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Digital Communication

Digital Communication. Instructor: Prof. Bikash Kumar Dey, Department of Electrical Engineering, IIT Bombay. The course provides an introduction to the principles of digital communication and investigates what happens inside digital communication systems. Topics covered in the lectures include: sampling, quantization, PCM and delta modulation, probability and random process, channels and their models, information theory, bandpass signal representation, digital modulation techniques, calculation of probability of error, and Equalizers. (from nptel.ac.in)

Lecture 24 - Calculation of Probability of Error for Biorthogonal Signal Sets, Upper Bound on Probability of Error


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Lecture 01 - Introduction to Digital Communication
Lecture 02 - Sampling
Lecture 03 - Quantization, PCM, and Delta Modulation
Lecture 04 - Probability and Random Process
Lecture 05 - Probability and Random Process (cont.)
Lecture 06 - Channels and Their Models
Lecture 07 - Channels and Their Models (cont.)
Lecture 08 - Information Theory
Lecture 09 - Information Theory (cont.)
Lecture 10 - Bandpass Signal Representation
Lecture 11 - Bandpass Signal Representation (cont.)
Lecture 12 - Digital Modulation Techniques: Pulse Amplitude Modulation
Lecture 13 - Digital Modulation Techniques: Pulse Amplitude Modulation (cont.)
Lecture 14 - Demodulation Techniques for PAM Signals
Lecture 15 - Demodulation of PAM Signals (cont.), PSK (Phase Shift Keying)
Lecture 16 - PSK and QAM (Quadrature Amplitude Modulation), Linear Algebra
Lecture 17 - Some Basic Linear Algebra for Digital Modulation
Lecture 18 - Frequency Shift Keying (FSK), Pulse Position Modulation (PPM)
Lecture 19 - Biorthogonal Signals, Demodulation
Lecture 20 - Demodulation: PAM, PSK, QAM, FSK, PPM, etc.
Lecture 21 - Digital Modulation Techniques: Eye Diagram, Mapper
Lecture 22 - Calculation of Probability of Error for PAM and Binary PAM
Lecture 23 - Calculation of Probability of Error for QAM, FSK, and PPM
Lecture 24 - Calculation of Probability of Error for Biorthogonal Signal Sets, Upper Bound on Probability of Error
Lecture 25 - Equalizers
Lecture 26 - Source Coding: Introduction, Huffman Code
Lecture 27 - Source Coding: Kraft Inequality, Optimal Codes
Lecture 28 - Source Coding: Block-wise Source Coding, Shannon-Fano-Elias Code
Lecture 29 - Source Coding: Arithmetic Coding, Lempel-Ziv Code
Lecture 30 - Channel Coding
Lecture 31 - Fundamentals of OFDM
Lecture 32 - Conclusion