KIT’s College of Engineering, Kolhapur. (An Autonomous Institute ...kitcoek.in/wp-content/uploads/2019/01/mtechetcsyllabus.pdf · ESE: Assessment is based on 100% course content

KIT’s College of Engineering, Kolhapur.

(An Autonomous Institute)

Department of Electronics Engineering

Teaching and Evaluation scheme for First Year M.Tech.

Program in Electronics& Telecommunication Engineering, Semester-I

Course Code

Subject Teaching Scheme Evaluation Scheme

L T P Credits Scheme Weightage

PETC0101 Next Generation Network System 3 1 - 4 Max Min Min

ISE-I 10 40 MSE 30

ISE-II 10

ESE 50 20

PETC0102 Engineering Linear Algebra 3 - - 3 ISE-I 10 40 MSE 30

ISE-II 10

ESE 50 20

PETC0103 Random Processes & Stochastic Process

4 - - 4 ISE-I 10 40 MSE 30

ISE-II 10

ESE 50 20

PETC01** Professional Elective-I 3 1 - 4 ISE-I 10 40

MSE 30 ISE-II 10

ESE 50 20

PETC01** Professional Elective-II 4 1 - 5 ISE-I 10 40

MSE 30 ISE-II 10

ESE 50 20

PETC0161 Research Methodology (Audit Course)

2 - - - ESE 100 40

PETC0131 Random Process& Stochastic Processlab

- - 2 1 ISE 50 20

ESE(OE) 50 20

PETC0132 Engineering Linear Algebra Lab - - 2 1 ISE 50 20

ESE(OE) 50 20 PETC0141 Seminar I - - 2 1 ISE 100 40

Total 17+ 2

3 6 23 Total Contact Hours/Week: 26+2Hrs

Total Credits: 23

Total Contact Hours/Week: 26+2Hrs Note: ESE: End Semester Examination, MSE: Mid Semester Examination, ISE: In Semester Evaluation.

KIT’s College of Engineering, Kolhapur. (An Autonomous Institute)

Teaching and Evaluation scheme for First Year M.Tech.

Program in Electronics & Telecommunication Engineering Semester-II

Course Code

Subject Teaching Scheme Evaluation Scheme

L T P Credits Scheme Weightage

PETC0204 RF and Microwave Circuit design 4 - - 4 Max Min Min

ISE-I 10 40 MSE 30

ISE-II 10

ESE 50 20

PETC0205 Software Defined Radio 4 1 - 5 ISE-I 10 40 MSE 30

ISE-II 10

ESE 50 20

PETC0206 Adaptive Signal Processing 3 - - 3 ISE-I 10 40

MSE 30 ISE-II 10

ESE 50 20

PETC02** Professional Elective III 3 1 - 4 ISE-I 10 40

MSE 30 ISE-II 10

ESE 50 40

PETC02** Professional Elective IV 4 1 - 5 ISE-I 10 40

MSE 30 ISE-II 10

ESE 50 20

PETC0262 Standards in communication systems(Audit)

2 - - - ESE 100 40

PETC0233 RF & Microwave Circuit Design Lab - - 2 1 ISE 50 20

ESE(OE) 50 20

PETC0234 Adaptive Signal Processing Lab - - 2 1 ISE 50 20

ESE(OE) 50 20

PETC0242 Pre Dissertation Seminar - - 2 1 ISE 100 40 PETC0243 Mini Project - - 2 1 ISE 100 40

Total 18+2 3 8 25 Total Contact Hours/Week: 29+2Hrs

Total Credits: 25

Total Contact Hours/Week: 29+2Hrs

Semester III

Course Code Subject Teaching Scheme Evaluation Scheme

L T P Credit Scheme Weightage

Max Min

PETC0343 Industrial Training

- - - 2 ISE 100 40

PETC0351 Dissertation Phase-I

- - - 2 ISE-I 50 20

4 ISE-II 100 40

PETC0352 Dissertation Phase-II

- - - 4 ESE(OE) 100 40

TOTAL - 12

Semester IV

Course Code Subject Teaching Scheme

Evaluation Scheme

L T P Credit Scheme Weightage

Max Min

PETC0453 Dissertation Phase- III

- - - 4 ISE III 100 40

- - - 4 ISE IV 100 40

PETC0454 Dissertation Phase-IV

- - - 8 ESE(OE) 200 80

Total 16

Course Code** Professional Elective-I Course Code** Professional Elective-II

PETC0121 Embedded System Programming PETC0124 Wireless Sensor Network

PETC0122 Fiber Optic Communication PETC0125 Radiating System

PETC0123 IOT Protocols & Application PETC0126 Optimization Techniques

Course Code** Professional Elective-III Course Code** Professional Elective-IV

PETC0221 Advances in Network Security PETC0224 RF IC Design

PETC0222 Adhoc Network PETC0225 Communication Protocol Design

PETC0223 Internet Traffic Engineering PETC0226 SoC Design and Verification

Kolhapur Institute of Technology’s College of Engineering, Kolhapur

Program Credit Distribution

Curriculum Component Credits

Professional Core 23

Professional Electives 18

Lab courses 4

Seminar and Mini Project 3

Industrial training 2

Dissertation 26

Total 76

23(31%)

18(24%) 4(5%)

2(3%)

2(3%)

26(35%)

Credits

Credit courses

Professional Electives

Lab courses

Seminar

Industrial training

Dissertation

Title of the Course: Next Generation Network Systems

Course Code : PETC0101

L T P Credit

3 1 - 4

Course Pre-Requisite: Computer Networks ,Wireless Networks ,Mobile Communication

Course Description: This course helps students to understand NGN along with new features.It will

help to learn technical, economic and service advantages of next generation networks. It will help to understand basic architecture of a next generation network (NGN) with reference to

mobile computing.

Course Objectives: 1. To learn the technical, economic and service advantages of next generation networks.

2. To learn the basic architecture of a next generation network (NGN) with reference to mobile computing

3. To learn the role of (IMS), network attachment and VoIP 4. To learn and compare the various methods of providing connection-oriented services over a

NGN with reference to MPLS, SMS and GSM

Course Learning Outcomes:

1. To be able to learn architecture of mobile computing and its design considertion. 2. To be able to compare emerging technologies of mobile computing over telephony and GSM.

3. To be able to learn SMS and GPRS features 4. To be able to compare various VoIP and IMS technologies

CO After the completion of the course the student

should be able to Bloom’s Cognitive

level Descriptor

CO1 Apply Design consideartions of mobile

computing methods

Application Cognitive

CO2 Classify emerging Technologies of mobile

computing over telephony

Complex

Response

Psychomotor

CO3 Differentiate SMS and GPRS features Application Cognitive

CO4 Apply VoIP and IMS applications Comprehension Cognitive

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 2

CO2 1 2

CO3 3

CO4 3 3

Assessments :

Teacher Assessment:

Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.

Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50

ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc. MSE: Assessment is based on 50% of course content (Normally first three modules)

ESE: Assessment is based on 100% course content with60-70% weightage for course content

(normally last three modules) covered after MSE.

Course Contents:

Unit 1:--- Global System for mobile Communication(GSM)

GSM architecture, GSM entities, call routing in GSM, PLMN interface, GSM addresses and identifiers, network aspects in GSM,GSM frequency allocation,

authentication and security.

-6- Hrs.

Unit 2:--- General Packet Radio Service (GPRS)

General packet radio service(GPRS) GPRS and packet data network, GPRS

network architecture, GPRS network operation, data services in GPRS, Applications of GPRS, Billing and charging in GPRS

-7- Hrs

Unit 3:--- IS 95 & WLAN

IS 95- Architecture,Channel Structure, Call Processing,Channel Capacity, Wireless LAN Architecture- Types, Adhoc and Infrasture Mode, Deploying

wireless LAN

-8- Hrs.

Unit 4 - Wireless Application Protocol

WAP, WAP Application Enviroment, Wireless Session Protocol,MMS- Architecture, Transaction Flow

-7- Hrs.

Unit 5:--- Voice over IP and IMS

Voice over IP,H.323 framework for voice over IP,SIP,Real time Protocol,Call Routing – SIP to PSTN to SIP, IMS

-6- Hrs.

Unit 6 – Security Issues

Attacks, Symmetric Key Cryptography, DES, Public Key Cryptography, Security

Protocols

-6- Hrs

Textbooks:

1. Mobile Computing , Asoke K Telukder, Roopa R Yavagal, TMH

2. Mobile Communications, Jochen Schiller, Pearson

References:

1.Next Generation Telecommunications Networks, Services, and Management by Thomas Plevyak,

VeliSahin, ISBN: 978-0-470-57528-4 , Wiley-IEEE Press 2. Next Generation Wireless Systems and Networks: Hsiao – Hwa Chen, Mohsen Guizani – Wiley

Unit wise Measurable students Learning Outcomes:

Unit1

UO1: Student should be able to understand basic concepts of Mobile Computing and architecture Unit2

UO2: Student should be able to understand different emerging Technolgy Unit3

UO3: Student should be able to understand basic concepts of GSM. Unit4

UO4: Student should be able to understand different Features of SMS

Unit5

UO5: Student should be able to understand basic concepts GPRS Unit6

UO6: Student should be able to understand basic concepts of VoIP,IMS and MPLS

Title of the Course: Engineering Linear Algebra

Course Code: PETC0102

L T P Credit

3 0 2 3

Course Pre-Requisite: Engineering Mathematics, MATLAB, Matrix Algebra.

Course Description: This course helps students to develop understanding and apply the concept in linear algebra including systems of linear equations and their solutions, Matrices and their properties

, Determinants and their properties, Vector Spaces, Linear Impedance of Vectors, Subspaces, basis and dimensions of vector spaces, inner product space, Linear transformation, Eigen values and Eigen

vectors.

Course Objectives: To Understand the algebraic structures and Linear Transformations.

To Understand the concept of Metric Space and Hilbert Space.

To Evaluate Orthogonality and Eigen values. To Evaluate Engineering problems using Algebraic Theorems.


CO After the completion of the course the student should be able to

CO1 Understand the algebraic structures and Linear Transformations.

CO2 Understand the concept of Metric Space and Hilbert Space.

CO3 Evaluate Orthogonality and Eigen values.

CO4 Evaluate Engineering problems using Algebraic Theorems.

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 2

CO2 2

CO3 2

CO4 2

Assessments :

Teacher Assessment:


Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50


ESE: Assessment is based on 100% course content with60-70% weightage for course content (normally last three modules) covered after MSE.

Course Contents:

UNIT 1 ALGEBRAIC STRUCTURES: -

Sets, Functions, Cardinality of sets, Groups, Rings, Fields, Vector spaces, Subspaces, Basis

and dimension, Finite and infinite dimensional vector spaces.

-5- Hrs.

UNIT 2: VECTOR SPACES AND LINEAR TRANSFORMATIONS (7 hours) Definition and examples – Subspaces – Linear independence – Basis and dimensions –

-7- Hrs.

Change of basis – Row space and Column space – Linear transformations: Definition –

Matrix representations, Sum, product and inverse of Linear Transformations, Rank-

nullity theorem, Isomorphism.

UNIT III – METRIC SPACE AND HILBERT SPACE (7 hours)

Metric space, Open sets, Closed sets, Neighborhoods, Sequences , Convergence,

Completeness, Continuous mappings, Normed space, Lp space and lp space, Hilbert

space, Signal space, Properties of inner product space, Orthogonal compliments and direct sums, Projections.

-7- Hrs.

UNIT IV - ORTHOGONALITY AND EIGENVALUES (9 hours)

The Scalar product in R – Orthogonal subspace – Least squares problem

Orthonormal sets – The Gram-Schmidt Orthogonalization procedure – Orthogonal

polynomials – Eigenvalues and Eigenvectors – Systems of Linear differential

equations – Diagonalization – Hermitian matrices – The Singular Value

Decomposition – Quadratic forms – Positive defnite matrices – Non-negative

matrices.

-9- Hrs.

UNIT V - NUMERICAL LINEAR ALGEBRA (7 hours) Floating point numbers – Gaussian elimination – Pivoting strategies – Matrix norms

and Condition numbers – Orthogonal transformations – The Eigenvalue problem –

Least squares problem.

-7- Hrs.

UNIT VI - ITERATIVE METHODS AND CANONICAL FORMS (7 hours) Power method – Inverse power method – Inverse power method with shifts –

Iterative method for finding eigen values – Jordan canonical form

-7- Hrs.

References:

1. Gilbert Strang (2009),” Introduction to Linear algebra”, Fourth edition, Wesley Cambridge Press, MA, USA.

2. Keith Mathews (1998), “Elementary Linear algebra”, University of Queensland, Australia. 3. Jim Hefferon (2001),” Linear algebra”, Saint Michael’s college, Vermont, USA. 4. Steven J. Leon (2009): “Linear algebra and its applications,” Eighth edition, Prentice Hall

Inc., NY, USA. 5. Hoffman Kenneth and Kunze Ray, Linear Algebra, Prentice Hall of India

6. Erwin Kreyzig, Introductory Functional Analysis with Applications, John Wiley, 2006. 7. G.F.Simmons, Topology and Modern Analysis , McGraw Hill 8. Frazier, Michael W. An Introduction to Wavelets through Linear Algebra, Springer

Publications. 9. Jin Ho Kwak & Sungpyo Hong, Linear Algebra, Springer International, 2004


Unit1

UO1: Students will able to understand Algebraic Structures Unit2

UO2: Students will able to work on Vector Spaces and Linear Transformations

Unit3

UO3: Students will understand Metric Space And Hilbert Space

Unit4

UO4: Student will understand the concept of Orthogonality and Eigenvalues

Unit5

UO5: Student will know the Numerical Linear Algebra Unit6

UO6: Student will able to understand Iterative Methods And Canonical Forms

Title of the Course: Random Process and Stochastic Process


L T P Credit

4 -- 2 5

Course Pre-Requisite: MATLAB, Digital Signal Processing

Course Description: This course helps students to develop understanding and apply the concept of Probability Discrete Random Variable, Continuous Random Variable. The student will be able to

evaluate Moments of Random Variable and understand types of Random Processes. The student will be able to apply Markov chains technique with continuous state space. The student will be able

to apply Queuing Theory with single or Multi server system to solve everyday problems.

Course Objectives: 1.Students should develop the logical concepts of probability theory.

2. Students should understand basic concepts of Random variables & Random Processes 3. Students should study the concepts of Markov Chains ,state-space analysis and Queuing Theory



should be able to

Bloom’s Cognitive

level Descriptor

CO1 apply Probability concepts and statistical

measures to solve Problems.


CO2 classify Continuous and Discrete multiple Random Variables

Complex

Response

Psychomotor

CO3 differentiate between various Random Processes. Application Cognitive

CO4 apply Markov Chain & Queuing Theory to solve Problems

Comprehension Cognitive

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 2

CO2 3

CO3 3 3

CO4 3 3

Assessments :

Teacher Assessment:


Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50



Course Contents:

Unit 1:--- Probability Theory: The concept of Probability; the axioms of Probability; sample space and events; Conditional probability and Baye’s theorem, Independence of events, Bernoulli trails.

-6- Hrs.

Unit 2:--- Random variables: Introduction to Random Variables, Discrete Random Variable, Continuous Random Variable, Expectation of Random Variable, Moments of Random Variable(mean, mode

variance, skewness, Kurtosis)

-7- Hrs.

Unit 3:--- Multiple Random Variables: cumulative distribution function and probability density function of single and multiple

Random Variables, statistical properties, Jointly distributed Gaussian random variables, Conditional probability density, properties of sum of random variables, Central limit

theorem, Estimate of population means, Expected value and variance and covariance.

-8- Hrs.

Unit 4:--- Random Processes: Classification of Processes; Properties, Auto correlation and cross correlation

function; Estimate of auto correlation function. Spectral Density: Definition, Properties, white noise, Estimation of auto-correlation

function using frequency domain technique, Estimate of spectral density, cross spectral density and its estimation, coherence.

-7- Hrs.

Unit 5:--- Markov Chains: Chapman Kolmogorov equation, Classification of states, Limiting probabilities, Stability of Markov system, Reducible chains, Markov chains with continuous state

space

-6- Hrs.

Unit 6:--- Queuing Theory: Elements of Queuing System Little's Formula, M/M/1 Queue, Multi server system

-6- Hrs.

Textbooks:

1. Introduction to probability Models,(Third edition) - Sheldon M. Ross. 2. Random Signal Processing, Prof.G.V.Kumbhojkar, C.Jamanadas &Company

References:

1 Probability and Random Processes for Electrical Engg.-Alberto Lean-Garcia (Pearson

Education.) 2. Probability, Random Variables and Stochastic Processes by Athanasios Papoulis and S.

Unnikrishna Pillai, PHI, 4th Edition, 2002 3. Stochastic Processes – J. Medhi , (New Age International.)


Unit1

UO1: Student should be able to understand basic concepts of Probability , Baye’s theorem and

Bernoulli trails. Unit2

UO2: Student should be able to understand types of Random Variable and Moments of RV. Unit3

UO3: Student should be able to understand basic concepts of cumulative distribution function and probability density function of single and multiple Random Variables and statistical properties

Unit4

UO4: Student should be able to estimate Auto correlation and cross correlation

function and spectral density of Random Processes

Unit5

UO5: Student should be able to understand basic concepts of Markov chains with continuous state space and apply it.

Unit6

UO6: Student should be able to understand basic concepts of single and Multiple server Queuing

system

Embedded System Programming PETC0121

Teaching Scheme Lectures: 3 Hrs/week, Tutorial 1Hr/ week

Examination Scheme ISE-I 10, MSE 30, ISE-II10, ESE50

Course Outcomes: At the end of the course, students will demonstrate the ability to: 1. Familiarity of the embedded Linux development model. 2. Understand and create Linux BSP for a hardware platform. 3. Develop and debug applications and drivers in embedded Linux. Syllabus Contents: Chapter 1 Review of super loop and RTOS programming, Need of embedded Linux, Embedded Linux Versus Desktop Linux, Embedded Linux Distributions and porting Chapter 2 Architecture of Embedded Linux, Linux Kernel Architecture: HAL, Memory manager, Scheduler, File System, I/O and Networking subsystem, IPC, User space, Linux Start-Up Sequence Chapter 3 Board Support Package: Inserting BSP in Kernel Build Procedure, The Boot Loader Interface, Memory Map, Interrupt Management, Timers, UATRS, Power management Chapter 4 Embedded Storage: MTD, Architecture, Drivers, Embedded File System Chapter 5 Embedded Drivers: Serial, Ethernet, I2C, USB, Timer, Kernel Modules Porting Applications Chapter 6 Introduction to BeagleBone hardware platform, Introduction to Raspberry PI hardware platform, Programming hardware resources of any of above boards using programming languages Text books:

1. P Raghvan, Amol Lad, SriramNeelakandan, “Embedded Linux System Design and Development”, Auerbach Publications

2. Derek Molloy, “Exploring BeagleBone: Tools and Techniques for Building with Embedded Linux”, Wiley, 1st Edition, 2014.

3. References:

1. Karim Yaghmour, “Building Embededd Linux Systems”, O'Reilly & Associates 2. Christopher Hallinan, “Embedded Linux Primer: A Practical Real World Approach”,

Prentice Hall, 2nd Edition, 2010. 3. Mastering Embedded Linux Programming.

Title of the Course: Fiber Optical communication Course Code: PETC122

L T P Credit

3 1 -- 4

Course Pre-Requisite: Knowledge of wave propagation in different media

Course Description:

The content in this course is designed to cover a one semester course at the post graduate level.

After providing the basic foundation of fiber optic communication, the course covers the

advanced topics like the power penalty in a link, fiber amplifiers like the EDFA and Raman

Amplifiers, non-linear fiber optics, optical switches and routers, dispersion compensators, DWDM

systems, wavelength routed optical networks, optical CDMA systems, etc.

Course Objectives:

On completion of this course you should be able to:

1. Explain the principles of operation of various optical fibre communication systems. 2. Analyze the performance of various digital and analogue optical fibre systems.

3. Calculate various key parameters of optical fibre systems. These include the system optical power budget and system rise time budget, receiver noise power, Q factor, bit error rate and

maximum usable bit rate of a digital optical fibre system. 4. Explain/compare the factors affecting the performance of different optical fibre

communication systems.


1. The students will be able to analyze the optical fiber components.

2. They will have understood the basic concepts of optical communication

3. Able to evaluate different parameters of the optical fiber.

CO After the completion of the course the

student should be able to

Bloom’s Cognitive

level Descriptor

CO1 C205.1 Recognize and classify the structures of

Optical fiber and types, the channel impairments like losses and dispersion.

II Understanding

CO2 C205.3 Analyze various coupling losses. VI Creating

CO3 C205. Classify the Optical sources and detectors and

to discuss their principle IV Analyzing

CO4 C205.5. Familiar with Design considerations of

fiber optic systems. VI Creating

CO5 C205.5. Measure characteristics of optical fiber,

sources and detectors, design as well as conduct experiments in software and hardware, analyze the

results to provide valid conclusions.

V Evaluating

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 2

CO2 3

CO3 1

CO4 3

CO5 2 21

Assessments :

Teacher Assessment:


Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50



Course Contents:

Unit 1:--- OPTICAL FIBERS Basic principles of light propagation, Optical fibers - modal propagation, ray model, wave model.

08 Hrs.

Unit 2:--- SIGNAL DISTORTION ON OPTICAL FIBERS. Attenuation and dispersion

08 Hrs.

Unit 3:--- FBG BASED DEVICES

Principle, Frequency Response of a Uniform FBG, Non-Uniform Fiber Bragg Grating, Narrow Band Filter, Add-Drop Multiplexer, Dispersion, Compensator Gain Equalizer, Mode Converter, Sensor, integrated optics, non-linear fiber optics

07 Hrs.

Unit 4:--- OPTICAL SOURCES AND RECEIVERS LED, Lasers, photo receivers

08 Hrs.

Unit 5:--- SONET/SDH AND OPTICAL LINK DESIGN

SONET/SDH, DWDM, optical switches, Optical link design, power penalty etc

08 Hrs.

Unit 6:--- OPTICAL AMPLIFIERS AND WDM NETWORKS

Fiber Amplifiers, EDFA, Raman ,DRA, WDM networks and components and Optical

CDAMA

07 Hrs.

Textbooks: 1. J.E. Midwinter, Optical fibers for transmission, John Wiley, 1979.

2.T. Tamir, Integrated optics, (Topics in Applied Physics Vol.7), Springer-Verlag, 1975.

3. Optical Fiber Communications– – John M. Senior, Pearson Education. 3rd Impression, 20073. 4.Ghatak & K. Thygarajan, Introduction to Fiber Optics, Cambridge, 1999. 5.S.E. Miller and A.G. Chynoweth, eds., Optical fibres telecommunications, Academic Press, 1979.

6.G.Agrawal, Nonlinear fibre optics, Academic Press, 2nd Ed. 1994.

7.F.C. Allard, Fiber Optics Handbook for engineers and scientists, McGraw Hill, New York (1990).

References:

1. Fiber optics communication by G.P Agrawal.

2. Optical Fiber Communication by G. Keiser.

3. Raman Amplifiers for communications by M.N. Islam (Ed).


1. Comprehend the principles of ray theory. 2. Apply the fundamentals of optics to analyze the performance of optical fibers. 3. Compare and contrast difference between different optical fibers. (L3) 4. Classify the transmitters and receivers in optical communication. (L4 and L5) 5. Test, debug and evaluate the performance of a typical optical fiber 6. Work in team to prepare a report based on survey of flux budget, link budget in optical comm.

Title of the Course: INTERNET OF THINGS


L T P Credit

3 1 - 4

Course Pre-Requisite: :Fundamentals of Computer Network, Computer Network

Course Description: This course looks at the Internet of Things (IoT) as the general theme of physical/real-world things becoming

increasingly visible and actionable via Internet and Web technologies. The goal of the course is to look top-down as well as bottom-up, to provide students with a comprehensive understanding of the IoT.

Course Objectives:

1. To understand what Internet of Things is.

2. To get basic knowledge of RFID Technology, Sensor Technology and Satellite Technology. 3. To

make students aware of resource management and security issues in Internet of Things.

Course Learning Outcomes: 1. 1. Explain what Internet of Thins is. 2. 2. Describe key technologies in Internet of Things. 3. 3. Understand wireless sensor network architecture and its framework along with WSN applications. 4. 4. Explain resource management in the Internet of Things. 5. 5. Understand business models for the Internet of Things.

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 3 3

CO2 1 2

CO3 3 2 2

CO4 2 1 2

CO5 2 3

Assessments :

Teacher Assessment:


Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50



Course Contents:

Unit 1

Internet/Web and Networking Basics OSI Model, Data transfer referred with OSI Model, IP

Addressing, Point to Point Data transfer, Point to Multi Point Data transfer & Network

Topologies, Sub-netting, Network Topologies referred with Web, Introduction to Web

Servers, Introduction to Cloud Computing IoT Platform overview Overview of IoT supported

Hardware platforms such as: Raspberry pi, ARM Cortex Processors, Arduino and Intel

Galileo boards. Network Fundamentals: Overview and working principle of Wired

Networking equipment’s – Router, Switches, Overview and working principle of Wireless

Networking equipment’s – Access Points, Hubs etc. Linux Network configuration Concepts:

Networking configurations in Linux Accessing Hardware & Device Files interactions.

12Hrs.

Unit 2: IoT Architecture:

History of IoT, M2M – Machine to Machine, Web of Things, IoT protocols Applications: Remote

Monitoring & Sensing, Remote Controlling,Performance Analysis The Architecture The Layering

concepts , IoT Communication Pattern, IoT protocol Architecture, The 6LoWPAN Security aspects

in IoT

8 Hrs.

Unit 3 IoT Application Development:

Application Protocols MQTT, REST/HTTP,CoAP, MySQL

Back-end Application Designing Apache for handling HTTP Requests, PHP & MySQL for data

processing, MongoDB Object type Database, HTML, CSS & jQuery for UI Designing, JSON lib for

data processing, Security & Privacy during development, Application Development for mobile

Platforms: Overview of Android / IOS App Development tools

13Hrs.

Unit 4Case Study & advanced IoT Applications:

IoT applications in home, infrastructures, buildings, security, Industries, Home appliances, other

IoT electronic equipments. Use of Big Data and Visualization in IoT, Industry 4.0 concepts.

Sensors and sensor Node and interfacing using any Embedded target boards (Raspberry Pi / Intel

Galileo/ARM Cortex/ Arduino)

6Hrs.

Textbooks: 1. 6LoWPAN: The Wireless Embedded Internet, Zach Shelby, Carsten Bormann, Wiley 2. Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems, Dr. Ovidiu Vermesan, Dr. Peter Friess, River Publishers 3. Interconnecting Smart Objects with IP: The Next Internet, Jean-Philippe Vasseur, Adam Dunkels, Morgan Kuffmann

REFERENCES:

1. The Internet of Things: From RFID to the Next-Generation Pervasive Networked Lu Yan, Yan Zhang,

Laurence T. Yang, Huansheng Ning

2. Internet of Things (A Hands-on-Approach) , Vijay Madisetti , Arshdeep Bahga

3. Designing the Internet of Things , Adrian McEwen (Author), Hakim Cassimally

4. Asoke K Talukder and Roopa R Yavagal, “Mobile Computing,” Tata McGraw Hill, 2010.

5. Computer Networks; By: Tanenbaum, Andrew S; Pearson Education Pte. Ltd., Delhi, 4 th Edition

6. Data and Computer Communications; By: Stallings, William; Pearson Education Pte. Ltd., Delhi, 6th

Edition

7. F. Adelstein and S.K.S. Gupta, “Fundamentals of Mobile and Pervasive Computing,” McGraw Hill, 2009. 8.

Cloud Computing Bible, Barrie Sosinsky, Wiley-India, 2010


Title of the Course: Wireless Sensor Networks


L T P Credit

3 1 -- 4

Course Pre-Requisite: Digital Communication, Wireless Communication Network, MATLAB

Course Description: This course helps student to understand wireless sensor networking protocols architectures, hardware and software tools and standards. This course helps to understand hardware details of different types of sensors in order to select right type of sensor for various applications

Course Objectives: 1.To acquire fundamental knowledge of Wireless Sensor Network.

2 To study the different types of sensors

3 To understand the basic concepts of radio standards and communication protocols used by wireless sensor network based systems

4. To study capacity of wireless channels and multiple antenna system

5. To understand operating systems and programming languages for wireless sensor nodes 6. To understand issues like energy conservation and security challenges.



should be able to

Bloom’s Cognitive

level Descriptor

CO1 Explain basic concepts and technologies used in wireless sensor networks.

I Cognitive

Explain

CO2 Design various types of sensor motes for different real life applications.

III Psychomotor

Design

CO3 Understand and remember radio standards and communication protocols used by wireless sensor network based systems.

II Cognitive

Understand

CO4 Classify Operating systems for wireless sensor networks and design

II Affective

Classify

CO-PO Mapping:

CO PO I PO II PO III

CO1

CO2

CO3

CO4

CO4

CO5

CO6

Assessments :

Teacher Assessment:

Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one

EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.

Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50

ISE 1 and ISE 2 are based on assignment/declared test/quiz/seminar/Group Discussions etc.

MSE: Assessment is based on 50% of course content (Normally first three modules) ESE: Assessment is based on 100% course content with60-70% weightage for course content


Course Contents:

Unit 1:--- Introduction and overview

Introduction and overview: basic building blocks of sensor node, functionality of a sensor

node, characteristics of a sensor node in WSN, WSN architecture, topologies, and applications.WSN v/s Adhoc networks, IOT and applications of IOT.

-6- Hrs.

Unit 2:--- Main Features of WSN

Simulation and experimental platforms; main features of WSNs; Research issues and trends, Sensor deployment mechanisms, coverage issues

-6- Hrs.

Unit 3:--- Protocols for sensor networks Routing Protocols for Wireless Sensor Networks- Routing Challenges and Design Issues

in Wireless Sensor Networks, Routing Strategies in Wireless Sensor Networks, Transport

Control Protocols for Wireless Sensor Networks. Enabling technologies, Fundamentals of 802.15.4, Bluetooth, and UWB; Physical and

MAC layers; node discovery protocols, Network layer protocols

-6- Hrs.

Unit 4:--- Sensor Node hardware Sensor node hardware : mica2, micaZ, telosB, cricket, Imote2, tmote, btnode, and Sun SPOT

-8- Hrs.

Unit 5:---Sensor Node Software Operating Systems for Wireless Sensor Networks-Operating System Design Issues, Examples of Operating Systems, TinyOS, Mate, MagnetOS, MANTIS, Contiki, RetOS and PicOS, Programming tools: C, nesC

-8- Hrs.

Unit 6:--- Data dissemination and processing

Data dissemination and processing: Data Dissemination and Gathering, multi-hop and

cluster based protocols; routing. Middleware and application layers, Data dissemination; data storage; query processing; sensor Web; sensor Grid, Open issues for future research,

Energy preservation and efficiency; security challenges; fault-tolerance, different case

studies

-6- Hrs.

Textbooks:

1. Protocols and Architectures for Wireless Sensor Networks by . H. Karl and A. Willig. John

Wiley & Sons, June 2005.

2. Wireless Sensor Networks: Technology, Protocols, and Applications by . K. Sohraby, D.

Minoli, and T. Znati. John Wiley & Sons, March 2007

References: 1. Wireless Sensor Networks by . C. S. Raghavendra, K. M. Sivalingam, and T. Znati, Editors. Springer

Verlag, Sep. 2006. 2. Wireless Sensor Networks: Architectures and Protocols by . E. H. Callaway, Jr.

AUERBACH, Aug. 2003. 3.Networking Wireless Sensors by B. Krishnamachari. Cambridge University Press, Dec. 2005.

4.Wireless Sensor Networks: An Information Processing Approach by . F. Zhao and L.Guibas. Morgan

Kaufmann, Jul. 2004. 5. Sensor Networks and Configuration: Fundamentals, Standards, Platforms, and Applications by . N. P.

Mahalik. Springer Verlag, Nov. 2006

6.Wireless Sensor Networks: A Systems Perspective by , N. Bulusu and S. Jha, Editors, Artech House, August 2005


Unit1

UO1: Student should be able to understand basic concepts of wireless sensor network protocols and

architecture

Unit2

UO2: Student should be able to understand the different simulation platforms for WSN. Unit 3

UO3.1: Student should be able to understand MAC and routing protocols Unit 4

UO4.1: Student should be able to understand basic concepts of various Sensor node hardware Unit 5

UO5.1: Student should be able to understand basic concepts of Sensor Node Software and Programming tools

UO5.2: : Student should be able to understand basic concepts of Sensor deployment mechanisms

Unit 6

UO6.1: Student should be able to understand basic concepts of Data dissemination and processing

Title of the Course: RADIATING SYSTEMS Course Code:PETC0125

L T P Credit

4 1 - 5

Course Pre-Requisite: Knowledge of wave propagation in different media

Course Description:

The purpose of introducing this course is to describe the advanced design principles used in the radiating systems. By undergoing this course, the student will learn to analyze and design different types of antennas.

Course Objectives:

On completion of this course you should be able to:

5. Understanding of the different types of antennas and sources of radiation. 6. Knowledge of the concepts of antenna synthesis techniques.

7. Understanding of the concept of microstrip antennas. 8. Learning the various methods of antenna measurements.

9. Studying Smart antennas for wireless systems.


4. The students will be able to analyze the optical fiber components.

5. They will have understood the basic concepts of optical communication

6. Able to evaluate different parameters of the optical fiber..



Bloom’s Cognitive

level Descriptor

CO1 C205.1 Recognize and classify the various types of

antennas II Understanding

CO2 C205.3 Analyze antenna parameters. VI Creating

CO3 C205.5. Design the antenna as per specifications VI Creating

CO4 C205.5. Measure characteristics of different

antennas V Evaluating

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 2

CO2 2

CO3 3

CO4 1 2

Assessments :

Teacher Assessment:


End Semester Examination (ESE) having 20%, 30% and 50% weights respectively.

Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50




Course Contents:

Unit 1:--- FUNDAMENTAL PARAMETERS OF ANTENNAS Introduction, Radiation Pattern, Radiation Power Density, Radiation Intensity, Beamwidth, Directivity, Numerical Techniques, Antenna Efficiency, Gain, Beam Efficiency, Bandwidth, Polarization, Input Impedance, Antenna Radiation Efficiency, Antenna Vector Effective Length and Equivalent Areas, Maximum Directivity and Maximum Effective Area, Friis Transmission Equation and Radar Range Equation, Antenna Temperature

04 Hrs.

Unit 2:--- LINEAR WIRE ANTENNAS Introduction, Infinitesimal Dipole, Small Dipole, Region Separation, Finite Length Dipole, Half-Wavelength Dipole, Linear Elements Near or on Infinite Perfect Conductors, Ground Effects, Computer Codes

08 Hrs.

Unit 3:--- LOOP ANTENNAS

Introduction, Small Circular Loop, Circular Loop of Constant Current, Circular Loop with Non-uniform Current, Ground and Earth Curvature Effects for Circular Loops, Polygonal Loop Antennas, Ferrite Loop, Mobile Communication Systems Applications

06 Hrs.

Unit 4:--- HORN ANTENNAS, REFLECTOR ANTENNAS Introduction, E-Plane Sectoral Horn, H-Plane Sectoral Horn, Pyramidal Horn, Conical Horn, Corrugated Horn, Introduction, Plane Reflector, Corner Reflector, Parabolic Reflector, Spherical Reflector

07 Hrs.

Unit 5:--- SMART ANTENNAS

Introduction, Smart-Antenna Analogy, Cellular Radio Systems Evolution, Signal Propagation,

Smart Antennas’ Benefits, Smart Antennas’ Drawbacks, , Antenna Beam forming, Mobile Ad hoc

Networks (MANETs), Smart-Antenna System Design, Simulation, and Results

07 Hrs.

Unit 6:--- ANTENNA MEASUREMENTS

Introduction, Antenna Ranges, Radiation Patterns, Gain Measurements, Directivity

Measurements, Radiation Efficiency, Impedance Measurements, Current Measurements,

Polarization Measurements, Scale Model Measurements

07 Hrs.

Textbooks:

1. J.R.James and P.S.Hall, Handbook of MIcrostrip Antennas, Peter Peregrinus, 1989

2. R.C.Johnson and H.Jasik, Antennas Engineering Handbook, McGraw Hill, 1984

3. W.L.Stutzman and G.A.Thiele, Antenna Theory and Design, John Wiley & Sons,

1981

References:

1. C.A.Balanis, Antenna Theory - Analysis and Design, John Wiley & Sons, 1998

2. J.D.Kraus and R.J.Marhefka, Antennas for all Applications, McGraw Hill, 2003

3. G.Kumar and K.P.Ray, Broadband Microstrip Antennas, Artech House, 2003


1. Comprehend the principles of ray theory. 2. Apply the fundamentals of antenna parameters to analyze the performance of different antennas 3. Compare and contrast difference between different antenna types . (L3) 4. Classify the antennas. (L4 and L5) 5. Test, debug and evaluate the performance of a typical antenna. 6. Work in team to prepare a report based on survey of different btypes of antennas.

Title of the Course: Optimization Techniques


L T P Credit

3 1 -- 4

Course Pre-Requisite: MATLAB

Course Description: This course helps students to develop understanding and apply Optimization Techniques to solve Engineering Problems. Students understand the concept of linear programming,

Nonlinear programming, Geometric programming, Dynamic programming. Students learn

formulation of problem and assignment of models. Students learn to apply Genetic Algorithms.

Course Objectives:

1. Students should understand the concept of Optimization Techniques. 2.Students should understand the concept of linear programming, Nonlinear programming,

Geometric programming, Dynamic programming. 3.Students should understand the method for formulation of problem and assignment of models.

4 .Students should understand single-dimensional and Multi-dimensional Search Methods



should be

able to

Bloom’s Cognitive

level Descriptor

CO1 Apply Optimization Techniques to Engineering

Problems.


CO2 implement Linear/Nonlinear, Dynamic, Geometric programming

Complex

Response

Psychomotor

CO3 apply single-dimensional and Multi-dimensional

Search Methods in constrained and Unconstrained problem environments


CO4 distinguish assignment of models.


CO-PO Mapping:

CO a b c d e f g h i j k

CO1 H H H

CO2 M H M H H

CO3 H H L M H H

CO4 H H M H H

CO4 H H L H H

CO5 H H

CO6 M H M H H

Assessments :

Teacher Assessment:



Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50




Course Contents:

Unit 1:--- Introduction :

Historical development, Application to Engineering Problems, Statement of Optimization problems, Classification of Optimization, Multivariable optimization with and without

constraints,

-6- Hrs.

Unit 2:--- Linear Programming :

Formulation, Geometry, Graphical solution, standard and matrix form of linear

programming problems, Simplex programming and its flow chart, revised simplex algorithm, Two-phase Simplex method ,Degeneracy .

Duality in linear programming: Definition of Dual Problem, General Rules for converting any Primal into its Dual Simplex method and its flow chart. Decomposition

principle, Transportation problem.

-7- Hrs.

Unit 3:--- Nonlinear programming :

Unimodal functions, single dimensional minimization methods, Exhaustive search, Fibonnaci method, Golden section, Comparison of Elimination method, Quadrature

interpolation, Cubic interpolation , Direct root method, Random search method , Steepest decent method, Fletcher-Reeves method, David-Fletcher-Powell Method, Convex sets and

convex functions, Kuhn-Tucker conditions. convex optimization, Lagrange multipliers Convex quadratic programming: Wolfe’s

and Pivot complementary algorithms. Separable programming, Constrained Multidimensional Search Methods: Rosen’s Gradient projection method, Penalty function

method.

-8- Hrs.

Unit 4:--- Geometric programming : Problems with positive coefficients up to one degree of difficulty, Generalized method for

the positive and negative coefficients Dynamic programming: Discrete and continuous dynamic programming (simple illustrations). Multistage decision problems, computation

procedure and case studies

-7- Hrs.

Unit 5:--- Assignment Models :

Formulation of problem, Hungarian Method for Assignment Problem, Unbalanced Assignment Problems

-6- Hrs.

Unit 6:--- Genetic Algorithms:

Introduction, Representation of design variables, Representation of objective function and constraints, Genetic operators, Application procedure and case studies

-6- Hrs.

Textbooks:

1. Optimization: Theory and Practices, S.S Rao ,New Age Int. (P) Ltd. Publishers, New Delhi 2. Optimization concepts & application in Engg. -A. D. Belegundu, Tirupati R.

Chandrupatla (Pearson Edn.)

References:

1 Linear Programming and Network Flows- Mokhtar S. Bazaraa,John J. Jarvis, Hanif D.

Sherali Second Edition (Wiley Publication) 2. Chong, E.K.P.and Zak, S. H.. An Introduction to Optimization, John Wiley &Sons,N.Y.

3.Peressimi A.L., Sullivan F.E., Vhi, J.J..Mathematics of Non-linear Programming, Springer –Verlag]


Unit1

UO1: Student should be able to understand basic concepts of Multivariable optimization with and without constraints,

Unit2

UO2: Student should be able to understand basic concepts of Linear Programming

Unit3

UO3: Student should be able to understand basic concepts of single dimensional minimization

methods ,Multidimensional Search Methods Unit4

UO4: Student should be able to understand basic concepts of Dynamic programming: Discrete and continuous dynamic programming (simple illustrations). Multistage decision problems

Unit5

UO5: Student should be able to understand basic concepts of Hungarian Method for Assignment

Problem, Unbalanced Assignment Problems Unit6

UO6: Student should be able to understand basic concepts of Genetic operators and the Application procedure

Title of the Course: Research Methodology


L T P Credit

2 - - 0

Course: There are no Pre-Requisite for this course

Course Description: This course will provide an opportunity for participants to establish or advance their understanding of research through critical exploration of research language, ethics, and

approaches.

Course Objectives:

1. Defending the use of Research Methodology 2. Judging the reliability and validity of experiments

3. Perform exploratory data analysis 4. Draw conclusions from categorical data

5. Using computer-intensive methods for data analysis 6. Compare statistical models


CO After the completion of the course the student should

be able to

Bloom’s Cognitive

level Descriptor

CO1 Defend the use of Research Methodology Affective domain

Defend

CO2 Judge the reliability and validity of experiments Psychomotor Judge

CO3 perform exploratory data analysis Psychomotor analysis

CO4 draw conclusions from categorical data Psychomotor conclude

CO5 Use computer-intensive methods for data analysis Psychomotor data

analysis

CO6 Drawing conclusions from statistical test results & compare statistical models

Psychomotor compare

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 3 1 1

CO2 3 1 1

CO3 1 1 2

CO4 1 2 2

CO5 3 1 1

CO6 3 1 1

Assessments :

Teacher Assessment: One EndSemester Examination (ESE) having 100% weightage

Assessment Marks

ISE 1 -

MSE -

ISE 2 -

ESE 50

ESE: Assessment is based on 100% course content

Course Contents:

Unit I: Introduction to Research An Introduction, Meaning of Research , Objectives of Research, Motivation in

Research, Types of Research, Research Approaches , Significance of Research , Research Methods versus Methodology Research and Scientific

Method , Importance of Knowing How Research is Done , Research Process Criteria of Good Research, Problems Encountered by Researchers

5 Hrs.

Unit II Research Design Meaning of Research Design, Need for Research Design, Features of a Good

Design, Important Concepts Relating to Research Design, Different Research Designs, Basic Principles of Experimental Designs

4 Hrs.

Unit III Sampling Design

Need for sampling, Population, Sample, Normal distribution, Steps in sampling, Systematic bias and Sampling error, Characteristics of good sample design,

Probability sampling and Random sampling, Determination of sample size

4 Hrs.

Unit IV:---

Results and Analysis Importance and scientific methodology in recording results, importance of negative

results, Different ways of recording, industrial requirement, artifacts versus true results, types of analysis (analytical, objective, subjective) and cross verification,

correlation with published results, discussion, outcome as new idea, hypothesis, concept, theory, model etc

4Hrs.

Unit V : Measurement and Scaling Techniques

Introduction, Concept of measurement - Measurement of scale, Developing measurement scale, Criteria of good measurement tools, Error measurement.

Concept of Scaling, Classification, Approaches of scale construction, Types of scales - Rating scale, Ranking scale, Arbitrary scale, Differential scale, Summated

scale, Cumulative scale, Factor scale.

3 Hrs.

Unit VI: Data Collection and Analysis of Data

Collection of Primary Data, Observation Method, Interview Method, Collection of Data through Questionnaires, Collection of Data through Schedules, Difference

between Questionnaires and Schedules, Collection of Secondary Data, Selection of Appropriate Method for Data Collection, Data Processing Operations, Problems in

Processing, Elements/Types of Analysis

4 Hrs.

Textbooks: 1. Books: C. R. Kothari, “Research Methodology”, New Age international, 2004.

2. Deepak Chopra and Neena Sondhi, “Research Methodology : Concepts and cases”, Vikas Publishing House, New Delhi, 2008.

3. Ranjit Kumar, “Research Methodology: A Step by Step Guide for Beginners”, 2nd Edition, Sage Publisher, 2011.


1. Recall research terminology

2. Be aware of the ethical principles of research, ethical challenges and approval processes

3. Describe quantitative, qualitative and mixed methods approaches to research

4. Identify the components of a literature review process

5. Critically analyze published research

6. Discuss Research Methodology

Title of the Course: Random Process and Stochastic Process Course Code: PETC0131

L T P Credit

0 0 2 1


Course Description: This Laboratory course helps students to develop understanding and

apply the concept of Probability Discrete Random Variable, Continuous Random Variable to solve Numerical problems. The student will be able to evaluate Moments of Random

Variable using MATLAB and estimate parameters to differentiate Random Processes. The student will be able to apply Markov chains technique with continuous state space. The

student will be able to apply Queuing Theory with single or Multi server system to solve everyday problems.

Course Objectives:

1. Students should develop the logical concepts of probability theory. 2. Students should understand basic concepts of Random variables & Random Processes

3. Students should study the concepts of Markov Chains ,state-space analysis and Queuing Theory



should be

able to

Bloom’s Cognitive

level Descriptor

CO1 apply Probability concepts and statistical measures

to solve Problems using MATLAB.


CO2 Carry out parameter evaluation of Continuous and Discrete multiple Random Variables using

MATLAB

Complex Response

Psychomotor

CO3 differentiate between various Random Processes

using MATLAB


CO4 apply Markov Chain & Queuing Theory to solve Problems using MATLAB


CO-PO Mapping:

CO PO1 PO2 PO3

CO1 2

CO2 3

CO3 3 3

CO4 3 3

Assessments :

Teacher Assessment:

One component of In Semester Evaluation (ISE) and one End Semester Examination (ESE) having 50%, and 50% weights respectively.

Assessment Marks

ISE 50

ESE 50

ISE are based on practical performed/ Quiz/ Mini-Project assigned/ Presentation/ Group

Discussion/ Internal oral etc. ESE: Assessment is based on oral examination

Course Contents:

Experiment No. 1:--- Bernoulli Trials ( Binomial Distribution ) Aim and Objectives: Understand Binomial Distribution and Carry out Case Study

Outcomes: Mathematical proof for Case Study Theoretical Background:

Experimentation:

Results and Discussions:

Conclusion:

-2- Hrs.

Experiment No. 2:--- Study of Rayleigh Probability Density Function

Aim and Objectives: Case Study

Outcomes: PDF and CDF plot Theoretical Background:

Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 3:--- Probability density function of Gaussian distributed

random variable. Effect of changing the Mean and Standard deviation in Gaussian PDF

Aim and Objectives: Case Study

Outcomes: PDF and CDF plot

Theoretical Background:

Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 4:--- Study of autocorrelation

Aim and Objectives: Evaluate autocorrelation of Random Processes

Outcomes: autocorrelation function value in the range 0-1


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 5:--- Study of cross correlation Aim and Objectives: Evaluate cross correlation of Two Random Processes

Outcomes: cross correlation value


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 6:--- power spectral density (psd) Aim and Objectives: Evaluate power spectral density of Random Processes by

different methods

Outcomes: power spectral density


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 7:--- Study of markov chain

Aim and Objectives: Markov Chains Case Study Outcomes: Draw Transition State Diagram


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 8:--- Calculation of various statistical parameters for random signal

Aim and Objectives: Evaluate various statistical parameters for random variable

Outcomes: Mean ,Mode ,Variance, Skew Factor , Moments etc


Experimentation:


Conclusion:

-2- Hrs.

Textbooks:

1. Introduction to probability Models,(Third edition) - Sheldon M. Ross. 2. Random Signal Processing, Prof.G.V.Kumbhojkar, C.Jamanadas &Company

References:

1. Probability and Random Processes for Electrical Engg.-Alberto Lean-Garcia (Pearson

Education.) 2. Probability, Random Variables and Stochastic Processes by Athanasios Papoulis and S.

Unnikrishna Pillai, PHI, 4th Edition, 2002 3. Stochastic Processes – J. Medhi , (New Age International.)

Experiment wise Measurable students Learning Outcomes:

EO1: Student should be able to understand basic concepts of Bernoulli Trials

EO2: Student should be able to understand basic concepts of Rayleigh Probability Density

Function EO3: Student should be able to understand basic concepts of Probability density function of

Gaussian distributed random variable. EO4: Student should be able to understand basic concepts of autocorrelation of Random

Processes EO5: Student should be able to understand basic concepts of cross correlation of Two

Random Processes EO6: Student should be able to understand basic concepts of power spectral density of

Random Processes EO7: Student should be able to understand basic concepts of Markov Chains ,Transition State

Diagram

EO8: Student should be able to understand basic concepts of Mean ,Mode ,Variance, Skew

Factor , Moments etc

Title of the Course: Engineering Linear Algebra Lab Course Code: PETC0132

L T P Credit

0 0 2 1

Course Pre-Requisite: MATLAB, Basic Matrix Theory


apply Linear Algebra to solve Engineering Problems.

Course Objectives:

1. Students should Understand important Concepts of Linear Algebra.

2. Students should solve Engineering Problems using Concepts of Linear Algebra. 3. Students should use the basic techniques of matrix algebra, including finding the inverse

of an invertible matrix using Gauss-Jordan elimination.



should be able to

Bloom’s Cognitive

level Descriptor

CO1 Understand the basic ideas of vector algebra:

linear dependence and independence

Understand Cognitive

CO2 Apply to Solve Engineering Problems using

Concepts of Linear Algebra.

Apply Cognitive

CO3 Apply the basic techniques of matrix algebra, including finding the inverse of an invertible

matrix using Gauss-Jordan elimination

Apply Cognitive

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 1 3

CO2 3

CO3 3

Assessments :

Teacher Assessment:

One component of In Semester Evaluation (ISE) and one End Semester Examination (ESE)

having 50%, and 50% weights respectively.

Assessment Marks

ISE 50

ESE 50

ISE are based on practical performed/ Quiz/ Mini-Project assigned/ Presentation/ Group Discussion/ Internal oral etc.

ESE: Assessment is based on oral examination

Course Contents:

Experiment No. 1:--- Solutions of linear equation

Aim and Objectives: To Study and solutions of linear equation Outcomes:


Experimentation:


-2- Hrs.

Conclusion:

Experiment No. 2:--- Applications of system of linear equation

Aim and Objectives: To Study of applications of system of linear equation Outcomes: Theoretical Background:

Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 3:--- Vector and Matrix Differentiation Aim and Objectives: To Study of vector and matrix Differentiation

Outcomes: Theoretical Background:

Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 4:--- Dimensions

Aim and Objectives: To Study use of Dimensions Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 5:--- Nullity Theorem

Aim and Objectives: To Study Row Space and Nullity Theorem Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 6:--- Eigen Vectors Aim and Objectives: To Study of Eigen Vectors Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 7:--- Complex Eigen Vectors

Aim and Objectives: To Study of Complex Eigen Vectors Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 8:--- Project I

Aim and Objectives: To Solve Engineering Problem Using Linear Algebra. Outcomes:


Experimentation:


-2- Hrs.

Conclusion:

Experiment No. 9:--- Project II Aim and Objectives: To Solve Engineering Problem Using Linear Algebra.

Outcomes:


Experimentation:


Conclusion

-2- Hrs.

Reference Books:

1. Gilbert Strang (2009),” Introduction to Linear algebra”, Fourth edition, Wesley

Cambridge Press, MA, USA. 2. Keith Mathews (1998), “Elementary Linear algebra”, University of Queensland,

Australia. 3. Jim Hefferon (2001),” Linear algebra”, Saint Michael’s college, Vermont, USA.

4. Steven J. Leon (2009): “Linear algebra and its applications,” Eighth edition, Prentice Hall Inc., NY, USA.

5. Hoffman Kenneth and Kunze Ray, Linear Algebra, Prentice Hall of India 6. Erwin Kreyzig, Introductory Functional Analysis with Applications, John Wiley,

2006. 7. G.F.Simmons, Topology and Modern Analysis , McGraw Hill

8. Frazier, Michael W. An Introduction to Wavelets through Linear Algebra, Springer Publications.

9. Jin Ho Kwak & Sungpyo Hong, Linear Algebra, Springer International, 2004

Title of the Course: RF and Microwave Circuit Design


L T P Credit

4 - - 4

Course Pre-Requisite:

Basics of Microwave engineering and transmission lines

Course Description: This course aims to introduce design strategies for various microwave circuit like microwave filters, amplifiers and oscillators and Mixers.

Course Objectives: 1. To understand the basic concepts of microwave waveguides and transmission lines.

2. To Design the microwave active filters 3. To Design microwave active amplifiers

4. To Design microwave oscillators and Mixers


CO After the completion of the course the student should be

able to

Bloom’s Cognitive

level

CO1 Understand the basic concepts of microwave waveguides and transmission lines.

CO2 Design the microwave active filters

CO3 Design microwave active amplifiers

CO4 Design microwave oscillators and Mixers

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 - - 2

CO2 - - 3

CO3 - - 3

CO4 - - 3

Assessments : Teacher Assessment:

Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one End Semester Examination (ESE) having 20%, 30% and 50% weights respectively.

Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50



Course Contents:

Unit 1:--- Introduction to transmission lines and waveguides : Solutions for TEM waves, rectangular waveguide, circular waveguide, co-axial line, stripline, microstrip, impedance and equivalent voltage and currents, the S- matrix, ABCD matrix, SFG,

discontinuities and model analysis, waveguide excitation, introduction to smith chart,

8 Hrs.

single and double stub matching, quarter wave transformer, binomial and chebyshev

multi-section matching transformer, Bode-fano criterion

Unit 2:--- Microwave Resonators, power dividers and directional couplers: Series and parallel

resonant circuits, transmission line resonator, rectangular waveguide cavities, circular

waveguide cavities, di-electric resonators, excitation of resonators, concept of power

dividers and couplers, T-junction power divider, Wilkinson power divider, directional

coupler, quadrature hybrid, Lange coupler, 180 degree hybrid

8 Hrs

Unit 3:--- Microwave Filters: Periodic structures, filter design by image parameter method and insertion loss methods, filter transformations, filter implementation, stepped impedance LPF, coupled line filters, filters using coupled resonators

8 Hrs

Unit 4:---. Noise and Active RF components: Noise in microwave circuits, dynamic range and

inter-modulation distortion, RF diode and transistor characteristics, MMIC.

8 Hrs

Unit 5:--- Microwave amplifier design: Two port power gain, stability, single stage and

broadband transistor amplifier design, Power amplifiers.

8 Hrs

Unit 6:--- Design of microwave oscillators and mixers: RF oscillators, microwave oscillators,

oscillator phase noise, frequency multipliers, different microwave sources, mixer design.

8 Hrs

Textbooks: 1. Microwave Engineering, David M Pozar, wiley publication, 3

rd edition

References:

1. RF circuit design theory and applications, reinhold Ludwig, gene bogdanov, pearson publication 2

nd edition

2. Microwave Circuit Design: A Practical Approach Using ADS, Kyung-Whan Yeom, PHI publication

3. Advanced RF & Microwave Circuit Design: The Ultimate Guide to Superior Design By Matthew M. Radmanesh, Authorhouse publication

4. Passive RF and Microwave Integrated Circuits, Leo Maloratsky, Elsevier publication

Unit wise Measurable students Learning Outcomes: Students will be able to understand the fundamental concepts of transmission lines and waveguides

Students will be able to understand the operations Microwave Resonators, power dividers and directional couplers

Students will be able to Design Microwave Filters Students will be able to calculate Noise in Active RF components

Students will be able to design Microwave amplifier design Students will be able to design microwave oscillators and mixers

Software Defined Radio (PETC0205) Teaching Scheme:

Lectures: 4Hrs/ Week

Tutorial: 1 Hr/ Week

Examination Scheme:

ISE-I 10

MSE 30 ISE-II 10

ESE 50

Course Objectives: To understand reconfigurable Modern Radio Communication System

To understand the concept of Cognitive Radio and Spectrum sharing

To understand how SDR allows access to both PHY and MAC layer

To understand GNU Radio

Course Outcomes: Aftersuccessfully completing the course students will be able to

Compare SDR with traditional Hardware Radio HDR

Simulate modern wireless system based on OFDM, MIMO & Smart Antenna

Build experiments with evaluation kits, accessing both PHY andMAC

.

Unit I : Software Defined Radio fundamentals 6L

Introduction to SDR, Need of SDR, Principles of SDR , Basic Principle and difference in Analog

radio and SDR , SDR characteristics, required hardware specifications, Software/Hardware

platform, GNU radio -What is GNU radio, GNU Radio Architecture, Hardware Block of GNU,

GNU software , MATLAB in SDR , Radio Frequency Implementation issues, Purpose of RF

front End, Dynamic Range ,RF receiver Front End topologies, Flexibility of RF chain with

software radio, Duplexer ,Diplexer ,RF filter ,LNA ,Image reject filters , IF filters , RF Mixers

Local Oscillator , AGC, Transmitter Architecture and their issues,Sampling theorem in ADC,

Noise and distortion in RF chain, Pre-distortion

Lab Tutorials : AM/FM/BPSK/QPSK/OFDM Simulation in Matlab

Unit II: SDR Architecture 10L

Architecture of SDR-Open Architecture, Software Communication Architecture,

ADC, DAC, DAC/ADC Noise, Budget, ADC and DAC Distortion

LAB Tutorials: JTRS –Goals of SCA ,Architectural details ,SDR forum Architecture

Unit III : Smart/MIMO Antennas 10L

Smart Antenna Architecture, Vector Channel Modeling , Benefits of Smart Antenna Phased

Antenna Array Theory, Adaptive Arrays, DOA Arrays, Applying Software Radio Principles to

Antenna Systems, Beam forming for systems-Multiple Fixed Beam Antenna Array, Fully

Adaptive Array , Relative Benefits and Trade-offs OF Switched Beam and Adaptive Array,

Smart Antenna Algorithms , Hardware Implementation of Smart Antennas, MIMO -frequency,

time, sample Synchronization, Space time block coding-Space Time Filtering, Space Time

Trellis Coding .

LAB Tutorials : Principles of MIMO-OFDM

Unit IV : Digital Hardware for SDR 6L

Key hardware elements, DSP processors,Role of FPGA/CPU/GPU in SDR, Applications of FPGA

inSDR, Design Principles using FPGA, Trade –offs in using DSP, FPGA and ASIC,

PowerManagement Issues in DSP, ASIC, FPGA

Unit V : Cognitive Radio 8L

Cognitive Radio Architecture, Dynamic Access Spectrum, Spectrum Efficiency, Spectrum

Efficiency gain in SDR and CR ,Spectrum Usage, SDR as a platform for CR, OFDM as PHY

layer ,OFDM Modulator, OFDM Demodulator, OFDM Bandwidth, Benefits of OFDM in CR,

Spectrum Sensing in CR, CR Network

Unit VI : Applications of SDR 8L

Application of SDR in Advance Communication System-Case Study, Challenges and Issues,

Implementation, Parameter Estimation –Environment, Location, other factors, Vertical Handoff,

Network Interoperability.

LAB Tutorials: 1)CR for Public Safety –PSCR , Modes of PSCR, Architecture of PSCR OR

2)Beagle board based SDR 3)Embedded PCSR using GNU radio

Text Books:

1. Jeffrey.H.Reed ,Software Radio : A Modern Approach to Radio Engineering , Pearson , LPE

Reference Books:

1. Markus Dillinger ,KambizMadani ,Nancy Alonistioti, Software Defined Radio : Architectures , Systems and Functions ,Wiley

2. Tony .J. Rouphael , RF and DSP for SDR, Elsevier Newness Press ,2008 3. Dr.TajStruman ,Evaluation of SDR –Main Document

4. SDR –Handbook , 8th Edition , PENTEK 5. Bruce a. Fette , Cognitive Radio Technology, Newness, Elsevier

Title of the Course: Adaptive Signal Processing


L T P Credit

3 - - 3


1. Familiar with Signals and Systems, Digital Signal Processing 2. Familiarity with linear algebra and random process theory

Course Description: This course aims to introduce Adaptive signal processing. It concerns with

processing of signals where the processing parameters are adjusted continuously to suit time varying signal environmental conditions. It consists of adaptive linear combiner, often called adaptive filter

where the combiner (filter) coefficients are trained continuously. The course consists of development of various adaptation algorithms and assessing them in terms of convergence rate, computational

complexity, robustness against noisy data, hardware complexity, numerical stability etc.

Course Objectives:

5. To Understand Concept of Adaption. 6. To Demonstrate concepts of Wiener Filter.

7. To Explain Least mean-square Adaptive Filter 8. To Design Kalman Filter


CO After the completion of the course the student should be able to

Bloom’s Cognitive

level

CO1 Understand Concept of Adaption.

CO2 Demonstrate concepts of Wiener Filter.

CO3 Explain Least mean-square Adaptive Filter.

CO4 Design Kalman Filter.

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 3

CO2 3

CO3 2 3

CO4 3

Assessments :

Teacher Assessment: Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE) and one

End Semester Examination (ESE) having 20%, 30% and 50% weights respectively.

Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50




Course Contents:

Unit 1:--- Introduction: Adaptive systems, areas of application, general properties, open and closed loop adaption, Application of closed loop adaption, Examples of Adaptive

systems. Adaptive linear combiner.

7 Hrs.

Unit 2:--- Wiener Filters: Linear optimum filtering, principal of Orthogonality, minimum

mean square error, Linear prediction, forward and backward, Method of steepest decent.

7 Hrs

Unit 3:--- Least mean-square Adaptive Filtering: Overview of structure and operation, statistical LMS Theory, normalized least mean –square Adaptive filters, Frequency domain and subband Adaptive filters, Methods of squares, Recursive least squares Adaptive filters.

7 Hrs

Unit 4:---. Kalman Filters: Statement of kalman filter problem, the innovation process

estimation, filtering, initial conditions varients extended kalman filters. Square root

adaptive filters. Order –recursive Adaptive filter.

7 Hrs

Unit 5:--- Finite precision Effects: Quantization errors, least mean-square Algorithm,

Recursive least square Algorithm, Square root Adaptive filters, Order recursive filters, Fast

Transversal Filters. Tracking of Time varying systems.

7 Hrs

Unit 6:--- Adaptive Filters using Infinite-Duration Impulse Response structure: IIR

Adaptive filters-Output Error Method, Equation Error Method. Some Practical

Considerations, Laguerre Transversal Filters, Adaptive Laguerre Latice Filters.

7 Hrs

Textbooks: 1. “Adaptive filter Theory” Simon Haykin Fourth Edition Pearson publication

References:

1. “Adaptive Signal Processing” Bernard Widrow, Samual Stearns Pearson publication 2. “Theory and Design of Adaptive Filters” John R.Treichler et.al PHI private Publication.

Unit wise Measurable students Learning Outcomes: UO1: Explain Adaptive systems.

UO2: Design Wiener Filters UO3: Explain Least mean-square Adaptive Filtering

UO4: Demonstrate concept of Kalman Filter. UO5: Explain Finite precision Effects

UO6: Understand Concepts of Adaptive Filters using Infinite-Duration Impulse Response structure.

Title of the Course: Advances in Network Security Course Code: PETC0221

L T P Credit

3 1 - 4

Course Pre-Requisite: Knowledge about attacks on computer and network system

Course Description: This course will focus on graduate-level topics inryptography and network security, including: Symmetric Key and Public Key encryption algorithms, Digital Signatures, Certificates, Cryptanalysis, Key management

and distribution, Classical network attacks and their solutions, User authentication protocols, Transport-level security, Wireless network security, E-mail security, Web security, IP security, Distributed system security,

Firewalls and Intrusion detection systems.

Course Objectives: 1. Understand Block Chiper and DES principles 2. Understand Symmetric Encryption Methods 3. Identify network security threat 4. Understand Key Resources and management resources



should be able to

Bloom’s Cognitive

level Descriptor

CO1 Define Cryptography methods on Network Security

concepts and Application

I Remembering

CO2 Classify Symmetric and Asymmetric methods II Understanding

CO3 Apply Message authentication and Hash Functions III Applying

CO4 Analyze the attacks and methods of web security IV Analyzing

CO-PO Mapping:

CO 1 2 3

CO1 2 1

CO2 1

CO3 1

CO4 3 1 2

Assessments :

Teacher Assessment:


Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50




Course Contents:

Unit 1:--- Overview:

Services, Mechanisms, and attacks, The OSI Security Architecture, A model for network

security, Classical Encryption Techniques: Symmetric Cipher Model, Substitution Techniques, Transposition Techniques, Rotor Machines, and Steganography

05 Hrs.

Unit 2:--- Block Ciphers and the Data Encryption Standard:

Simplified DES, Block Cipher Principles, The Data Encryption Standard, The Strength of

DES, Differential Linear Cryptanalysis, Block Cipher Design Principles, Block Cipher

Modes of Operation.

06 Hrs.

Unit 3:--- Contemporary symmetric Ciphers:

Triple DES, Blowfish, RC5, Characteristics of Advanced Symmetric Block Ciphers, Confidentially

using symmetric Encryption:Placement of Encryption Function, Traffic Confidentiality, Key

Distribution, and Random Number Generation

08 Hrs.

Unit 4:--- Public Key Cryptography and RSA:

Principles of Public Key cryptosystems, The RSA Algorithm, Key Management, other Public Key

Cryptosystems key Management, Diffle-Hellman Key exchange

07 Hrs.

Unit 5:--- Message Authentication and hash functions:

Authentication Requirements, F Authentication Function, Message Authentication

Codes, Hash Functions, Security of Hash Functions and MACs. Hash Algorithms: MD5

Message Digest Algorithm, Secure Hash Algorithm. Digital signatures and Authentication

protocols: Digital signatures, Authentication protocols and Digital signature Standard

08 Hrs

Unit 6:--- Authentication Applications:

Kerberos, X. 509 Authentication Service. Electronic Mail Security: Pretty Good Privacy,

S/MIME, IP Security Overview, IP Security Architecture, Authentications, Header,

Encapsulating Security Payload, Combining Security Associations, Key Management.

Web Security: Web Security Considerations, Secure socket layer and Transport layer

security. Secure electronic transaction. System Security: Intruders, Intrusion detection,

password management. Malicious Software, Viruses, Viruses and Related Threats,

Firewalls: Firewall Design Principles, Trusted systems.

7 Hrs

Textbooks: 1] Willam Stallings, Cryptography and Network Security, Third Edition, Pearson Education

References: 1.Cbarlie Kaufman, Radia Perlman, Mike Speciner, Network Security, Private communication in a public world, Second Edition, Pearson Education Asia, 2002

2.Atul Kahate, Cryptography and Network Security, Tata McGrawhill, 2003


1. Comprehend the objectives attacks and Encryption methods(L1) 2. Apply Block Cipher Principles (L2) 3. Compare and contrast Symmentric and Assymmentric methods(L3) 4. Classify Public Key Cryptography methods (L4) 5. Test, debug and evaluate Message authentication and Hash Function (L5)

Title of the Course: Adhoc Network


L T P Credit

3 1 -- 4

Course Pre-Requisite: Digital Communication, Wireless Communication Network, Wireless Sensor

Network MATLAB

Course Description: This course helps student to understand adhoc networks, MACprotocols design issues. This course helps to understand various routing algorithms ,Transport Protocols and Ad Hoc

Wireless Internet applications

Course Objectives: 1.To acquire fundamental knowledge of adhoc networks.

2 To study the MAC Protocols: design issues

3 To understand the basic concepts of Multicast routing algorithms, hybrid routing algorithm

4. To understand adhoc transport protocols. Security issues in adhoc networks 5. To understand Ad Hoc Wireless Internet Application



should be able to

Bloom’s Cognitive

level Descriptor

CO1 design technique appropriate to adhoc network systems

Design Cognitive

CO2 apply the MAC protocols Application Cognitive

CO3 discuss protocols using Directional Antenna Comprehension Cognitive

CO4 remember Security issues in adhoc networks Remembering Cognitive

CO5 discuss special issues related to Ad Hoc Wireless

Internet

Comprehension Affective

CO-PO Mapping:

CO PO I PO II PO III

CO1 2

CO2 2

CO3 3 3

CO4 3 3

CO5 2

Assessments :

Teacher Assessment:



Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50


MSE: Assessment is based on 50% of course content (Normally first three modules)


Course Contents:

Unit 1:--- Introduction and overview Introduction to adhoc networks – definition, characteristics features, applications.

Characteristics of Wireless channel, Adhoc Mobility Models:- Indoor and out door models.

-6- Hrs.

Unit 2:--- Medium Access Protocols MAC Protocols: design issues, goals and classification. Contention based protocols- with

reservation, scheduling algorithms, protocols using directional antennas. IEEE standards: 802.11a,

802.11b, 802.11g, 802.15. HIPERLAN

-6- Hrs.

Unit 3:--- Network Protocols Routing Protocols: Design issues, goals and classification. Proactive Vs reactive routing, Unicast

routing algorithms, Multicast routing algorithms, hybrid routing algorithm, Energy aware routing

algorithm, Hierarchical Routing, QoS aware routing.

-6- Hrs.

Unit 4:--- End-End Delivery And Security

Transport layer : Issues in designing- Transport layer classification, adhoc transport protocols. Security issues in adhoc networks: issues and challenges, network security attacks, secure routing

protocols

-8- Hrs.

Unit 5:--- Cross Layer Design And Integration Of Adhoc For 4G Cross layer Design: Need for cross layer design, cross layer optimization, parameter optimization

techniques, Cross layer cautionary perspective. Integration of adhoc with Mobile IP networks.

-8- Hrs.

Unit 6:--- Ad Hoc Wireless Internet Gateways, Address mobility, Routing, Transport layer protocol, Load balancing, Pricing/billing, Provisioning of security, QoS support, Service, address, and location discovery

-6- Hrs.

Textbooks: 1. C.Siva Ram Murthy and B.S.Manoj, Ad hoc Wireless Networks Architectures and protocols, 2nd edition, Pearson Education. 2007

2. Charles E. Perkins, Ad hoc Networking, Addison – Wesley, 2000

References: 1. Stefano Basagni, Marco Conti, Silvia Giordano and Ivan stojmenovic, Mobilead hoc

networking, Wiley-IEEE press, 2004. 2. Mohammad Ilyas, The handbook of adhoc wireless networks, CRC press, 2002.

3. T. Camp, J. Boleng, and V. Davies “A Survey of Mobility Models for Ad Hoc Network

4. Research,” Wireless Commun. and Mobile Comp., Special Issue on Mobile Ad Hoc Networking Research, Trends and Applications, vol. 2, no. 5, 2002, pp. 483–502.

5. A survey of integrating IP mobility protocols and Mobile Ad hoc networks, Fekri M.

Abduljalil and Shrikant K. Bodhe, IEEE communication Survey and tutorials, v no.1 2007

6. V.T. Raisinhani and S.Iyer “Cross layer design optimization in wireless protocol stacks”Comp. communication, vol 27 no. 8, 2004.

7. V.T.Raisinhani and S.Iyer,”ÉCLAIR; An Efficient Cross-Layer Architecture for

wireless protocol stacks”,World Wireless cong., San francisco,CA,May 20044.Wireless Sensor Networks: An Information Processing Approach by . F. Zhao and L.Guibas. Morgan Kaufmann, Jul. 2004.

5. Sensor Networks and Configuration: Fundamentals, Standards, Platforms, and Applications by . N. P. Mahalik. Springer Verlag, Nov. 2006

6.Wireless Sensor Networks: A Systems Perspective by , N. Bulusu and S. Jha, Editors, Artech House,

August 2005


Unit1

UO1: Student should be able to understand basic concepts of adhoc networks Unit2

UO2: Student should be able to understand basic concepts of MAC Protocols

Unit 3

UO3.1: Student should be able to understand basic concepts of Energy aware routing algorithm, UO3.2: Student should be able to understand basic concepts of Hierarchical Routing Protocols

Unit 4 UO4.1: Student should be able to understand basic concepts of adhoc transport protocols.

Unit 5 UO5.1: Student should be able to understand Need for cross layer design Security issues in adhoc

networks Unit 6

UO6.1: Student should be able to understand basic concepts of Ad Hoc Wireless Internet

Title of the Course: Internet Traffic Engineering


L T P Credit

3 1 -- 4


Course Description:

Course Objectives:

To optimize an operational network so that performance requirements are met, yet network

resources are well utilized

To develop the platform for understanding the basics of routers and types of routers, and as

the background material to understand more details about a router’s critical functions, such as

address lookup and packet class classification,

Make students to understand forwarding capacity of a router is highly dependent on how

quickly it can determine to which interface transfer the packet i,e. algorithms for fast IP address lookup

Make student to understand algorithms for efficient packet classification to offer differentiated services based agreements

Make students to understand paradigm of QoS routing and its inherent relation to traffic engineering. Extending different routing algorithms to fit the QoS routing framework

To study applicability of MPLS for routing and traffic engineering for a set of representative

real-world problems


After successfully completing the course students will be able to

estimate traffic in the network, as well as what performance measures might be of interest in IP

networks

evaluate various IP router architectures and highlight their advantages and disadvantages.

apply algorithms to meet specifications viz: lookup speed, memory usage, scalability, and

updatability

evaluate performance requirements of a packet classification algorithm in terms of number of

memory accesses and the amount of storage requirement

use of numerical studies, to understand the implications of different routing schemes and roles

played by different network controls

student can solve set of routing and traffic engineering problems in which MPLS can be used by giving due consideration to path management, traffic assignment, network information

dissemination, and network management


student should be able to Bloom’s Cognitive

level Descriptor

CO-PO Mapping:

CO PO1 PO2 PO3

Assessments :

Teacher Assessment:



Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50




Course Contents:

Unit1:IP traffic engineering: Evolution of Traffic engineering in internet domain,

Taxonomy and recommendation for internet traffic engineering, Performance Measures

and characteristics, applications view and traffic models, Architectural frame work, link

weight determination, Duality of the MCNF Problem

6 Hrs

Unit2: Internet Routing and Router Architectures: Architectural View of the Internet,

Allocation of IP Prefixes and AS Number, Policy-Based Routing, Point of Presence,

Traffic Engineering Implications, Internet Routing Instability. Router Architectures:

Functions, Types, Elements of a Router, Packet Flow, Packet Processing: Fast Path versus

Slow Path, Router Architectures

8 Hrs

Unit 3: Analysis of IP address lookup Algorithms: Network Bottleneck, Network

Algorithmics, Strawman solutions, Thinking Algorithmically, Refining the Algorithm,

Cleaning up, Characteristics of Network Algorithms. IP Address Lookup Algorithms :

Impact, Address Aggregation, Longest Prefix Matching, Naïve Algorithms, Binary ,

Multibit and Compressing Multibit Tries

6 Hrs

Unit 4: IP Packet Filtering and Classification Search by Length Algorithms, Search by Value Approaches, Hardware Algorithms, Comparing Different Approaches IP Packet Filtering and Classification : Classification, Classification Algorithms, Naïve Solutions, Two-Dimensional Solutions, Approaches for d Dimensions

6 Hrs

Unit 5: Quality of Service Routing: QoS Attributes, Adapting Routing: A Basic

Framework. Update Frequency, Information Inaccuracy, and Impact on Routing,

Dynamic Call Routing in the PSTN, Heterogeneous Service, SingleLink Case, A General

Framework for Source-Based QoS Routing with Path Caching , Routing Protocols for

QoS Routing, QOSPF: Extension to OSPF for QoS Routing, ATM PNNI

6 Hrs

Unit 6: Routing and Traffic Engineering with MPLS: Traffic Engineering of IP/MPLS

Networks, VPN Traffic Engineering, Problem Illustration: Layer 3 VPN, LSP Path

Determination: Constrained Shortest Path Approach, LSP Path Determination: Network

Flow Modeling Approach, Layer 2 VPN Traffic Engineering, Observations and General

Modeling Framework, Routing/Traffic Engineering for Voice Over MPLS.

8 Hrs


Title of the Course: RF IC Design


L T P Credit

4 1 -- 5


Course Description:

Course Objectives:




Bloom’s Cognitive

level Descriptor

CO-PO Mapping:

CO PO1 PO2 PO3

Assessments :

Teacher Assessment:

Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE)

and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.

Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50





Course Contents:


Title of the Course: Communication Protocol Design


L T P Credit

4 1 -- 5

Course Pre-Requisite: Knowledge of Communication Protocol and network architecture

Course Description:

Course Objectives:



student should be able to Bloom’s Cognitive

level Descriptor

CO-PO Mapping:

CO PO1 PO2 PO3

Assessments :

Teacher Assessment:



Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50





Course Contents:

Unit 1:--- Communication Model: OSI and TCP/IP model, Flow control Protocols, Noisy

and Noiseless protocol, Piggybacking, HDLC

07 Hrs.

Unit 2 – IPv4, Datagrams, Fragmentation, Options, Checksum, IP over ATM, Security,IP

Package, ARP, ATMARP, ARP Package

08 Hrs.

Unit 3:--- Introduction to ICMPv4, Debugging Tools, ICMP package, Mobile IP –

Addressing, Agents, Three Phase, Ineffciency in Mobile IP

07 Hrs.

Unit 4:--- SCTP-Introduction,SCTP Services, SCTP Features, Packet Format, SCTP

Association, State transition Diagram, Flow Control

07 Hrs.

Unit 5:--- DHCP operation, Packet Format, Configuration, DNS, Name Space, DNS in

internet, Resolution, DNS messages, Types of Records, SMTP

07 Hrs.

Unit 6:--- SSH- Components,Port Forwarding,SSH packets, TFTP -

messages,Connection, Data Transfer,UDP Ports,Options, World Wide web, SNMP-

Management Components,SMI,MIB,Format and Messages

07 Hrs.

Textbooks:

References:

1, TCP/IP Protocol Suite Behrouz Fourouzan

2.Adavanced Computer Network, Dr Deven Shah,Dreamtek

3. Data Communication and Networking, Fourozon


Title of the Course: System on Chip


Unit 1: Introduction to Architectures

Introduction to System on Chip (SoC); Architectures of GPP, DSP, ASIC-semi and full custom

ASICs, Gate arrays, FPGA, CPLD; Comparison among all these Architectures on the basis of related

performance parameters

Unit 2: Fundamentals of Design

Design abstractions: Behavioral Modeling, Structural Modeling, Physical; Hardware Design Flow,

Hardware Software Co-design; Design Partitions: Data Path Unit; Control unit; Case Study of

System Design; Need of IP, Types of IP, IP Life Cycle.

Unit 3: Buses and Interconnects

Bus circuits, Bus protocol and Specifications; Logic Design for Buses, System Buses; GPIO; AXI

Bus Architecture, PCI Buses.

Unit 4: Gates and Interconnect Delay

Static Complementary Gate: Logic Levels, Inverter, Delay and Transition Time, Power

Consumption, Switch Logic; Delay through Resistive Network: Delay through RC Transmission

Line, Buffer Insertion in RC Transmission Line, Cross Talk; Delay through Resistive Network: RLC

Transmission Line, Buffer insertion in RLC Transmission Line.

Unit 5: Sequential and Subsystem Design

Sequential Design: Generic Sequential System, Clocking Disciplines,

One Phase Clocking for flip-flop, Two Phase Clocking for Latches, Power Optimization, Design

Validation, Sequential Testing; Subsystem Design: Adder, Multiplier, SRAM Cell, DRAM Cell,

Flash Memory Cell.

Unit 6: Floor Planning and Low Power Architectures

Physical Design, Blocks and Channels, Routing, Global Interconnects, Power Distribution, Decap

Capacitor, Clock Distribution Methods, Floor Planning Rules; Off Chip Connections, Packages,

Effect of Power Line Inductance, I/O Architectures and Pads; Generic IC Design Flow; Architecture

for Low Power: Gate Power Control, Data Latching, Clock Gating, Architecture Driven Voltage

Scaling.

References:

1. Wayne Wolf, “Modern VLSI Design”, Prentice Hall publication, Fourth edition.

2. ION Grout, “Digital systems design with FPGAs” Newnes Publication.

Title of the Course: Measurements and Standards in

Communication Systems


L T P Credit

2 -- --


Study of RF signal spectrum, Characteristics of RF signal, Wired and Wireless communication networks

Course Description:

The course is designed to make students aware of measurements in RF domain, use of RF equipment to carry out measurements on RF signals derived from various sources

Course Objectives: 1. Understanding measurement techniques for various parameters in communication system

2. Understanding instruments for signal analysis.

3. Understanding various standards in communication system


CO After the completion of the course the student should be

able to

Bloom’s Cognitive

level Descriptor

CO1 Select wright instruments for RF measurements

CO2 Evaluate performance parameters of communication system by physical measurements

CO3 Interpret standards in wired and wireless communication

systems

CO-PO Mapping:

CO 1 2 3 4 5 6 7 8 9 10 11 12 PSO1 PSO2

CO1 L M L M M L M L M L L L H H

CO2 M M M M M L L L L L L L H M

CO3 L M M M M

L L L L L L L M L

Assessments :

Teacher Assessment:

Two components of In Semester Evaluation (ISE), One Mid Semester Examination (MSE)

and one EndSemester Examination (ESE) having 20%, 30% and 50% weights respectively.

Assessment Marks

ISE 1 10

MSE 30

ISE 2 10

ESE 50




Course Contents:

Unit 1:--- Measurements and instruments for communication signal analysis:

Spectrum analyzer, Network analyzer and related measurements, harmonic

distortion analyzer, RF measurement issues, receiver related measurements.

8 Hrs.

Unit 2:---

Standards for communication systems: Study of IEEE 802.11 a, b and g

(Wi - fi) standards, 802.16 d and e Wi - MAX standards

8 Hrs.

Unit 3:---

Mobile communication standards 2G, 2.5G, 3G standards, current scenario

of 3G and 4G standards, GSM, EDGE, HSCSD, CDMA, WCDMA

standards, Concept of convergence of the standards towards broadband

communication

8 Hrs.

Textbooks:

Theodore S. Rappaport, Wireless communications: principles and practice, Pearson education

H. S. Kalsi, Electronic Instrumentation, Tata McGraw Hill, 2/e.

Vijay K. Garg, Joseph E. Wilkes, “Principle & Applications of GSM”, Person Education.


1 Student should be able to measure performance parameters of system under test

2 Student should be able to specify wireless LAN system for application in design

3 Students should be able analyses standards of cellular communication

Title of the Course: RF & Microwave Circuit Design Lab Course Code: PETC0233

L T P Credit

0 0 2 1

Course Pre-Requisite: MATLAB, Electromagnetic Engineering, Microwave Engineering.


apply the concept of Microwave Engineering

Course Objectives:

1. Students should understand basic concepts of Microwave Engineering

2. Students should Design Microwave Circuits. 3. Students should able to perform Experimentation on apply Microwave Circuits.



should be able to

Bloom’s Cognitive

level Descriptor

CO1 Understand concepts of Microwave Circuits Comprehension Cognitive

CO2 Apply theory to design Microwave Circuits Applying Psychomotor

CO3 Analyze the designed Microwave circuits Analysis Cognitive

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 1 3

CO2 1 3

CO3 1 3

Assessments :

Teacher Assessment:



Assessment Marks

ISE 50

ESE 50



Course Contents:

Experiment No. 1:--- Overview of Microwave Engineering

It is Expected to Perform Following Experiments as a Overview Using Virtual Lab Lab of IIT Kanpur (Separate List Enclosed)

Aim and Objectives: Overview of Microwave Engineering

Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 2:--- Microwave Resonators, Power Dividers and Directional

Couplers

-2- Hrs.

Aim and Objectives: To Study of Microwave Resonators, Power Dividers and

Directional Couplers

Outcomes:


Experimentation:


Conclusion:

Experiment No. 3:---Microwave Filters. Aim and Objectives: Design of Microwave Filters (Using CAD Tool)


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 4:--- Characteristics of Active Components. Aim and Objectives: To Study of characteristics of Active Components

Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 5:--- Microwave Amplifier

Aim and Objectives: Design of Single stage Microwave Amplifier Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 6:--- Broadband Transistor Amplifier

Aim and Objectives: To Design of Broadband Transistor Amplifier Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 7:--- Power Amplifier

Aim and Objectives: To Design of Power Amplifier

Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 8:--- Microwave Oscillators Aim and Objectives: To Design of Microwave Oscillators

Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 9:--- Structures of Adaptive Filter

Aim and Objectives: To Design of Microwave Mixers Outcomes:


Experimentation:


Conclusion

-2- Hrs.

Textbooks:

1. Microwave Engineering, David M Pozar, wiley publication, 3rd

edition

References:

1. RF circuit design theory and applications, reinhold Ludwig, gene bogdanov, pearson publication 2

nd edition

2. Microwave Circuit Design: A Practical Approach Using ADS, Kyung-Whan Yeom, PHI publication

3. Advanced RF & Microwave Circuit Design: The Ultimate Guide to Superior Design By Matthew M. Radmanesh, Authorhouse publication

4. Passive RF and Microwave Integrated Circuits, Leo Maloratsky, Elsevier publication

Title of the Course: Adaptive Signal Processing Lab Course Code: PETC0234

L T P Credit

0 0 2 1



apply the concept Adaptive Signal Processing

Course Objectives:

1. Students should understand the concept of Adaption . 2. Students should understand basic concepts of Random variables & Random Processes

3. Students should study the concepts of Markov Chains ,state-space analysis and Queuing Theory



should be

able to

Bloom’s Cognitive

level Descriptor

CO1 Understand the Basic Concepts of Adaption. Application Cognitive

CO2 Design Adaptive Filters using various algorithms. Comprehension Cognitive

CO3 Realize the Adaptive filters. Construct Psychomotor

CO-PO Mapping:

CO PO1 PO2 PO3

CO1 1 3

CO2 3

CO3 3

Assessments :

Teacher Assessment:



Assessment Marks

ISE 50

ESE 50



Course Contents:

Experiment No. 1:--- Linear Optimal Filtering

Aim and Objectives: To Study Concept Linear Optimal Filtering

Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 2:--- Steepest Decent Method

Aim and Objectives: To Study Steepest Decent Method :Case Study


-2- Hrs.

Experimentation:


Conclusion:

Experiment No. 3:--- Least Square Algorithm

Aim and Objectives: Study of Normalized Least Square Algorithm


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 4:--- Kalmans Filter Aim and Objectives: To Study Kalmans Filter

Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 5:--- Quantization Effect

Aim and Objectives: To Study Quantization Effect. Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 6:--- Principal of Orthogonality

Aim and Objectives: To Study Principal of Orthogonality. Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 7:--- To Study Recursive Least Square Algorithm. Aim and Objectives: Recursive Least Square Algorithm

Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 8:--- Transversal Filter Aim and Objectives: To Study Transversal Filter

Outcomes:


Experimentation:


Conclusion:

-2- Hrs.

Experiment No. 9:--- Structures of Adaptive Filter

Aim and Objectives: To study various structures of Adaptive Filter Outcomes:


Experimentation:


Conclusion

-2- Hrs.

Experiment No. 10:--- IIR Adaptive Filter

Aim and Objectives: To study IIR Adaptive Filter Outcomes:


Experimentation:


Conclusion

-2- Hrs.

Reference Books: Textbooks: 1. “Adaptive filter Theory” Simon Haykin Fourth Edition Pearson publication

References: 1. “Adaptive Signal Processing” Bernard Widrow, Samual Stearns Pearson publication

2. “Theory and Design of Adaptive Filters” John R.Treichler et.al PHI private

Publication.

Documents

KIT’s College of Engineering, Kolhapur. (An Autonomous Institute ...kitcoek.in/wp-content/uploads/2019/01/mtechetcsyllabus.pdf · ESE: Assessment is based on 100% course content