(SEM VI) THEORY EXAMINATION 2022-23 DIGITAL COMMUNICATION

DIGITAL COMMUNICATION – KEC-601

Section-wise Important Questions & Ready Answers

SECTION A

(Attempt all questions – 2 marks each)

(a) Probability Problem (Dice Thrown Twice)

When two dice are thrown, the total number of possible outcomes is 36. The combinations whose sum is 7 are (1,6), (2,5), (3,4), (4,3), (5,2), and (6,1). Hence, the probability is

P=636=16P = \frac{6}{36} = \frac{1}{6}P=366​=61​ 

(b) Mean and Variance

The mean is the average value of a random variable and represents its central tendency.
The variance measures the spread of data around the mean and indicates how much the values deviate from the average.

(c) Block Diagram of Digital Communication System

A digital communication system consists of an information source, source encoder, channel encoder, digital modulator, channel, demodulator, channel decoder, source decoder, and destination.
(Neat block diagram must be drawn in exam.)

(d) Eye Diagram

An eye diagram is obtained by overlapping multiple bits of a digital signal. It helps in analyzing noise margin, timing jitter, distortion, and intersymbol interference (ISI).

(e) Advantages of PSK over ASK

PSK has better noise immunity compared to ASK because information is carried in phase rather than amplitude. PSK also provides better power efficiency and lower bit error rate.

(f) Bandwidth Comparison of ASK, PSK, and FSK

ASK and PSK require approximately the same bandwidth, while FSK requires larger bandwidth because different frequencies are used to represent binary data.

(g) PN Sequence

A PN (Pseudo-Noise) sequence is a deterministic sequence that appears random. It is widely used in spread spectrum systems for security and interference reduction.

(h) Disadvantages of Non-Coherent FSK

Non-coherent FSK has poor noise performance, requires higher bandwidth, and results in higher bit error rate compared to coherent detection.

(i) Mutual Information Symmetry

Mutual information is symmetric because the information shared between two random variables X and Y is the same whether measured as I(X;Y) or I(Y;X).

(j) Properties of Cyclic Codes

Cyclic codes are linear block codes with the property that a cyclic shift of a valid codeword is also a valid codeword. They have simple encoder and decoder implementation using shift registers.

SECTION B

(Attempt any three – 10 marks each)

2(a) Properties of a Random Variable

A random variable assigns numerical values to outcomes of a random experiment. It may be discrete or continuous. Its properties include probability distribution, mean, variance, and higher-order moments which describe its behavior statistically.

2(b) Gram-Schmidt Orthogonalization Scheme

The Gram-Schmidt process converts a set of linearly independent signals into an orthogonal set. This simplifies signal detection in digital communication systems and reduces interference between signals.

2(c) ASK Modulation and Demodulation

In Amplitude Shift Keying (ASK), the carrier amplitude is varied according to the digital data. During demodulation, an envelope detector or coherent detector is used to recover the original data.
(Block diagrams required in exam.)

2(d) DSSS with Block Diagram

Direct Sequence Spread Spectrum spreads the signal by multiplying it with a high-rate PN sequence. This increases bandwidth and improves resistance to noise and interference.
(Neat block diagram compulsory.)

2(e) Mutual Information and Entropy

Entropy measures the average uncertainty in a source, while mutual information measures the amount of information shared between input and output of a communication system.

SECTION C

3(a) Random Process – Classification and Properties

A random process is a collection of random variables indexed by time. It may be stationary or non-stationary. Properties include mean, autocorrelation, and power spectral density.

3(b) Short Notes

(i) Power Spectral Density (PSD)
PSD describes how signal power is distributed over frequency.

(ii) Autocorrelation Function
It measures similarity of a signal with its delayed version.

(iii) Gaussian Random Process
A process whose amplitude follows Gaussian distribution at every time instant.