communication engineering

38 Pages·2011·0.19 MB·English

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(2011ADMISSION ONWARDS)
SCHEME AND SYLLABI FOR M. Tech. DEGREE
PROGRAMME IN COMMUNICATION ENGINEERING
SEMESTER – I
Hrs / Week Evaluation Scheme (Marks)
Sl. Course Credits
Subject Sessional
No. No. (C)
L T P ESE Total
Sub
TA CT
Total
Applied Mathematics for
1 MECCE 101 3 1 0 25 25 50 100 150 4
Communication Engineering
2 MECCE 102 Advanced Digital Communication 3 1 0 25 25 50 100 150 4
3 MECCE 103 High Frequency Circuits Design 3 1 0 25 25 50 100 150 4
High Performance Communication
4 MECCE 104 3 1 0 25 25 50 100 150 4
Network
5 MECCE 105 Elective I 3 0 0 25 25 50 100 150 3
6 MECCE 106 Elective II 3 0 0 25 25 50 100 150 3
7 MECCE 107 Communication Engineering Lab 0 0 3 25 25 50 100 150 2
8 MECCE 108 Seminar I 0 0 2 50 0 50 0 50 1
Total 18 4 5 225 175 400 700 1100 25

Elective - I (MECCE 105) Elective - II (MECCE 106)
MECCE 105-1 Soft Computing MECCE 105-1 Soft Computing
MECCE 105-2 Antenna Theory and Design MECCE 105-2 Antenna Theory and Design
MECCE 105-3 Global Tracking and Positioning Systems MECCE 105-3 Global Tracking and Positioning Systems
MECCE 105-4 Satellite Communication MECCE 105-4 Satellite Communication
L – Lecture, T – Tutorial, P – Practical
TA – Teacher’s Assessment (Assignments, attendance, group discussion, Quiz, tutorials,
seminars, etc.)
CT – Class Test (Minimum of two tests to be conducted by the Institute)
ESE – End Semester Examination to be conducted by the University
Electives: New Electives may be added by the department according to the needs of emerging
fields of technology. The name of the elective and its syllabus should be submitted to
the University before the course is offered.
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SEMESTER - II
Hrs / Week Evaluation Scheme (Marks)
Sl. Course Credits
Subject Sessional
No. No. (C)
L T P ESE Total
Sub
TA CT
Total
1 MECCE 201 Advanced Digital Signal Processing 3 1 0 25 25 50 100 150 4
Wireless Communications and
2 MECCE 202 3 1 0 25 25 50 100 150 4
Networks
Photonics and Light Wave
3 MECCE 203 3 1 0 25 25 50 100 150 4
Communication
4 MECCE 204 Radio Frequency Integrated Circuits 3 1 0 25 25 50 100 150 4
5 MECCE 205 Elective III 3 0 0 25 25 50 100 150 3
6 MECCE 206 Elective IV 3 0 0 25 25 50 100 150 3
7 MECCE 207 DSP Lab 0 0 3 25 25 50 100 150 2
8 MECCE 208 Seminar II 0 0 2 50 0 50 0 50 1
Total 18 4 5 225 175 400 700 1100 25

Elective - III (MECCE 205) Elective IV- (MECCE 206)
MECCE205-1 Communication Network Security MECCE205-1 Communication Network Security
MECCE 205-2 Speech and Audio Processing MECCE 205-2 Speech and Audio Processing
MECCE 205-3 Wireless Sensor Networks MECCE 205-3 Wireless Sensor Networks
MECCE 205-4 Optical Signal Processing MECCE 205-4 Optical Signal Processing
L – Lecture, T – Tutorial, P – Practical
TA – Teacher’s Assessment (Assignments, attendance, group discussion, Quiz, tutorials,
seminars, etc.)
CT – Class Test (Minimum of two tests to be conducted by the Institute)
ESE – End Semester Examination to be conducted by the University
Electives: New Electives may be added by the department according to the needs of emerging
fields of technology. The name of the elective and its syllabus should be submitted to
the University before the course is offered

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SEMESTER - III
Hrs / Week Evaluation Scheme (Marks)
Sl. Credits
Course No. Subject Sessional
No. ESE** (C)
L T P Total
Sub (Oral)
TA* CT
Total
Industrial Training or
1 MECCE 301 Industrial Training and Mini 0 0 20 50 0 50 100 150 10
Project
2 MECCE 302 Master’s Thesis Phase - I 0 0 10 100*** 0 100 0 100 5
Total 0 0 30 150 0 150 100 250 15
* TA based on a Technical Report submitted together with presentation at the end of the
Industrial Training and Mini Project
** Evaluation of the Industrial Training and Mini Project will be conducted at the end of the
third semester by a panel of examiners, with at least one external examiner, constituted by the
University.
*** The marks will be awarded by a panel of examiners constituted by the concerned institute

SEMESTER - IV
Hrs / Week Evaluation Scheme (Marks)
Sl. ESE** Credits
Course No. Subject Sessional
No. (Oral (C)
L T P Total
Sub &
TA* CT
Total Viva)
1 MECAE 401 Master’s Thesis 0 0 30 100 0 100 100 200 15
2 MECAE 402 Master’s Comprehensive Viva 100 100
Total 30 100 0 100 200 300 15
Grand Total of all Semesters 2750 80
* 50% of the marks to be awarded by the Project Guide and the remaining 50% to be awarded
by a panel of examiners, including the Project Guide, constituted by the Department
** Thesis evaluation and Viva-voce will be conducted at the end of the fourth semester by a panel
of examiners, with at least one external examiner, constituted by the University.

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SEMESTER I
APPLIED MATHEMATICS FOR L T P C
MECCE 101
COMMUNICATION ENGINEERING 3 1 0 4
ELECTRONIC SYSTEM MODELING AND
Module 1: Random Processes -I: -
Review of random variables(RV), distributions and properties – characteristic functions–
functions of RVs, joint pdf. Random processes(RP) – stationary, WSS and ergodic RP –
properties – RP and linear systems – Power spectrum – Weiner-Khinchin theorem.
Module 2: Random Processes -II: -
Discrete/continuous state and discrete/continuous parameter RP- independent RP –
renewal process –poisson and exponential processes – markov process – birth-death
process. Discrete and continuous parameter markov chains – transition probabilities,
limiting distributions – theory of M/M/1.
Module 3: Vector Space and Linear Transformation
Vector spaces. Subspaces, Linear independence, Span, basis, dimension, finite
dimensional vector spaces, direct sum. Examples of finite dimensional vector spaces –
RN, CN, vector space of matrices. Dimensionality of Row and Column space (rank of the
matrix). Non-singular, Hermitian and Unitary matrices. Linear Transformation, range and
null space, rank nullity theorem, Matrix representation of linear transform. Change of
basis
Module 4: Inner Product Spaces:-
Inner Product spaces, norm, orthogonality, Hilbert spaces, orthogonal complements,
projection theorem, orthogonal projections, orthonormal basis.
References:
1. H. Stark, J.W Woods, Probability and Random Processes, Pearson Education, 2002
2. K. S. Trivedi, Probability & Statistics with Reliability, Queuing and Computer Science
Applications, (Second Edition), John Wiley
3. K. Huffman, R. Kunze, Linear Algebra, Prentice Hall of India, 1998
4. Michael W. Frazier, An introduction to wavelets through linear Algebra, Springer,2004
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5. S.D. Sharma, Operation Research
6. Manmohan Gupta, Optimization techniques
7. R D Yates, D J Goodman, Probability and Stochastic Processes, John Wiley and Sons,
2005
8. Richard A. Johnson, Miller and Freund's Probability and Statistics for Engineers, 7th
Edition, PHI, 2004

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L T P C
MECCE 102 ADVANCED DIGITAL COMMUNICATION
3 1 0 4

Module 1: Detection and Estimation
Fundamentals of digital communication-Model-response of bank of correlators-PoE-
correlation receiver-matched filter-Estimation-maximum likelihood-Weiner-linear
prediction-optimum detection of Equivalent signal-optimum detection of random signal.
Module 2: Multiplexing and multiple access
Multiple access techniques-system and architecture-Access algorithms-multiple access
techniques for INTELSAT-multiple access techniques for LAN
Module 3: Spread spectrum Techniques
Spread spectrum overview-PN sequences-DS spread spectrum-Frequency hopping-
synchronization-jamming considerations- commercial applications-cellular systems
Module 4: Digital Communications through Fading Channels
Fading-signal time spreading-time varience caused by motion-mitigating the degradation
effects of Fading-Rake Receiver-viterbi equaliser.
References:
1. Bernard Sclar and Pabitra kumar Ray “Digital Communications Fundamentals and
Applications”, Pearson Education,2nd edition,2001
2. Simon Haykin, “Digital Communications”, John Wiley and sons,1998
3. 1. J. Proakis, “Digital Communications”, McGraw Hill, 4th edition,2007
4. J. Viterbi and J. K. Omura, “Principles of Digital Communications and Coding”,
McGraw Hill, 1979
5. Marvin K. Simon, Jim K. Omura, Robert A. Scholtz, Barry K. Levit, “Spread
Spectrum Communications”, Computer Science Press, 1988.
6. Andrew J Viterbi, “CDMA Principles of Spread Spectrum Communications”,
Addison Wesley, 1995.

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L T P C
MECCE 103 HIGH FREQUENCY CIRCUITS DESIGN
3 1 0 4
Module 1: Review of Basic Transmission Line Theory
Review of basic transmission line theory, transmission lines analysis, transmission lines,
circuit representations, parameters, transmission line equations, microstrip transmission
line terminated lossless transmission line, special termination condition, sourced and
loaded transmission lines, smith chart.
Module 2: RF Filter Design
Basic resonator and filter configurations, special filter realization, filter
implementation, scattering parameters.
Module 3: Active RF Components
RF Diodes, BJT, FET, impedance matching using discreet components, microstrip line
matching networks, Amplifier classes of operation and biasing networks.
Module 4: RF Transistor Amplifier and Oscillators Design
Amplifier power relation, stability considerations, constant gain, noise figure circles,
constant VSWR circles, Basic oscillator modal, High frequency oscillator configuration,
basic characteristics of mixers
References:
1. R.Ludwig, P. Bretchko, “RF Circuit Design”, Pearson Asia Education, New Delhi,
2004.
2. D. M. Pozar, “Microwave Engineering”, 2nd Edition, John Wiley & Sons, 2005.
3. M.M. Radmanesh, “Radio Frequency and Microwave Electronics”, Pearson
Education Asia, 2001.
4. B. Bhat & S.K. Koul, “Stripline - Like Transmission Line for Microwave
Integrated Circuits”, New Age Intl. (P) Ltd., 1989.
5. D. K. Misra, “Radio Frequency and Microwave Communication Circuits- Analysis
and Design”, John Wiley & Sons, 2004,

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HIGH PERFORMANCE COMMUNICATION L T P C
MECCE 104
NETWORK 3 1 0 4

Module 1: Review of Networking Concepts
Services, layered architectures, packet switching, OSI and IP models, IEEE 802.x,
ethernet, token ring, Fiber Distributed Data Interface (FDDI), Distributed-Queue Dual-
Bus(DQDB), Frame Relay and Switched Multimegabit Data Service(SMDS). Internet and
TCP/IP networks, TCP and UDP.
Module 2: TCP/IP Network
Performance of TCP/IP Networks, Circuit switched networks, performance of
Synchronous Optical Networking(SONET), Dense Wavelength Division
Multiplexing(DWDM), Fiber To The Home(FTTH), DSL, Intelligent networks, CATV.
Module 3: ATM Network
ATM network, features, addressing, signalling, routing, ATM adaptation layer (AAL),
management and control, BISDN, internetworking with ATM. Optical networks, WDM
systems, cross connects, optical LANs and Networks.
Module 4: Switching
Switching, performance measures, time and space division switching, modular switch
designs, packet switching, distributed buffer, shared buffer, output buffer and input buffer
switches, attributes of a global multimedia network, challenges in its realization.
References:
1. Jean Walrand & Pravin Varaiya, “High Performance Communication Networks” ,
2nd edition, Morgan Kaufman Publishers,2000
2. Leon Gracia, Widjaja, “Communication Networks”, 2nd edition, Tata McGraw
Hill, New Delhi, 2003.
3. Sumit Kasera, Pankaj Sethi, "ATM Networks ", Tata McGraw,Hill, New Delhi,
2000.
4. Behrouz.a. Forouzan, “Data Communication and Networking”, Tata McGraw Hill,
New Delhi, 2006
5. Larry L. Peterson, Bruce S. Davie, “Computer networks”, 4th edition, Elsevier,
2007
6. Dimitri P. Bertsekas, Robert G. Gallager, “Data Networks” 2nd edition, Prentice
Hall, 1992.
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ELECTIVE - I
L T P C
MECCE 105- 1 SOFT COMPUTING
3 0 0 3
Module 1: Introduction
Soft computing constituents, conventional artificial intelligence, computational
intelligence, characteristics, fuzzy sets, set theoretic operations, membership functions,
one and two dimensional, fuzzy union, intersection and compliment.
Module 2: Rules and Reasoning
Extension principle, fuzzy relations, if-then rules, reasoning, inference systems-mamdani
model, considerations, input space partitioning, fuzzy modeling.
Module 3: Least-Square Methods
Basics of matrix manipulation and calculus, least square estimator, geometric
interpretation of LSE, recursive LSE, neuro networks, architecture, back propagation for
feedback.
Module 4: Adaptive Neuro-Fuzzy Inference System
Architecture, hybrid learning algorithm, data clustering algorithms- clustering, k-means,
fuzzy c-means (FCM), rule base structure - input selection, space partitioning, rule base
organization.
References:
1. Jang J.S.R., Sun C.T, Mizutami E, “Neuro Fuzzy and Soft Computing”, Prentice
hall New Jersey, 2008
2. Timothy J. Ross, “Fuzzy Logic Engineering Applications”, McGraw Hill, New
York, 2004.
3. Laurene Fauseett, “Fundamentals of Neural Networks”, Prentice Hall India, New
Delhi, 1994.

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