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An Introduction to Coding Theory

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1236 min
Anytime
English
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Why enroll

People join this course to understand the core principles behind error detection and error correction used in real-world communication systems. It is especially useful for students and professionals in electronics, communication engineering, computer science, and information theory who want to strengthen their theoretical foundation and improve their problem-solving skills. The course also helps learners prepare for higher studies, research, competitive exams, and careers in fields like wireless communication, data transmission, and digital system design.

Is this course for you?

You should take this if

  • You work in Telecommunication
  • You're a Electronics & Telecommunication / Instrumentation Engineering professional
  • You have 3+ years of hands-on experience in this field
  • You prefer self-paced learning you can revisit

You should skip if

  • You're new to this field with no prior experience
  • You need a different specialisation outside Electronics & Telecommunication
  • You need live interaction with an instructor

Course details

An Introduction to Coding Theory provides a foundational understanding of how information is encoded, transmitted, and decoded reliably over noisy communication channels. The course focuses on mathematical and practical techniques used to detect and correct errors in digital communication and data storage systems. It bridges concepts from linear algebra, probability, and digital communications to explain how modern technologies such as mobile networks, satellite communication, QR codes, and data storage devices achieve high reliability.

SOURCE - NPTEL [YOUTUBE]

Course suitable for

Key topics covered

  1. Basics of information theory and communication channels

  2. Types of errors in digital communication systems

  3. Linear block codes and their properties

  4. Hamming codes and error correction capability

  5. Cyclic codes and generator polynomials

  6. Encoding and decoding techniques

  7. Syndrome decoding and error detection methods

  8. Introduction to convolutional codes

  9. Applications of coding theory in communication and data storage

Course content

The course is readily available, allowing learners to start and complete it at their own pace.

33 lectures20 hr 36 min
  1. Introduction to Error Control Coding-I
    24 min
  2. Introduction to Error Control Coding-II
    20 min
  3. Introduction to Error Control Coding-III
    35 min
  4. Introduction to Linear Block Codes, Generator Matrix and Parity Check Matrix
    29 min
  5. Syndrome, Error Correction and Error Detection
    20 min
  6. Problem Solving Session-I
    30 min
  7. Decoding of Linear Block Codes
    47 min
  8. Distance Properties of Linear Block Codes-I
    22 min
  9. Distance Properties of Linear Block Codes-II
    40 min
  10. Problem Solving Session-II
    41 min
  11. Some Simple Linear Block Codes-I
    51 min
  12. Some Simple Linear Block Codes-II: Reed Muller Codes
    51 min
  13. Bounds on the Size of a Code
    32 min
  14. Problem Solving Session-III
    18 min
  15. Introduction to Convolutional Codes-I: Encoding
    46 min
  16. Introduction to Convolutional Codes-II: State Diagram, Trellis Diagram
    26 min
  17. Convolutional Codes: Classification, Realization
    43 min
  18. Convolutional Codes:Distance Properties
    30 min
  19. Decoding of Convolutional Codes-I: Viterbi Algorithm
    35 min
  20. Decoding of Convolutional Codes-II: BCJR Algorithm
    66 min
  21. Problem solving session-IV
    40 min
  22. Problem solving session-V
    32 min
  23. Performance Bounds for Convolutional Codes
    34 min
  24. Low Density Parity Check Codes
    51 min
  25. Decoding of Low Density Parity Check Codes-I
    28 min
  26. Decoding of Low Density Parity Check Codes-II: Belief Propagation Algorithm
    41 min
  27. Turbo Codes
    40 min
  28. Turbo Decoding
    60 min
  29. Problem Solving Sessions-VI
    26 min
  30. Distance Properties of Turbo Codes
    33 min
  31. Convergence of Turbo Codes
    40 min
  32. Automatic Repeat reQuest (ARQ) Schemes
    63 min
  33. Applications of Linear Codes
    42 min

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Questions and Answers

A: A higher code rate looks attractive but pushes the operating point out of the waterfall so HARQ churn eats the gain. Reduced trellis depth does cut compute but it doesn't rescue distance properties at fixed Eb/N0. Ideal interleaving doesn't cancel the fundamental parity overhead at a fixed error target. Extra parity reduces payload bits and you're already past the knee so there's no BER headroom to trade.

A: Metric quantization spreads errors more uniformly rather than in bursts. LLR scaling errors raise BER but don't align errors in time. Shortened blocks hurt distance but still randomize error locations. A shallow interleaver lets a fade wipe adjacent coded bits, which the decoder can't decorrelate.

A: Two parity bits can't index all error locations so single error correction fails. Padding to powers of two confuses block length with parity count and overstates distance. Single error correction still requires distance three, not two. Three parity bits satisfy 2^p ≥ n+1, giving a (7,4) code with distance three.

A: CRCs are very effective against random independent errors. Thermal noise is exactly the environment CRCs are designed around. Overhead affects efficiency, not protection. A repeating fault that maps to a multiple of the polynomial can slip through undetected.