ) is the impulse response of the receiver filter ISI=0 13 Dr. Uri Mahlab

14. Substituting Z(t) from equation 1 and making change of the variable, the signal component :will look like that 14 Dr. Uri Mahlab

15. The noise component n0(kTb) is given by .The output noise n0(t) is a stationary zero mean Gaussian random process The variance of n0(t) is The probability density function of n0(t) is 15 Dr. Uri Mahlab

16. The probability that the kth bit is incorrectly decoded is given by .2 16 Dr. Uri Mahlab

17. The conditional pdf of V0 given bk = 0 is given by .3 :It is similarly when bk is 1 17 Dr. Uri Mahlab

18. Combining equation 2 and 3 , we obtain an expression for the probability of error- Pe as .4 18 Dr. Uri Mahlab

19. Conditional pdf of V0 given bk The optimum value of the threshold T0* is 19 Dr. Uri Mahlab

20. Substituting the value of T*0 for T0 in equation 4 we can rewrite the expression for the probability of error as 20 Dr. Uri Mahlab

21. The optimum filter is the filter that maximizes the ratio or the square of the ratio (maximizing eliminates the requirement S01<S02) 21 Dr. Uri Mahlab

22. Transfer Function of the Optimum Filter The probability of error is minimized by an appropriate choice of h(t) which maximizes Where And 22 Dr. Uri Mahlab

23. If we let P(t) =S2(t)-S1(t), then the numerator of the :quantity to be maximized is Since P(t)=0 for t<0 and h( )=0 for <0 :the Fourier transform of P0 is 23 Dr. Uri Mahlab

24. :Hence can be written as (*) We can maximize by applying Schwarz’s* :inequality which has the form (**) 24 Dr. Uri Mahlab

25. Applying Schwarz’s inequality to Equation(**) with- and We see that H(f), which maximizes ,is given by- (***) !!! Where K is an arbitrary constant 25 Dr. Uri Mahlab

26. Substituting equation (***) in(*) , we obtain- :the maximum value of as :And the minimum probability of error is given by- 26 Dr. Uri Mahlab

27. Exrecise - 1 Matched Filter Receiver

28. Exrecise - 1 Matched Filter Receiver If the channel noise is white, that is, Gn(f)= /2 ,then the transfer - :function of the optimum receiver is given by From Equation (***) with the arbitrary constant K set equal to /2- :The impulse response of the optimum filter is 27 Dr. Uri Mahlab

29. Recognizing the fact that the inverse Fourier of P*(f) is P(-t) and that exp(-2 jfTb) represent a delay of Tb we obtain h(t) as Since p(t)=S2(t)-S1(t) , we have The impulse response h(t) is matched to the signal S1(t) and S2(t) and for this reason the filter is called MATCHED FILTER 28 Dr. Uri Mahlab

30. Impulse response of the Matched Filter S2(t) 1 t 0 2 \Tb (a) S1(t) 0 2 \Tb t 1- (b) 2 P(t)=S2(t)-S1(t) 2 \Tb 0 t Tb 2 (c) (P(-t t (d) Tb- 0 2 h(Tb-t)=p(t) h(t)=p(Tb-t) 2 \Tb 0 t 29 (e) Tb Dr. Uri Mahlab

31. Exrecise - 2 Correlation Receiver

32. Exrecise - 2 Correlation Receiver The output of the receiver at t=Tb* Where V( ) is the noisy input to the receiver Substituting and noting that we can rewrite the preceding expression as (# #) 30 Dr. Uri Mahlab

33. Equation(# #) suggested that the optimum receiver can be implemented as shown in Figure 1 .This form of the receiver is called A Correlation Receiver integrator Figure 1 Threshold device (A\D) - + Sample every Tb seconds integrator 31 Dr. Uri Mahlab

34. In actual practice, the receiver shown in Figure 1 is actually .implemented as shown in Figure 2 In this implementation, the integrator has to be reset at the (end of each signaling interval in order to ovoid (I.S.I !!! Inter symbol interference :Integrate and dump correlation receiver White Gaussian noise Closed every Tb seconds (n(t Filter to limit noise power Threshold device (A/D) + + c R (Signal z(t High gain amplifier Figure 2 The bandwidth of the filter preceding the integrator is assumed to be wide enough to pass z(t) without distortion 32 Dr. Uri Mahlab

35. Exrecise - 3 PSK 27

36. Exrecise - 3 Example: A band pass data transmission scheme uses a PSK signaling scheme with The carrier amplitude at the receiver input is 1 mvolt and the psd of the A.W.G.N at input is watt/Hz. Assume that an ideal correlation receiver is used. Calculate the .average bit error rate of the receiver 33 Dr. Uri Mahlab

37. :Solution Data rate =5000 bit/sec Receiver impulse response Threshold setting is 0 and 34 Dr. Uri Mahlab

38. :Solution Continue =Probability of error = Pe From the table of Gaussian probabilities ,we get Pe 0.0008 and Average error rate (rb) pe /sec = 4 bits/sec 35 Dr. Uri Mahlab

39. Exrecise - 4 Binary ASK 27

40. Exrecise - 4 Binary ASK signaling schemes The binary ASK waveform can be described as Where and We can represent Z(t) as: 36 Dr. Uri Mahlab

41. Where D(t) is a lowpass pulse waveform consisting of .rectangular pulses :The model for D(t) is 37 Dr. Uri Mahlab

42. Exrecise - 5 Power Spectrum 27

43. Exrecise - 5 The power spectral density is given by The autocorrelation function and the power spectral density is given by 38 Dr. Uri Mahlab

44. The psd of Z(t) is given by 39 Dr. Uri Mahlab

45. If we use a pulse waveform D(t) in which the individual pulses g(t) have the shape 40 Dr. Uri Mahlab

46. Exrecise - 6 Coherent ASK 27

47. Exrecise - 6 Coherent ASK We start with The signal components of the receiver output at the :of a signaling interval are 41 Dr. Uri Mahlab

48. The optimum threshold setting in the receiver is The probability of error can be computed as 42 Dr. Uri Mahlab

49. The average signal power at the receiver input is given by We can express the probability of error in terms of the average signal power The probability of error is sometimes expressed in terms of the average signal energy per bit , as 43 Dr. Uri Mahlab