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# Important Short Questions and Answers: Sampling & Quantization

Digital Communication - Sampling & Quantization - Important Short Questions and Answers: Sampling & Quantization

SAMPLING &QUANTIZATION

1. Draw the typical digital communication system 2. How can BER of an system be improved.

·              Increasing the transmitted signal power

·              Employing modulation and demodulation technique

·              Employing suitable coding and decoding methods

·              Reducing noise interference with help of improved filtering

3. Give an example for time limited and time unlimited signals

Time limited- rectangular pulse, triangular pulse

Time unlimited signals - sinusoidal signal,exponential signal and step signal.

Speech, video and other data can be transmitted simultaneously Wide dynamic range is possible since data is digital

digital communication required synchronization

data rate are very high

5. Which parameter is called figure of merit of a digital communication system and why?

The ration Eb/No or bit energy to noise power spectral density is called figure of merit of a digital communication system.

6. What is meant by distortion less transmission?

For distortion less transmission, the transfer function of the system if given as, H(w)=Ke-jwto

K- Constant magnitude response

The transfer function impose two requirements on the system

1. The system response must have constant magnitude response

2. The system phase shift response must be linear with frequency

7. Why prefilterring done before sampling

The signal must be limited to some highest frequency W Hz before sampling.

Then the signal is sampled at the frequency of fs=2W of higher. Hence the single should be prefiltered at higher that W Hz.If the signal is not prefiltered, then frequency component higher that W Hz will generate aliasing in the sampled signal spectrum.

8. Define quantization noise power

Quantisation noise power is the noise power due to quantisation noise. Let the quantization noise has the pdf of f€(Є).Then Quantisation noise power is given as, E[Є]2 = Є2 f(Є) d Є.

9. State sampling theorem.

A band limited signal of finite energy, which has no frequency components higher than W Hz, may be completely recovered from the knowledge of its samples taken at the rate of 2W samples per second.

10. What is quantization error

Because of quantization inherent error are introduces in the signal. The error is called Quantization error Є=xq(nTs)-x(nTs)

xq(nTs)- quantis ed value of the signal

x(nTs)- value of te sample before quantization

11. Compare uniform and non uniform quantization

Uniform Quantization

1. The quantization step size remains same throughout the dynamic range of the signal

2. SNR ratio varies with the input signal amplitude

Non-uniform Quantization

1. The quantization step size varies with the amplitude of the input signal.

2. SNR ratio can be maintained constant 12. What is meant by quantization.

The conversion of analog sample of the signal into digital form is called quantizing process

13. Differentiate the principle of temporal waveform coding and model based coding

TEMPORAL WAVEFORM CODING

The signal which varying with time can be digitized by periodic time sampling and amplitude quantization. This process is called temporal waveform coding .DM,ADM,DPCM are example of temporal waveform coding

MODEL BASED CODING

The signal is characterised in various parameter. This parameter represent the model of the signal.LPC is an example model based coding.

14. What is meant by aliasing effect?

Aliasing effect takes place when sampling frequency is less than Nyquist rate.Under such condition, the spectrum of the sampled signal overlaps with itself.Hence higher frequencies take the form of lower frequencies. This interference of the frequency components is called aliasing effects.

15.      What is the effects of aliasing? How it is reduced?

(i)          Since high and low frequencies interfere with each other,distortion is generated.

(ii)       The data is lost and it can not be recovered.

Aliasing can be avoided by two methods:

(i) Sampling rate fs ≥ 2W samples/sec. Where W---> Max.frequency present in the signal

(ii)Strictly bandlimit the signal to „W‟Hz.

16. What is the function of Low pass filter on sampling?

A low pass filter basically a reconstruction of filter.This filter should pass all the frequencies between(-W,W), Since original signal was having maximum frequency of „W‟Hz.Therefore cut-off frequency of this low pass reconstruction filter will be „W‟Hz.

17. Define Non-uniform quantization.

In non-uniform quantization, the step size is not fixed. It varies according to certain level of input signal amplitude. Step size is small at low input signal levels and the step size is higher at high input levels. Hence signal to noise power ratio remains almost same throughout the input signal.

18. What is meant by compander?

The non-uniform quantization(variable stepsize „∂‟)becomes very difficult to implement.

Therefore the signal is amplified at low signal levels and attenuated high signal levels.After this process,uniform quantization is used.This is equivalent to more stepsize at low signal levels and small step size at high signal levels.At the receiver a reverse process is done.That is the signal is attenuated at low signal levels and amplified at high signal levels to get original signal.Thus the compressionbof signal at transmitter and expansion at receiver is called combinely as Companding.

IMPORTANT TERMS

Quantization:

The conversion of analog sample of the signal into digital form is called quantizing process.

Aliasing effect:

Aliasing effect takes place when sampling frequency is less than Nyquist rate.Under such condition, the spectrum of the sampled signal overlaps with itself.Hence higher frequencies take the form of lower frequencies. This interference of the frequency components is called aliasing effects.

Sampling theorem:

A band limited signal of finite energy, which has no frequency components higher than W Hz, may be completely recovered from the knowledge of its samples taken at the rate of 2W samples per second.

Quantization error:

Because of quantization inherent error are introduces in the signal. The error is called Quantization error Є=xq(nTs)-x(nTs)

xq(nTs)- quantis ed value of the signal x(nTs)- value of te sample before quantization

Non-uniform quantization:

In non-uniform quantization, the step size is not fixed. It varies according to certain level of input signal amplitude. Step size is small at low input signal levels and the step size is higher at high input levels. Hence signal to noise power ratio remains almost same throughout the input signal.

Compander:

The non-uniform quantization(variable stepsize „∂‟)becomes very difficult to implement.

Therefore the signal is amplified at low signal levels and attenuated high signal levels.After this process,uniform quantization is used.This is equivalent to more stepsize at low signal levels and small step size at high signal levels.At the receiver a reverse process is done.That is the signal is attenuated at low signal levels and amplified at high signal levels to get original signal.Thus the compressionbof signal at transmitter and expansion at receiver is called combinely as Companding.

Quantization noise power:

Quantisation noise power is the noise power due to quantisation noise. Let the quantization noise has the pdf of f€(Є).Then Quantisation noise power is given as, E[Є]2 = Є2 f(Є) d Є.

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Digital Communication : Sampling & Quantization : Important Short Questions and Answers: Sampling & Quantization |