•A digital signal is superior to an analog signalbecause it is more robust to noise and can easilybe recovered, corrected and amplified.• For this reason, the tendency today is tochange an analog signal to digital data.•Generally used two techniques are :pulse code modulation anddelta modulation.
PCM PCM consists of three steps to digitize an analog signal: 1. Sampling 2. Quantization 3. Binary encoding Before we sample, we have to filter the signal to limit the maximum frequency of the signal as it affects the sampling rate. Filtering should ensure that we do not distort the signal, ie remove high frequency components that affect the signal shape.
SAMPLING Analog signal is sampled every TS secs. Ts is referred to as the sampling interval. fs = 1/Ts is called the sampling rate or sampling frequency. There are 3 sampling methods: Ideal - an impulse at each sampling instant Natural - a pulse of short width with varying amplitude Flattop - sample and hold, like natural but with single amplitude value
Quantization Quantization is the process of “rounding off” a sample according to some rule.
Nonuniform Quantizing Voice analog signals are more likely to have amplitude values near zero than at the extreme peak values allowed. For signals with nonuniform amplitude distribution, the granular quantizing noise will be a serious problem if the step size is not reduced for amplitude values near zero and increased for extremely large values. This is called nonuniform quantizing since a variable step size is used.
Encoding Encoding is the process of representing the sampled values as a binary number in the range 0 to n. The value of n is chosen as a power of 2, depending on the accuracy required. Increasing n reduces the step size between adjacent Quantization levels and hence reduces the Quantization noise. The down side of this is that the amount of digital data required to represent the analog signal increases.
Quantization Error and SNQR When a signal is quantized, we introduce an error - the coded signal is an approximation of the actual amplitude value. The difference between actual and coded value (midpoint) is referred to as the quantization error. Signals with lower amplitude values will suffer more from quantization error as the error range: /2, is fixed for all signal levels. Non linear quantization is used to alleviate this problem. Goal is to keep SNQR fixed for all sample values. Two approaches: The quantization levels follow a logarithmic curve. Smaller ’s at lower amplitudes and larger ’s at higher amplitudes. Companding: The sample values are compressed at the sender into logarithmic zones, and then expanded at the receiver. The zon
PCM DECODER To recover an analog signal from a digitized signal we follow the following steps: We use a hold circuit that holds the amplitude value of a pulse till the next pulse arrives. We pass this signal through a low pass filter with a cutoff frequency that is equal to the highest frequency in the pre-sampled signal.
Companding In telecommunication, signalprocessing, companding (occasionally called compansion) is a method of mitigating the detrimental effects of a channel with limited dynamic range. The name is a portmanteau of compressing and expanding
Speech Companding The human auditory system is believed to be a logarithmic process in which high amplitude sounds do not require the same resolution as low amplitude sounds. The human ear is more sensitive to quantization noise in small signals than large signals. A-law and µ-law coding apply a logarithmic quantization function to adjust the data resolution in proportion to the level of the input signal.
Differential Pulse Code Modulation(DPCM) quantises the difference between the original and the predicted signals, i.e. the difference between successive values. Leads to reduction in the number of bits used per sample over that used for PCM. Using DPCM can reduce the bit rate of voice transmission down to 48 kbps. DPCM can be described as a predictive coding scheme.
Adaptive Differential Pulse Code Modulation(ADPCM) ADPCM adapts the Quantization levels of the difference signal that is generated during the DPCM process. If the difference signal is low, ADPCM reduces the size of the Quantization levels. If the difference signal is high, ADPCM increases the size of the Quantization levels. The Quantization level is thus adapted to the size of the input difference signal, generating a uniform signal-to-noise ratio throughout the dynamic range of the difference signal.
Applications of PCM-TDM systems TDM and Codecs Digital Transmission Hierarchies Plesiochronous Digital Hierarchy (PDH)
Limitations of PCM systems Choosing a discrete value near the analog signal for each sample leads to quantization error. Between samples no measurement of the signal is made; the sampling theorem guarantees non-ambiguous representation and recovery of the signal only if it has no energy at frequency fs/2 or higher (one half the sampling frequency, known as the Nyquist frequency); higher frequencies will generally not be correctly represented or recovered. As samples are dependent on time, an accurate clock is required for accurate reproduction. If either the encoding or decoding clock is not stable, its frequency drift will directly affect the output quality of the device.