In this slide we discuss about what is Digital Transmission and How how convert Analog signal to Digital Signals (Analog to Digital Conversion)...............
2. Digital Transmission:
• Data or information can be stored in two ways, analog and
digital. For a computer to use the data, it must be in discrete
digital form. Similar to data, signals can also be in analog and
digital form. To transmit data digitally, it needs to be first
converted to digital form.
• A computer network is designed to send information from one
point to another. This information needs to be converted to
either a digital signal or an analog signal for transmission.
3. Analog-to-Digital Conversion:
● Microphones create analog voice and camera creates analog videos,
which are treated is analog data. To transmit this analog data over
digital signals, we need analog to digital conversion.
● Analog data is a continuous stream of data in the wave form whereas
digital data is discrete.
● To convert analog wave into digital data we describe two techniques,
pulse code modulation(PCM) and delta modulation.
4. Pulse code modulation (PCM):
● The most common technique to change an analog signal
to digital data (digitization) is called pulse code
modulation (PCM).
It involves three steps:
● Sampling
● Quantization
● Encoding
5. Sampling:
● Sampling is defined as, “The process of measuring the instantaneous values
of continuous-time signal in a discrete form.”
● Sample is a value or set of values at a point in time and/or space.
● The analog signal is sampled every T interval. Most important factor in
sampling is the rate at which analog signal is sampled. According to Nyquist
Theorem, the sampling rate must be at least two times of the highest
frequency of the signal.
6. Sampling:
● The analog signal is sampled every Ts s, where Ts is the sample
interval or period. The inverse of the sampling interval is called the
sampling rate or sampling frequency and denoted by is, where
is = IITs'
● There are three sampling methods:
1. Ideal sampling
2. Natural sampling
3. flat-top sampling
7. Ideal Sampling (Impulse Sampling):
● Ideal Sampling is also known as Instantaneous sampling or
Impulse Sampling. ... In this sampling technique
the sampling function is a train of impulses and the principle used is
known as multiplication principle. Here, Figure (a), represent message
signal or input signal or signal to be sampled
● In ideal sampling, pulses from the analog signal are sampled. This is
an ideal sampling method and cannot be easily implemented.
9. Natural sampling:
● In natural sampling, a high-speed switch is turned on for only the small period
of time when the sampling occurs. The result is a sequence of samples that
retains the shape of the analog signal.
10. Flat top sampling:
● During transmission, noise is introduced at top of the transmission pulse
which can be easily removed if the pulse is in the form of flat top. Here, the
top of the samples are flat i.e. they have constant amplitude. Hence, it is
called as flat top sampling or practical sampling. Flat top sampling makes
use of sample and hold circuit.
11.
12. Nyquist sampling rate for low-pass and bandpass
signals:
● we can sample a signal only if the signal is band-limited.
● If the analog signal is low-pass, the bandwidth and the
highest frequency are the same value.
● If the analog signal is bandpass, the bandwidth value is
lower than the value of the maximum frequency.
13. Quantization:
● It is a process to converting infinite value signal into a finite value
level.
● Quantization is the process of converting the sampled continuous
Valued signals into discrete-valued data.
● The number of possible states that the converter can output is:
● N=2n where n is the number of bits in the AD converter
● Example: For a 3 bit A/D converter, N=23=8.
● Analog quantization size:
Q=(V max -V min)/N = (10V – 0V)/8 = 1.25V
14. Actual Amplitude:
● In a PCM stream, the amplitude of the analog signal is sampled regularly at
uniform intervals, and each sample is quantized to the nearest value within a
range of digital steps.
15. Quantization Levels:
● Quantization is representing the sampled values of the amplitude by a
finite set of levels, which means converting a continuous-amplitude
sample into a discrete-time signal. ... The discrete amplitudes of
the quantized output are called as representation levels or
reconstruction levels.
● The choice of L, the number of levels, depends on the range of the
amplitudes of the analog signal and how accurately we need to recover
the signal. If the amplitude of a signal fluctuates between two values
only, we need only two levels; if the signal, like voice, has many amplitude
values, we need more quantization levels. In audio digitizing, L is normally
chosen to be 256; in video it is normally thousands. Choosing lower values of L
increases the quantization error if there is a lot of fluctuation in the signal.
16. Encoding:
● Assigning a digital word or number to each state and matching it to the input
signal.
● The last step in PCM is encoding. After each sample is quantized and the
number of bits per sample is decided, each sample can be changed to an llb-
bit code word. A quantization code of 2 is encoded as 010; 5 is encoded as
101; and so on. Note that the number of bits for each sample is determined
from the number of quantization levels. If the number of quantization levels is
L, the number of bits is llb =log2 L.
17. Step 1(Encoding):
● :Quantizing Example: You have 0-10V signals. Separate them into a set of
discrete states with 1.25V increments. (How did we get 1.25V? (Discussed in
previous slide)
● Output States Discrete Voltage Ranges (V) 0 0.00-1.25 1 1.25-2.50 2 2.50-
3.75 3 3.75-5.00 4 5.00-6.25 5 6.25-7.50 6 7.50-8.75 7 8.75-10.0
● See next slide for this example
19. Step 2 (Encoding):
● Encoding • Here we assign the digital value (binary number) to each
state for the computer to read.
Output States Output Binary Equivalent
0 000
1 001
2 010
3 011
4 100
5 101
6 110
7 111