INTRODUCTION TO DIGITAL COMMUNICATION

1. INTRODUCTION TO DIGITAL COMMUNICATION Prepared by: Zainab Zakir (RA) Under the guidance of Sir Rizwan-ul-Hasan (Asst. Prof)

2. Topics Digital Signals Digital Communication Components Sampling and Quantization AWGN and Probability Density Function

3. Digital Signals • A digital signal is a physical signal that is a representation of a sequence of discrete values (a quantified discrete-time signal).

4. Digital Signals • The term digital signal can refer to • a continuous-time waveform signal used in any form of digital communication. • a pulse train signal that switches between a discrete number of voltage levels or levels of light intensity, also known as a a line coded signal, for example a signal found in digital electronics or in serial communications using digital baseband transmission in, or a pulse code modulation (PCM) representation of a digitized analog signal.

5. Digital Communication Components It is composed of five basic components. • The input block • The transmitter • Channel • Receiver • Output

22. Sampling

29. Over sampling • When the sampling rate is higher than, the space between sample spectrums gets wider • This is one way to eliminate aliasing. • Note that the filtering process using LPF becomes easier and there is no need for sharp edge filters.

30. Quantization • The samples from the analog signal are not yet in the digital form (bit stream) because these samples have infinite amplitudes. • To make the amplitudes have finite levels (i.e. belong to a finite range of amplitude levels), different amplitude levels are created known as the quantized level. • Each sample is going to be mapped into one of these levels (i.e. the nearest level for that sample). • More levels mean lower error of mapping known as the quantized error but at the expense of increasing BW.

31. Performance criteria For digital signals, probability of bit error( ) is the main performance criteria. Higher this error rate, lower the performance of such systems.

32. Probability and random signals • For random signal, we use the statistical and probabilistic methods to describe a signal since there is no definite expression for such random signals.

33. Probability - cont’d

35. Probability Density Function (PDF)

37. What does it mean?

38. AWGN

39. Normal or Gaussian PDF

40. Properties of AWGN The noise signal has low amplitudes with high probabilities and high amplitudes with low probability. So the noise signal is mostly low amplitude signals.

41. Power of AWGN

42. Power of AWGN – cont’d