1. Computer Communication & Networks
Lecture # 04
Physical Layer: Signals & Digital Transmission
Nadeem Majeed Choudhary

2. Physical Layer Topics to Cover
Signals
Digital Transmission
Analog Transmission
Multiplexing
Transmission Media

3. Analog & Digital Data
Data can be analog or digital. The term analog data refers to information that is continuous; digital data refers to information that has discrete states. Analog data take on continuous values. Digital data take on discrete values.

4. Note
To be transmitted, data must be transformed to electromagnetic signals.

5. Note
Signals can be analog or digital. Analog signals can have an infinite number of values in a range; digital signals can have only a limited number of values.

6. Analog Vs Digital

7. Analog Signals

8. Sine Wave

9. Cont’ Three parameters to describe a sine wave Peak amplitude
Frequency and time period
Phase

10. The bandwidth of a composite signal is the difference between the
Note
The bandwidth of a composite signal is the difference between the
highest and the lowest frequencies contained in that signal.

11. Bandwidth

12. Digital Signals

13. Digital Signals
In addition to being represented by an analog signal, information can also be represented by a digital signal. For example, a 1 can be encoded as a positive voltage and a 0 as zero voltage. A digital signal can have more than two levels. In this case, we can send more than 1 bit for each level.

14. Digital Signal

15. Bit Rate & Bit Interval (contd.)

16. Bit Interval and Bit Rate
Example
A digital signal has a bit rate of 2000 bps. What is the duration of each bit (bit interval)
Solution
The bit interval is the inverse of the bit rate.
Bit interval = 1/ 2000 s = s = x 106 ms = 500 ms

17. The bit rate and the bandwidth are proportional to each other.
Note
The bit rate and the bandwidth are proportional to each other.

18. Analog Vs Digital

19. Analog versus digital signals

20. Low Pass & Band Pass

21. Data Rate Limits

22. Data Rate Limits
A very important consideration in data communications is how fast we can send data, in bits per second, over a channel. Data rate depends on three factors:
1. The bandwidth available
2. The level of the signals we use
3. The quality of the channel (the level of noise)

23. Noiseless Channel: Nyquist Bit Rate
Defines theoretical maximum bit rate for Noiseless Channel:
Bit Rate=2 X Bandwidth X log2L

24. Example
Consider a noiseless channel with a bandwidth of 3000 Hz transmitting a signal with two signal levels. The maximum bit rate can be calculated as
Bit Rate = 2  3000  log2 2 = 6000 bps

25. Example 8
Consider the same noiseless channel, transmitting a signal with four signal levels (for each level, we send two bits). The maximum bit rate can be calculated as:
Bit Rate = 2 x 3000 x log2 4 = 12,000 bps

26. Note
Increasing the levels of a signal may reduce the reliability of the system.

27. Noisy Channel: Shannon Capacity
Defines theoretical maximum bit rate for Noisy Channel:
Capacity=Bandwidth X log2(1+SNR)

28. C = B log2 (1 + SNR) = B log2 (1 + 0) = B log2 (1) = B  0 = 0
Example
Consider an extremely noisy channel in which the value of the signal-to-noise ratio is almost zero. In other words, the noise is so strong that the signal is faint. For this channel the capacity is calculated as
C = B log2 (1 + SNR) = B log2 (1 + 0) = B log2 (1) = B  0 = 0

29. C = B log2 (1 + SNR) = 3000 log2 (1 + 3162) = 3000 log2 (3163)
Example
We can calculate the theoretical highest bit rate of a regular telephone line. A telephone line normally has a bandwidth of The signal-to-noise ratio is usually For this channel the capacity is calculated as
C = B log2 (1 + SNR) = 3000 log2 ( ) = 3000 log2 (3163)
C = 3000  = 34,860 bps

30. Example
We have a channel with a 1 MHz bandwidth. The SNR for this channel is 63; what is the appropriate bit rate and signal level?
Solution
First, we use the Shannon formula to find our upper limit.
C = B log2 (1 + SNR) = 106 log2 (1 + 63) = 106 log2 (64) = 6 Mbps
Then we use the Nyquist formula to find the
number of signal levels.
6 Mbps = 2  1 MHz  log2 L  L = 8

31. Note
The Shannon capacity gives us the upper limit; the Nyquist formula tells us how many signal levels we need.

32. Transmission Impairments

33. Transmission Impairments
Signals travel through transmission media, which are not perfect. The imperfection causes signal impairment. This means that the signal at the beginning of the medium is not the same as the signal at the end of the medium. What is sent is not what is received. Three causes of impairment are attenuation, distortion, and noise.

34. Transmission Impairments

35. Decibel Used to signal gained or lost strength
dB = 10 log P2/P1 (Power)
dB Voltage = 20 log (V1/V2)
dB Current = 20 log (I1/I2)
The dB is not an absolute quantity, it is always a RATIO of two quantities.  The unit can be used to express power gain (P2>P1), or power loss (P2<P1) -- in the latter case the result will be a negative number.
The decibel (dB) is a logarithmic unit that indicates the ratio of a physical quantity (usually power or intensity) relative to a specified or implied reference level. A ratio in decibels is ten times the logarithm to base 10 of the ratio of two power quantities
The decibel (dB) is a very commonly used and often misunderstood unit of measurement.  The dB is a logarithmic unit expressing the RATIO of two powers.  It is defined as:  
Number of dB = 10 log (P2/P1). The dB is not an absolute quantity, it is always a RATIO of two quantities.  The unit can be used to express power gain (P2>P1), or power loss (P2<P1) -- in the latter case the result will be a negative number.
The decibel  actually comes from a logarithmic unit of measurement called a "Bel", named after Alexander Graham Bell.  One Bel is defined as a power ratio of ten (or ten times the power).  It was originally used to measure acoustic power (sound)  ratios in telephony.  The Bel is a rather large unit, so the decibel (dB), which is 1/10 of a bel, is more commonly used.
Although the dB is defined with respect to power, it has become common practice to also use it to express voltage or current ratios, in which case it is defined as:  
 dB Voltage = 20 log (V1/V2),  or  dB Current = 20 log (I1/I2).

36. Example
Suppose a signal travels through transmission medium and its power is reduced to one half…. Calculate attenuation loss?

37. Signal Distortion
attenuation
distortion
noise

38. Performance
One important issue in networking is the performance of the network—how good is it?

39. Performance Bandwidth Throughput Latency (Delay)
Bandwidth-Delay Product

40. Throughput

41. Latency Latency = propagation time + transmission time queuing time
processing time

42. Propagation Time
In computer networks, propagation delay is the amount of time it takes for the head of the signal to travel from the sender to the receiver. It can be computed as the ratio between the link length and the propagation speed over the specific medium.
Propagation delay is equal to d / s where d is the distance and s is the wave propagation speed. In wireless communication, s=c, i.e. the speed of light. In copper wire, the speed s generally ranges from .59c to .77c

43. Note
The bandwidth-delay product defines the number of bits that can fill the link.
In data communications, bandwidth-delay product refers to the product of a data link's capacity (in bits per second) and its end-to-end delay (in seconds). The result, an amount of data measured in bits (or bytes), is equivalent to the maximum amount of data on the network circuit at any given time, i.e. data that has been transmitted but not yet received. Sometimes it is calculated as the data link's capacity multiplied by its round trip time

44. Physical Layer Topics to Cover
Signals
Digital Transmission
Analog Transmission
Multiplexing
Transmission Media

45. Analog To Digital Conversion

46. Sampling Pulse Code Modulation Sampling Rate: Nyquist Theorem

47. PCM

48. Quantization & Encoding Samples

49. According to the Nyquist theorem, the sampling rate must be
Note
According to the Nyquist theorem, the sampling rate must be
at least 2 times the highest frequency contained in the signal.