![ As we know,
L=2n, then Step size Q = (Fmax – Fmin) / L
Interval i is mapped to the middle value. We will store or
send only index value of quantized value.
An Index value of quantized value Qi (F) = [F – Fmin / Q]
Quantized value Q (F) = Qi (F) Q + Q / 2 + Fmin
But there are some problems raised in uniform
quantization those are
Only optimal for uniformly distributed signal.
Real audio signals are more concentrated near zeros.
The Human ear is more sensitive to quantization errors at
small values.
The solution for this problem is using Non- uniform
quantization. In this Process quantization interval is
smaller near zero.](https://image.slidesharecdn.com/170050111022dcom-201012112836/85/Pulse-code-modulation-PCM-12-320.jpg)
Pulse code modulation (PCM)
- 1. Prepared BY :- Mahima Shastri Enroll no. :- 170050111022 Branch :- EC (Sem 6) Sub :- DCOM Topic :- Pulse Code Modulation (PCM)
- 2. Pulse code modulation is a method that is used to convert an analog signal into a digital signal, so that modified analog signal can be transmitted through the digital communication network. PCM is in binary form ,so there will be only two possible states high and low(0 and 1). We can also get back our analog signal by demodulation. The Pulse Code Modulation process is done in three steps Sampling, Quantization, and Coding. There are two specific types of pulse code modulations such as differential pulse code modulation(DPCM) and adaptive differential pulse code modulation(ADPCM)
- 3. Here is a block diagram of the steps which are included in PCM.
- 4. To get a pulse code modulated waveform from an analog waveform at the transmitter end (source) of a communications circuit, the amplitude of the analog signal samples at regular time intervals. The sampling rate or number of samples per second is several times the maximum frequency. The message signal converted into binary form will be usually in the number of levels which is always to a power of 2. This process is called quantization. At the receiver end, a pulse code demodulator decodes the binary signal back into pulses with same quantum levels as those in the modulator. By further processes we can restore the original analog waveform.
- 6. Sampling is a process of measuring the amplitude of a continuous-time signal at discrete instants, converts the continuous signal into a discrete signal. For example, conversion of a sound wave to a sequence of samples. The Sample is a value or set of values at a point in time or it can be spaced. Sampler extract samples of a continuous signal, it is a subsystem ideal sampler produces samples which are equivalent to the instantaneous value of the continuous signal at the specified various points. The Sampling process generates flat- top Pulse Amplitude Modulated (PAM) signal.
- 8. Sampling frequency, Fs is the number of average samples per second also known as Sampling rate. According to the Nyquist Theorem sampling rate should be at least 2 times the upper cutoff frequency. Sampling frequency, Fs>=2*fmax to avoid Aliasing Effect. If the sampling frequency is very higher than the Nyquist rate it become Oversampling, theoretically a bandwidth limited signal can be reconstructed if sampled at above the Nyquist rate. If the sampling frequency is less than the Nyquist rate it will become Undersampling. Basically two types of techniques are used for the sampling process. Those are 1. Natural Sampling and 2. Flat- top Sampling.
- 9. In quantization, an analog sample with an amplitude that converted into a digital sample with an amplitude that takes one of a specific defined set of quantization values. Quantization is done by dividing the range of possible values of the analog samples into some different levels, and assigning the center value of each level to any sample in quantization interval. Quantization approximates the analog sample values with the nearest quantization values. So almost all the quantized samples will differ from the original samples by a small amount. That amount is called as quantization error.
- 10. The result of this quantization error is we will hear hissing noise when play a random signal. Converting analog samples into binary numbers that is 0 and 1. In most of the cases we will use uniform quantizers. Uniform quantization is applicable when the sample values are in a finite range (Fmin, Fmax). The total data range is divided into 2n levels, let it be L intervals. They will have an equal length Q. Q is known as Quantization interval or quantization step size. In uniform quantization there will be no quantization error.
- 12. As we know, L=2n, then Step size Q = (Fmax – Fmin) / L Interval i is mapped to the middle value. We will store or send only index value of quantized value. An Index value of quantized value Qi (F) = [F – Fmin / Q] Quantized value Q (F) = Qi (F) Q + Q / 2 + Fmin But there are some problems raised in uniform quantization those are Only optimal for uniformly distributed signal. Real audio signals are more concentrated near zeros. The Human ear is more sensitive to quantization errors at small values. The solution for this problem is using Non- uniform quantization. In this Process quantization interval is smaller near zero.
- 13. The encoder encodes the quantized samples. Each quantized sample is encoded into an 8-bit code word by using A-law in the encoding process. Bit 1 is the most significant bit (MSB), it represents the polarity of the sample. “1” represents positive polarity and “0” represents negative polarity. Bit 2,3 and 4 will defines the location of sample value. These three bits together form linear curve for low level negative or positive samples. Bit 5,6,7 and 8 are the least significant bits (LSB) it represents one of the segments quantized value. Each segment is divided into 16 quantum levels.
- 14. PCM is two types Differential Pulse Code Modulation (DPCM) and Adaptive Differential Pulse Code Modulation (ADPCM). In DPCM only the difference between a sample and the previous value is encoded. The difference will be much smaller than the total sample value so we need some bits for getting same accuracy as in ordinary PCM. So that the required bit rate will also reduce. For example, in 5 bit code 1 bit is for polarity and the remaining 4 bits for 16 quantum levels.
- 15. ADPCM is achieved by adapting the quantizing levels to analog signal characteristics. We can estimate the values with preceding sample values. Error estimation is done as same as in DPCM. In 32Kbps ADPCM method difference between predicted value and sample value is coded with 4 bits, so that we’ll get 15 quantum levels. In this method data rate is half of the conventional PCM.
- 16. Pulse Code Demodulation will be doing the same modulation process in reverse. Demodulation starts with decoding process, during transmission the PCM signal will effected by the noise interference. So, before the PCM signal sends into the PCM demodulator, we have to recover the signal into the original level for that we are using a comparator. The PCM signal is a series pulse wave signal, but for demodulation we need wave to be parallel.
- 17. By using a serial to parallel converter the series pulse wave signal will be converted into a parallel digital signal. After that the signal will pass through n-bits decoder, it should be a Digital to Analog converter. Decoder recovers the original quantization values of the digital signal. This quantization value also includes a lot of high frequency harmonics with original audio signals. For avoiding unnecessary signals we utilize a low-pass filter at the final part.
- 18. Analog signal can be transmitted over a high- speed digital communication system. Probability of occurring error will reduce by the use of appropriate coding methods. PCM is used in Telkom system, digital audio recording, digitized video special effects, digital video, voice mail. PCM is also used in Radio control units as transmitter and also receiver for remote controlled cars, boats, planes. The PCM signal is more resistant to interference than normal signal.