EEE | Master of Technology in Communication Engineering
Courses id Courses Title
[3 - 0 - 0]
Selected Topics in Information Processing-I
[3 - 0 - 0]
Selected Topics in Information Processing-II
[0 - 1 - 4]
Telecommunication Software Laboratory
Contents: CASE tools, object-oriented program development, use of telecom network simulator, implementation using C/C++/Java, network management software design, V.5 test and simulation.
[0 - 0 - 12]
Major Project Part-I (Communication Engineering)
[3 - 0 - 0]
Signal Theory
Discrete random variables (Bernoulli, binomial, Poisson, geometric, negative binomial, etc.) and their properties like PDF, CDF, MGF.|Continuous random variables: Gaussian, multivariate Gaussian; whitening of the Gaussian random vector; complex Gaussian random vector, circularity; Rayleigh and Rician; exponential; chi-squared; gamma.|Signal spaces: convergence and continuity; linear spaces, inner product spaces; basis, Gram-Scmidt orthogonalization.|Stochastic convergence, law of large numbers, central limit theorem.|Random processes: stationarity; mean, correlation, and covariance functions, WSS random process; autocorrelation and cross-correlation functions; transmission of a random process through a linear filter; power spectral density; white random process; Gaussian process; Poisson process.
[3 - 0 - 0]
Digital Communications
Review of random variables and random process, signal space concepts, Common modulated signals and their power spectral densities, Optimum receivers for Gaussian channels, Coherent and non-cohrerent receivers and their performance (evaluating BER performance through software tools), Basics of Information theory, source and channel coding, capacity of channels, band-limited channels and ISI, multicarrier and spread-spectrum signaling, multiple access techniques.
[3 - 0 - 0]
Microwave Theory and Techniques
Review of EM theory: Maxwells equations, plane waves in dielectric and conducting media, energy and power. Transmission lines and waveguides: closed and dielectric guides, planar transmission lines and optical fibre. Network analysis: scattering matrix other parameters, signal flow graphs and network representation. Impedance matching and tuning. Analysis of planar transmission lines. Analysis of design of passive components.
[0 - 1 - 4]
Microwave Laboratory
Design, fabrication and testing of simple linear microwave circuits using microstrip technology.
[3 - 0 - 0]
Human & Machine Speech Communication
Overview of human and machine speech communication: Applications; Speech signal measurement and representation. Speech science topics: Speech production and phonetics: Speech production mechanism; Articulatory and acoustic phonetics; Speech production model; International Phonetic Alphabet; Phonetic transcription; Hearing and perception. Speech signal analysis: Time domain analysis; Spectrum domain analysis; Spectrogram; Cepstrum domain analysis; Pitch estimation; Voicing analysis; Linear prediction analysis. Engineering applications: Speech coding; Speech quality assessment: Subjective and objective evaluation of quality; Automatic speech recognition: HMM; Language models; Keyword spotting; Text-to-speech synthesis: Concatenative and HMM speech synthesis; Prosody modification.|The course will include audio demonstrations and require students to do practical exercises with recorded speech signals. An isolated word speech recognizer using open source resources shall be designed.
[3 - 0 - 0]
Underwater Electronic Systems
Introduction to High Resolution Underwater Imaging Applications, Sidescan Sonar principles, Sector Scan Sonar Principles: Principle of within-pulse scanning, role of grating lobe in sector coverage, Swept-frequency delay line scanning technique, Time-Delay-Integrate scanning technique, Modulation Scanning Technique: Multi-stage scanning, Spatial DFT-based imaging technique, True Phase-Shift beamforming: Near-field focusing, Hilbert-transform based implementation, Synthetic Aperture Sonar: range migration issue, PRF limits, swath coverage, real beam pattern effects, tow-body precision issues, CTFM Sonar, Dual Demodulation CTFM Sonar Phase-Difference based SAS, Radial Projection method of imaging, Monopulse technique, Navigation: Doppler Log, JANUS system, Localization: LBL (Long baseline), SBL (Short baseline), SSBL/USBL (super/ultra short baseline), requirements of tracking and positioning systems, hyperbolic and spherical-based localization using pingers and transponders, Passive Inverse Synthetic Aperture for localizing radiated tonals from moving platforms, Underwater Acoustic Communication Modems and their applications.
[3 - 0 - 0]
Radiating Systems for RF Communication
Revision of Maxwells equations,radiation, Poynting vector; antenna parameters like gain, radiation pattern, VSWR wire antennas dipole monopole; antenna arrays; aperture antennas and equivalence theorems; printed antennas, scattering.
[0 - 0 - 24]
Major Project Part-II
[3 - 0 - 0]
Mathematical Methods in Control
Linear Spaces Vectors and Matrices, Transformations, Norms - Vector and Matrix norms, Matrix factorization, Eigenvalues and Eigenvectors and Applications, Singular Value Decomposition and its Applications, Projections, Least Square Solutions. Probability, Random Variables, Probability distribution and density functions, Joint density and Conditional distribution, Functions of random variables, Moments, characteristic functions, sequence of random variables, Correlation matrices and their properties, Random processes and their properties, Response of Linear systems to stochastic inputs, PSD theorem.
[3 - 0 - 0]
Coding Theory
Measure of information, Source coding, Communication channel models, Channel Capacity and coding, Linear Block codes, Low Density Parity Check (LDPC) Codes, Bounds on minimum distance, Cyclic codes, BCH codes, Reed Solomon Codes, Convolutional codes, Trellis coded Modulation, Viterbi decoding, Turbo codes, Introduction to Space-Time Codes and Introduction to Cryptography. If time permits, LDPC/Turbo codes in the wireless standards. There are no laboratory or design activities involved with this course.
[3 - 0 - 0]
Basic Information Theory
Introduction to entropy, relative entropy, mutual information, fundamental inequalities like Jensens inequality and log sum inequality. Proof of asymptotic equipartition property and its usage in data compression. Study of entropy rates of the stochastic process following Markov chains. Study of data compression: Kraft inequality and optimal source coding. Channel capacity: symmetric channels, channel coding theorem, Fanos inequality, feedback capacity. Differential entropy. The Gaussian channel: bandlimited channels, channels with colored noise, Gaussian channels with feedback. Detailed study of the rate-distortion theory: rate distortion function, strongly typical sequences, computation of channel capacity. Joint source channel coding/separation theorem. There are no laboratory or design activities involved with this course.
[3 - 0 - 0]
Telecommunication Switching and Transmission
Wireline access circuits, long haul circuits, signaling, switching exchanges, analysis of telecom switching networks, teletraffic engineering, management protocols, multi-service telecom protocols and networks.
[3 - 0 - 0]
Micro and Nanoelectronics
Technology basics and digital logic families such as static CMOS, pass transistor, transmission gate, dynamic and domino logic. Advanced sequential logic elements with latch-based design and timing and clocking concepts. Power and delay of digital circuits. Physical and logical synthesis for ASICs and FPGAs. Verilog and VHDL with design examples. Design for testability with fault models.
[3 - 0 - 0]
MOS VLSI design
Digital integrated circuit design perspective. Basic static and dynamic MOS logic families. Sequential Circuits. Power dissipation and delay in circuits. Arithmetic Building blocks, ALU. Timing Issues in synchronous design. Interconnect Parasitics.
[3 - 0 - 0]
Analog Integrated Circuits
Introduction to MOSFETs, Single stage amplifiers, Biasing circuits, Voltage and Current reference circuits, Feedback analysis, Multistage amplifiers, Mismatch and noise analysis, Differential amplifiers, High speed and low noise amplifiers, Output stage amplifiers, Oscillators.
[3 - 0 - 0]
Introduction to Machine Learning
Introduction to Machine intelligence and learning; linear learning models; Artificial Neural Networks: Single Layer Networks, LTUs, Capacity of a Single Layer LTU, Nonlinear Dichotomies, Multilayer Networks, Growth networks, Backpropagation and some variants; Support Vector Machines: Origin, Formulation of the L1 norm SVM, Solution methods (SMO, etc.), L2 norm SVM, Regression, Variants of the SVM; Complexity: Origin, Notion of the VC dimension, Derivation for an LTU, PAC learning, bounds, VC dimension for SVMS, Learning low complexity machines - Structural Risk Minimisation; Unsupervised learning: PCA, KPCA; Clustering: Origin, Exposition with some selected methods; Feature Selection: Origin, Filter and Wrapper methods, State of the art - FCBF, Relief, etc; Semi-supervised learning: introduction; Assignments/Short project on these topics.
[3 - 0 - 0]
Computer Communication Networks
Theory/Lecture: Review of data communication techniques, basic networking concepts, layered network and protocol concepts, quality of service, motivations for cross-layer protocol design. Motivations for performance analysis, forward error correction and re-transmission performances, Markov and semi-Markov processes, Littles theorem, M/M/m/k, M/G/1 systems, priority queueing, network of queues, network traffic behavior. Concepts and analysis of multi-access protocols; contention-free and contention multi-access protocols. Basic graph theoretic concepts, routing algorithms and analysis.|Suggested lab Course content:|Laboratory: Simulation and hardware experiments on different aspects of computer communication networks. Network traffic generation and analysis, differentiated service queues, network of queues using discrete event simulations.
[3 - 0 - 0]
Computer Vision
Link between Computer Vision, Computer Graphics, Image Processing and related fields; feature extraction; camera models; multi-view geometry; applications of Computer Vision in day-to-day life.
[3 - 0 - 0]
Telecommunication Technologies
Types of Data Networks, types of access and edge networks, core networks, OSS/NMS and Telecom Management network (TMN), Teletraffic Theory and Network analysis.
Block II, IIT Delhi Main Rd, IIT Campus, Hauz Khas, New Delhi, Delhi 110016