B.Tech – Semester IV | Total Marks: 70 | Time: 3 Hours
This question paper checks a student’s understanding of information theory, entropy, coding techniques, error detection & correction, channel capacity, block codes, Huffman/Shannon coding, BSC/BEC channels, and convolution/Hamming codes.
The paper has three sections:
Short concepts (A)
Medium-level problems (B)
Long analytical/coding questions (C)
SECTION A — Short Answer Questions (2 × 7 = 14 Marks)
This section contains 7 short questions covering basics of information theory & codes.
Topics include:
Information=0 if receiver already knows message Entropy
Kraft–McMillan inequality BSC (Binary Symmetric Channel) matrix & diagram
Channel capacity theorem Advantages of cyclic codes
Golay codes (short note)
These test basic concepts, definitions, and core theories of information systems.
SECTION B — Medium-Length Analytical Questions (7 × 3 = 21 Marks)
Attempt ANY 3 out of 5.
Topics include:
(a) Noiseless Channel Entropy
Prove:
H(X)=H(Y)H(X)=H(Y)H(X)=H(Y) H(Y∣X)=0H(Y|X)=0H(Y∣X)=0
(b) Shannon–Fano Coding
For a given 7-symbol DMS, construct code and calculate code efficiency.
(c) Mutual Information for BSC
Derive mutual information equation Calculate I(X;Y) for α=0.5 and p=0.1
(d) Linear Block Code (7,4)
Using parity-check matrix H, find:
Generator matrix G All code vectors
Minimum distance Error-detecting & correcting capability
(e) Coding Techniques
Explain:
BCH codes Reed–Solomon codes
Shortened cyclic codes
This section tests mathematical reasoning, probability, and coding construction skills.
SECTION C — Long / Analytical Questions (7 marks each)
Each question has two choices (a or b).
These require full derivations, coding steps, numerical results, or theoretical explanation.
Q3 – Information Rate / Mutual Information
(a) Calculate information rate of telegraph source
OR
(b) Mutual information and its properties (with examples)
Q4 – Huffman Coding / Block Codes
(a) Construct Huffman code for 6-symbol DMS and find code efficiency
OR
(b) Explain block codes and their properties
Q5 – Channel Capacity / Channel Types
(a) Find channel capacity of Binary Erasure Channel
OR
(b) Explain different channels with their channel matrix & diagram
Q6 – Error Detection / Linear Block Code
(a) Different error detection methods with examples
OR
(b) Given (6,3) code & G matrix → find transmitted data word from received word
Q7 – Convolution / Hamming Codes
(a) Convolution codes + generator matrix
OR
(b) Hamming code (7,4) using polynomial g(x) — find syndrome and error polynomial
These questions test coding design, decoding, channel analysis, error control methods, and polynomial-based coding theory.
OVERALL PURPOSE OF THE EXAM
The question paper evaluates whether the student can:
Understand entropy, information, and source coding
Construct Shannon–Fano & Huffman codes
Compute mutual information, conditional entropy, and channel capacity
Build and decode linear block codes
Analyze BSC/BEC channels
Understand cyclic, BCH, Reed–Solomon, and convolutional codes
Perform error detection & correction
Work with generator/parity-check matrices and syndrome decoding
Apply coding theory in reliable communication systems
This paper focuses on mathematical fundamentals + coding design + theoretical reasoning, essential for communication engineering.
