Digital transmission & analog Digital to conversion
- 1. Digital Transmission & ‘Analog to digital conversion’ Date 21-10-2020
- 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.
- 8. Ideal Sampling (Impulse Sampling)
- 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.
- 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
- 18. 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
- 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
- 20. Regard: Muhammad Awais For any mistake please contact: chawais2001@gmail.com