NOC:Principles of Digital Communications (2018)


Lecture 1 - Introduction


Lecture 2 - Signal Spaces : Waveforms and Vector Spaces


Lecture 3 - Inner Product and Orthogonal Expansion


Lecture 4 - Signal Spaces : Gram Schmidt Orthogonalization and Receiver Structures


Lecture 5 - Signal Spaces : Fourier Series and Related expansions


Lecture 6 - Signal Spaces : Bandwidth and Degree of Freedom


Lecture 7 - Random Variables and Random Processes : Discrete Random Variable


Lecture 8 - Random Variables and Random Processes : Continuous Random Variable


Lecture 9 - Random Variables and Random Processes : Multiple Random Variable


Lecture 10 - Random Variables and Random Processes : Random Vectors


Lecture 11 - Random Variables and Random Processes : Introduction to Random Process


Lecture 12 - Random Variables and Random Processes : Properties of Random Process


Lecture 13 - Random Variables and Random Processes : Gaussian Random Process - Part 1


Lecture 14 - Random Variables and Random Processes : Gaussian Random Process - Part 2


Lecture 15 - Random Variables and Random Processes : Types of Random Process


Lecture 16 - Random Variables and Random Processes : Random Process through an LTI system


Lecture 17 - Random Variables and Random Processes : Spectral description of Random Process


Lecture 18 - Waveform Coding


Lecture 19 - Modulation : Complex Baseband Representation of Passband Signals - Part 1


Lecture 20 - Modulation : Complex Baseband Representation of Passband Signals - Part 2


Lecture 21 - Modulation : Complex Baseband Representation of Passband Signals - Part 3


Lecture 22 - Modulation : Spectral Description of Sources - Part 1


Lecture 23 - Modulation : Spectral Description of Sources - Part 2


Lecture 24 - Modulation : Spectral Description of Sources using Markov Chains and Cyclostationary Random Processes


Lecture 25 - Modulation : Nyquist Pulses


Lecture 26 - Modulation : Pulse Amplitude Modulation and Quadrature Amplitude Modulation - Part 1


Lecture 27 - Modulation : Pulse Amplitude Modulation and Quadrature Amplitude Modulation - Part 2


Lecture 28 - Modulation : Orthogonal Modulation Schemes


Lecture 29 - Modulation : Differential Modulation Schemes


Lecture 30 - Detection : Maximum Aposteriori Probability (MAP) Detector and Maximum Likelihood (ML) Detector


Lecture 31 - Detection : Vector Detection


Lecture 32 - Detection : Theorem of Irrelevance and Waveform Detection


Lecture 33 - Detection : Sequence Detection


Lecture 34 - Detection : Performance of Binary Signalling Schemes


Lecture 35 - Detection : Performance of M-ary Signaling Schemes


Lecture 36 - Detection : Performance of Orthogonal Modulation Schemes and Bit-Level Demodulation


Lecture 37 - Detection : Performance of Non-Coherent Systems Systems


Lecture 38 - Detection : Fading Channel