Modern Digital Communication Techniques

Modern Digital Communication Techniques. Instructor: Prof. Suvra Sekhar Das, G. S. Sanyal School of Telecommunication, IIT Kharagpur. The objective of this course is to present the engineering principles, theories and practices, which are necessary for successful design of a digital communication system. The course will delve into the design principles of transmitter and receiver so as to establish a reliable communication link. This course aims at enabling the participants to establish unambiguous mathematical statements describing every step of transmitting and receiving a signal through a communication link. It aims at exposing the details of noise, its modeling and its effect on communication systems design. It will cover methods of performance analysis of digital communication systems. Through use of fundamental knowledge developed in related areas of signal processing, the course aims at presenting a unified way of analyzing and designing a digital communication system. It will encompass central aspects of estimation and detection theory, which are crucial in designing a complete receiver (synchronization, channel equalization, etc.). At the end of the course, the participant will be equipped with methods of systematic representation, analysis and design of a digital communication system which are essential in designing communication systems with complex and futuristic requirements. (from

Differences between Analog and Digital Communication Systems

Introduction to Digital Communication System
Lecture 01 - Differences between Analog and Digital Communication Systems
Lecture 02 - Important Aspects of a Digital Communication System
Lecture 03 - Standardized Interfaces and Layering
Lecture 04 - Probability and Randomness in the Communication System
Lecture 05 - Components of Transmitter
Source Coding
Lecture 06 - Rx Block Diagram, Discrete Sources and Fixed Length Coding
Lecture 07 - Fixed Length Coding, Fixed Length Coding for M Tuples and Variable Length Coding
Lecture 08 - Variable Length Coding, Unique Decodability, Prefix Free Code
Lecture 09 - Prefix Free Code (Full Tree), Kraft Inequality
Lecture 10 - Kraft Inequality: Minimum L for Prefix Free Code
Lecture 11 - Entropy Bounds on L
Lecture 12 - Fixed to Variable Length Coding
Lecture 13 - Examples on Source Coding
Lecture 14 - Huffman Algorithm
Analog to Digital Conversion
Lecture 15 - Sampling of Analog Sources
Lecture 16 - Quantization
Characterization of Signals and Systems
Lecture 17 - Signals and Characterization, Unit Step Function, Delta Function
Lecture 18 - Important Fourier Relationships for Communication System Analysis
Lecture 19 - Representation of Bandpass Signals
Lecture 20 - Representation of Bandpass Systems, Representation of Bandpass Signal Output of a Band Pass System
Lecture 21 - Representation of Bandpass Stochastic Processes
Lecture 22 - Autocorrelation and Power Spectral Density of White Noise in Communication System
Lecture 23 - Signal Space Representation: Gram Schmidt Procedure, Signal Space Concept, Orthogonal Expansion of Signal
Memoryless Modulation
Lecture 24 - Introduction to Modulation, Difference between Analog and Digital Modulation
Lecture 25 - Pulse Amplitude Modulation
Lecture 26 - Distinction between Quantizer Levels and Pulse Amplitude Level, Symbol Mapping
Lecture 27 - Gray Coding, Signal Energy, Euclidean Distance between Signals
Lecture 28 - Phase Shift Keying (PSK)
Lecture 29 - Quadrature Amplitude Modulation (QAM)
Lecture 30 - Signal Generation for QAM, Scalable/ Flexible QAM Constellation
Lecture 31 - Spectral Efficiency, N-Dimensional Signalling
Lecture 32 - M-ary Orthogonal Frequency Shift Keying
Modulation with Memory
Lecture 33 - Orthogonal FSK (cont.), Orthogonal Frequency Division Multiplexing, NRZI
Lecture 34 - Continuous Phase Frequency Shift Keying
Lecture 35 - Continuous Phase Modulation
Lecture 36 - Minimum Shift Keying
Lecture 37 - QPSK and Offset QPSK
Lecture 38 - Spectral Characteristics of Digitally Modulated Signals
Lecture 39 - Power Spectral Density
Optimum Receivers for Additive White Gaussian Noise (AWGN)
Lecture 40 - AWGN Channel, Receiver Structure
Lecture 41 - Receiver Architecture: Correlation Demodulator
Lecture 42 - Receiver Architecture: Matched Filter Demodulator
Lecture 43 - Properties of the Matched Filter
Lecture 44 - The Optimum Detector
Lecture 45 - The Optimum Detector (cont.)
Performance of Digital Modulation Techniques
Lecture 46 - Probability of Error: Binary Modulation, M-ary PAM
Lecture 47 - Probability of Error: PAM, QAM
Lecture 48 - Probability of Error for M-ary Orthogonal Signals
Lecture 49 - Probability of Error for Binary Orthogonal Signals
Lecture 50 - Channel Models: Binary Symmetric channel, Waveform Channels
Lecture 51 - Channel Capacity
Lecture 52 - Channel Capacity (cont.)
Channel Estimation and Equalization
Lecture 53 - Communication through Band Limited Channels
Lecture 54 - Nyquist Pulse and Filter, Inter Symbol Interference (ISI)
Lecture 55 - Data Detection for Controlled ISI, Equalizer
Lecture 56 - Channel Estimation, Equalizer
Synchronization Techniques
Lecture 57 - Signal Parameter Estimation, Minimum Variance Unbiased Estimator, Cramer Rao Lower bound
Lecture 58 - Maximum Likelihood Estimator
Lecture 59 - Total Carrier Phase or the Carrier Frequency at the Receiver
Lecture 60 - Symbol Timing Recovery

Modern Digital Communication Techniques
Instructor: Prof. Suvra Sekhar Das, G. S. Sanyal School of Telecommunication, IIT Kharagpur. This course discusses the engineering principles, theories and practices, which are necessary for successful design of a digital communication system.