C. Information & Communication Engineering Core
These courses stress fundamental Information & Communication Engineering concepts (a total of 81 credit hours).
Course Number and Name Credit Hours ICE 103 Structured Programming 4 ICE 107 Object Oriented Programming 4 ICE 109 Electrical Circuits 4 ICE 204 Discrete Mathematics 3 ICE 207 Data Structures 4 ICE 213 Electronic Circuits 4 ICE 216 Signals & Systems 3 ICE 217 Digital Electronics 4 ICE 245 Algorithms 4 ICE 275 Operating Systems 3 ICE 302 Computer Communications & Networks 4 ICE 305 Database Systems 4 ICE 310 Electromagnetic Theory 3 ICE 312 Communication Theory 3 ICE 313 Microprocessors & Interfacing 4 ICE 314 Digital Communications 4 ICE 322 Digital Signal Processing 4 ICE 370 Applied Numerical Methods 3 ICE 439 Engineering Ethics 3 ICE 441 Wireless & Mobile Communications 3 ICE 473 Project Management, Entrepreneurship and Industry Interaction 3 ICE 496 Capstone Project 6 Total 81
ICE103: Structured Programming
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: None
Course Contents: Programming Language: Concept of programming language and its classification; Programming logic and flow Chart; Structured Programming using C  Constants, variables and data types, arithmetic and logical operation, loops and decision making, userdefined functions, character and strings, arrays, pointers, structures, file management. The course includes lab work based on theory taught.
Recommended Textbook:
1. The C Programming Language, Brian W. Kernighan, Dennis M. Richie.
2. Programming in ANSI C, E. Balagurusamy, McGrawHill Education.
Reference Book:
1. Schaum's Outlines Programming with C, Byron Gottfried, McGrawHill.
Course Outcomes (COs): After completion of this course students will be able to
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Apply basic knowledge of C programming language to solve engineering problems.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Apply appropriate decision making and control statements, functions, and arrays to solve engineering problems.

PO1

Cognitive/
Apply

Written Exams

Class lectures and brainstorming sessions

CO3

Apply pointers, strings, structures and unions to solve engineering problems.

PO1

Cognitive/
Apply

Written Exams, Assignment

Class lectures and brainstorming sessions

CO4

Develop and execute realistic C programs in the laboratory.

PO1

Cognitive/
Apply

Lab Reports

Conducting lab experiments

ICE107: Object Oriented Programming
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit
Hours

3

1

4

Contact
Hours

3 Hours/Week for 13 weeks+
Final Exam in the 14th week

2 hours/Week for 13 Weeks

5 Hours/Weeks for 13 Weeks+ Final Exam in the 14th week

Prerequisite: ICE103Structured Programming
Course Contents: Object Oriented Concepts: Classes, objects, methods, inheritance, and class methods.OO Programming in JAVA: Java foundation, control flow, abstract classes and packages, exception handling, applets, webbased Java application, multithreading.The course includes lab work based on theory taught.
Recommended Textbook:
1. Introduction to Java Programming, Daniel Liang, 11^{th} edition.
Reference Book:
1. The Complete Reference Java 2, Herbert Schildt, McGrawHill Osborne Media.
Course Outcomes (COs): After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Apply basic knowledge of C programming language to solve engineering problems.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO1

Apply the basic concepts such as variables, conditional and iterative execution methods to write objectoriented programs.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Implement classes, objects, invoking methods, and exception handling mechanisms to write objectoriented programs.

PO1

Cognitive/
Apply

Written Exams, Assignment

Class lectures and brainstorming sessions

CO3

Apply the principles of inheritance, polymorphism, encapsulation and abstraction to write objectoriented programs.

PO1

Cognitive/
Apply

Written Exams

Class lectures and brainstorming sessions

CO4

Develop and execute reallife objectoriented programs in the laboratory.

PO1

Cognitive/
Apply

Project reports,
Lab experiments,
Lab viva

Lab demonstration

ICE109: Electrical Circuits
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: None.
Course Contents:
Basic concept of DC circuits: Fundamental electrical concepts and measuring units, DC voltage, current, resistance and power. Introduction to circuit theory and Ohm's law, Kirchhoff's current and voltage laws. Simple resistive circuits: Series and parallel circuits, voltage and current division, WyeDelta transformation. Various techniques for solving circuit problems: Mesh and Nodal analysis. Network theorems: Superposition theorem, Source transformation, Thévenin's and Norton's theorems; maximum power transfer theorem. Energy storage elements: Inductors and capacitors, series parallel combination of inductors and capacitors.
Basic concept of AC circuits: sinusoids, phasors, impedance and admittance. Basic circuit laws for AC circuits. Nodal and mesh analysis, network theorems for AC circuits. AC power analysis: instantaneous, average, complex, apparent and reactive power due to sinusoidal excitation, RMS values, power factor calculation and improvement. Three phase circuits: balanced and unbalanced, magnetically coupled circuits and introduction to transformer. Series and parallel resonant circuits and passive filters.The course includes lab work based on theory taught.
Recommended Textbook:
1. Fundamental of Electric Circuits, Charles K Alexander and Mathew N O Sadiku, Tata, McGraw Hill.
Reference Book:
1. Introduction to Electric Circuits, RC. Dorf, John Wiley.
2. Introductory Circuit Analysis, Robert L Boylestad.
3. Introduction to Electrical Circuits, Nilsson, AddisonWesley.
Course Outcomes: After successfully completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Apply basic circuit laws, analyze techniques, and theorem to solve DC and AC circuits in steady state.

PO1

Cognitive (Comprehension)

Written test,
Assignment

Class Lectures

CO2

Evaluate DC and AC response in RL, RC, and RLC circuits.

PO1

Cognitive (Comprehension)

Written test

Class lectures and brainstorming sessions

CO3

Analyze three phase circuits in phasor domain to compute voltages, currents and powers.

PO1

Cognitive (Comprehension)

Written test

Class lectures and brainstorming sessions

CO4

Build and simulate DC and AC circuits in the laboratory.

PO1

Cognitive (Comprehension), Psychomotor

Lab Viva and lab Test, Lab performance

Conducting lab experiments

ICE204: Discrete Mathematics
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

0

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: ICE103 Structured Programming
Course Contents: Propositional logic, propositional equivalences, predicates and quantifiers, nested quantifiers, rules of inference, introduction to proofs, mathematical induction, sets, set operations, functions, relations and their properties, the basics of counting, the pigeonhole principle, permutations and combinations, algorithms, the growth functions, complexity of algorithms, the integers and division, primes and greatest common divisor, graphs, graphs terminologies and special types of graphs, representing graphs and graphs isomorphism, introduction to trees.
Recommended Textbook:
1.Discrete Mathematics, Gary Chartrand and Ping Zhang, WAVELEND PRESS INC.
Reference Book:
1. Discrete Mathematics with Applications, Susanna S. Epp.
Course Outcomes (COs): After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Explain propositional logic, predicate logic, and proving theorem with
mathematical reasoning.

PO1

Cognitive (Comprehension)

Written Exam

Class Lectures

CO2

Interpret counting, permutations, and combinations in combinatorial
analysis.

PO1

Cognitive (Comprehension)

Written Exam

Class Lectures

CO3

Comprehend the growth of functions, complexity analysis of algorithms
and integer algorithms for algorithmic thinking.

PO1

Cognitive (Comprehension)

Written Exam

Class lectures and brainstorming sessions

CO4

Apply knowledge of discrete structures to solve realistic engineering problems.

PO3

Cognitive (Application)

Written Exam and/or Assignment

Class lectures and brainstorming sessions

ICE207: Data Structures
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: ICE107 Object Oriented Programming
Course Contents: Data types, abstract data types and data structures; Efficiency of algorithms; Sequential and linked implementation of lists; Linked list and applications; Stacks and queue and applications; Tree representations and traversals, Binary heaps, binary search tree, AVL tree, Searching; Graphs, DFS and BFS, shortest path and minimum spanning tree; Internal and external sorting. The course includes lab work based on theory taught.
Recommended Textbook:
1.Data Structures and Program Design in C, Kruse, Leung and Tondo, Prentice Hall.
Reference Book:
1.Data Structure and Algorithms in Java, Robert Lafore, Sams.
Course Outcomes (COs):
After completion of this course students will be able to:
COs  CO Statements  POs  Domain  Assessment Strategy  TeachingLearning Strategy 
CO1  Understand the basics of data structures and algorithm

PO1  Cognitive (Comprehension+ Analysis)

Written Exam  Class Lectures 
CO2  Develop knowledge of different data structures, arrays, linked lists, binary trees, stack, queues, and graphs etc.

PO1  Cognitive (Analysis+ Synthesis)  Written Exam,
Assignment 
Class lectures and brainstorming sessions 
CO3  Apply knowledge of data structures to implement algorithm for the creation, insertion, deletion, searching, and sorting.  PO1  Cognitive (Comprehension+ Analysis)  Written Exam  Class lectures and brainstorming sessions 
CO4  Choose appropriate data structures as applied to specific problem definition.  PO5  Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response) 
Lab Experiments, Lab Exam, Laboratory Project, Project Report  Lab Demonstration 
ICE213: Electronic Circuits
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: ICE109
Course Contents:
Diode: Physical operation, terminal characteristics, load line analysis, circuit analysis, and its applications: rectifier, clipper, clamper.
OpAmp: Ideal opamp, inverter, noninverter, difference amplifier, integrator, differentiator, and weighted summer. Design of different amplifier and instrumentation circuits using opamps.
BJT: Physical operation, terminal characteristics, operating modes. BJT as amplifier and switch, DC biasing and small signal operations.
MOSFET: Physical operation, terminal characteristics, operating modes, biasing, amplification, small signal model, gain and MOSFET switch.
The course includes lab work based on theory taught.
Recommended Textbook:
1. Microelectronic Circuits, Sedra and Smith, Oxford University Press.
Reference Book:
1. Electronic devices and circuit theory, Robert L Boylestad, Prentice Hall.
2. Microelectronic Circuits and Devices, M. N. Horenstein, Prentice Hall.
3. The Art of Electronics, P. Horowitz and W. Hill, Cambridge University Press.
Course Outcomes:
After successful completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Explain the physical operation and terminal characteristics of diodes, BJTs and MOSFETs.

PO1

Cognitive (Comprehension)

Written Exam

Class Lectures

CO2

Apply fundamental concepts to analyze diode with DC and AC biases.

PO1

Cognitive (Application)

Written Exam

Class lectures

CO3

Apply fundamental concepts to analyze BJT and MOSFET circuits with DC and AC biases.

PO1

Cognitive (Application)

Written Exam,
Assignment

Class lectures

CO4

Apply fundamental concept to analyze simple opamp circuits.

PO1

Cognitive (Application)

Written Exam

Class lecture & Software Simulation

CO5

Build and simulate electronic circuits; and perform measurements using electronic equipment.

PO5

Cognitive (Analysis), Psychomotor

Designed lab or
open ended lab
and/ or report

Lab Demonstration

ICE216: Signals & Systems
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week


3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: MAT205 Linear Algebra & Complex Variables
Course Contents: Signals and their properties; Basic operations on signals; Different types of signals; Relation between signals and systems; Linear TimeInvariant Systems: Introduction; Convolution: Impulse Response Representation for LTI Systems; Properties of the Impulse Response Representation for LTI Systems; Differential and Difference Equation Representations for LTI Systems; Block Diagram Representations; State Variable Descriptions for LTI Systems. Fourier Representations for Signals (both continuoustime and discretetime). Application of Fourier analysis in signals. The Laplace Transform; Transform Analysis of Systems; Applications of Laplace Transform.
Recommended Textbook:
1. Signals & Systems, S. Haykin and B. Van Veen, Wiley & Sons.
2. Digital Signal Processing, S. Salivahanan and A. Vallavaraj, Tata McGraw Hill.
Reference Book:
1. Signals & Systems, Alan V. Oppenheim, Prentice Hall.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Explain the characteristics of different properties of signals and systems.

PO1

Cognitive
(Comprehension)

Written exam

Class lectures

CO2

Analyze the response of LTI systems for different excitations.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO3

Analyze the stability of LTI system.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

ICE217: Digital Electronics
Credit Hours and Teaching Scheme:

Theory 
Laboratory 
Total 
Credit Hours 
3 
1 
4 
Contact Hours 
3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week 
2 Hours/Week for 13 Weeks 
5 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week 
Prerequisite: ICE213
Course Contents:
Review of Number systems and codes; Boolean operators (NOT, AND, OR, NAND, NOR, XOR, and XNOR); Boolean algebra and logic circuits: De Morgan's Theorem; Simplification of Boolean functions using Boolean algebra and Karnaugh map. Combinational circuit analysis: Adders, Subtractor, Encoder, Decoder, Multiplexer, Demultiplexer, ROM, PLA. Sequential logic circuits Analysis: Latch, flip flops, counters, Shift Registers, Memory: Classification, capacity calculation, SRAM, DRAM. Different logic families (TTL, ECL, IIL, CMOS) and performance parameters (Fanout, Noise margin, noise immunity, power dissipation, propagation delay, delaypower product).
The course includes lab work based on theory taught.
Recommended Textbook:
1. Digital Design, M. M. Mano, Prentice Hall.
Reference Book:
1. Digital Systems – Principles and Applications, Ronald J Tocci, Prentice Hall.
2. Digital Logic Design, Dr. Mozammel Huq Azad Khan, UGC.
Course Outcomes: After successful completion of this course students will be able to
COs  CO Statements  POs  Domain  Assessment Strategy  TeachingLearning Strategy 


CO1  Synthesize logic functions using Boolean algebra, Karnaugh map, truth tables and fundamental logic gates.

PO1  Cognitive (Analysis)  Written Exam  Class Lecture 


CO2  Design combinational and sequential logic circuits based on the given problem statement incorporating different logic elements and blocks.  PO1  Cognitive (Synthesis)  Written Exam,
Assignment 
Class Lecture 


CO3  Explain the working principles of semiconductor memories and logic families.  PO1  Cognitive (Analysis)  Written Exam  Class Lecture 


CO4  Synthesize, create, and demonstrate digital systems using ICs and simulation tools.  PO5  Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response) 
Lab Experiments, Lab Exam, Laboratory Project, Project Report  Demonstration and Feedback 



CO4 




X 




























ICE245: Algorithms
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: ICE207 Data Structures
Course Contents: Complexity of Algorithms: worst case, average case, and amortized complexity. Algorithm analysis. Algorithm design paradigms. Lists: stacks, queues, implementation, garbage collection. Dictionaries: Hash tables, binary search trees, AVL trees, redblack trees, splay trees, skiplists, Btrees. Priority queues. Graphs: Shortest path algorithms, minimal spanning tree algorithms, depthfirst and breadthfirst search. Sorting: Advanced sorting methods and their analysis, lower bound on complexity, order statistics. The course includes lab work based on theory taught.
Recommended Textbook:
1. Data Structures and Program Design in C, Kruse, Leung and Tondo, PrentECE Hall.
Reference Book:
1. Data Structure and Algorithms in Java, Robert Lafore, Sams.
Course Outcomes (COs):
After completion of this course students will be able to
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Apply asymptotic analysis to estimate worstcase running times of algorithm.

PO1

Cognitive (Comprehension + Analysis)

Written Exam

Class Lectures

CO2

Derive and solve recurrences based on performance evaluated by divideandconquer paradigm and explain when an algorithmic design situation calls for it.

PO1

Cognitive (Analysis + Synthesis)

Written Exam,
Assignment

Class lectures and brainstorming sessions

CO3

Synthesize dynamicprogramming and greedy algorithms.

PO1

Cognitive (Comprehension + Analysis)

Written Exam

Class lectures and brainstorming sessions

CO4

Apply different algorithm to model engineering problems and execute them in the laboratory.

PO5

Cognitive (Application)
Psychomotor (Origination + Guided & Complex Response)

Lab Experiments, Lab Exam, Laboratory Project, Project Report

Lab Demonstration

ICE275: Operating Systems
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14th week


3 Hours/Week for 13 Weeks + Final Exam in the 14th week

Prerequisite: ICE 245 Algorithms
Course Contents: Basic concepts of operating system; Operating systems hardware interaction; Process and thread management; Inter process communication; Scheduling algorithms for multitasking; Mutual exclusion principles and deadlock handling; Memory and I/O management. Storage Management; Implementing file management;
Recommended Textbook:
1. Operating Systems: Design and Implementation, Andrew Tanenbaum and Albert S. Woodhull, Prentice Hall.
Reference Book:
1. Operating System Concepts, Silberschatz, Galvin and Gagne, Wiley.
Course Outcomes (COs):After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Understand and distinguish different components of modern operating system for examining design goals.

PO1

Cognitive (Knowledge)

Written Exam

Class Lectures

CO2

Apply resource management techniques for solving resource constrained problems.

PO2

Cognitive (Application)

Written Exam

Class lectures and brainstorming sessions

CO3

Comprehend and describe different methods of resource management and
communication for operating system performance analysis and illustrate memory organization and I/O management techniques to demonstrate and master the knowledge for realistic problem analysis.

PO2

Cognitive (Analysis)

Written Exam and/or Presentation

Class lectures and brainstorming sessions

ICE302: Computer Communications & Networks
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE245 Algorithms
Course Contents: Use of computer networks, network hardware and software; Layering, reference models and their comparison. Theoretical basis for data communication, transmission media and impairments, IEEE802.3, switching systems. Design issues, framing, MAC address, error detection and correction, elementary and sliding window protocols, examples of data link layer protocols. Ethernet, data link layer switching. Routing algorithms, congestion control, QoS, internetworking, IPv4 and IPv6 addressing, subnetting, VLSM, NAT, CIDR. Transport service, elements of transport protocols, port address, TCP and UDP. Client/server model, peer to peer model, Email, DNS, HTTP, HTTPS, FTP. The course includes lab work based on theory taught.
Recommended Textbook:
1. Computer Networks, Andrew S. Tanenbaum, Prentice Hall.
Reference Book:
1. Data and Computer Communications, Stallings, MacMillan.
Course Outcomes (COs): After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Characterize network layers and related issues for designing computer networks

PO1

Cognitive (Comprehension)

Written exam

Class Lectures

CO2

Analyze different network algorithm and protocols for effective design of computer networks

PO2

Cognitive (Analysis)

Written exam

Class lectures and brainstorming sessions

CO3

Investigate several network security algorithms and future development trends in network security for Cyberphysical system

PO4

Cognitive (Analysis)

Term paper, Assignment

Class lectures and brainstorming sessions

CO4

Use software tools to design, test and evaluate real life computer network applications.

PO5

Cognitive (Analysis),
Psychomotor

Lab Experiments, Lab Exam, Laboratory Project, Project Report

Lab Demonstration

ICE305: Database Systems
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks +Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks +Final Exam in the 14th week

Prerequisite: ICE275Operating Systems
Course Contents: Concept & Overview of DBMS, Data Models, Database Languages, Database Administrator, Database Users, Three Scheme architecture of DBMS. Basic concepts, Design Issues, Mapping Constraints, Keys, EntityRelationship Diagram, Weak Entity Sets, Extended ER features. Structure of relational Databases, Relational Algebra, Relational Calculus, Extended Relational Algebra Operations, Views, Modifications Of the Database. Concept of DDL, DML, DCL. Basic Structure, Set operations, Aggregate Functions, Null Values, Domain Constraints, Referential Integrity Constraints, assertions, views, Nested Sub queries, Database security application development using SQL, Stored procedures and triggers. Functional Dependency, Different anomalies in designing a Database., Normalization using functional dependencies, Decomposition, BoyceCode Normal Form, 3NF, Normalization using multivalued dependencies, 4NF, 5NF. File & Record Concept, Placing file records on Disk, Fixed and Variable sized Records, Types of SingleLevel Index (primary, secondary, clustering), Multilevel Indexes, Dynamic Multilevel Indexes using B tree and B+ tree.The course includes lab work based on theory taught.
Recommended Textbook:
1. Fundamentals of Database Systems, Elmasri and Navathe, Addison Wesley.
Reference Book:
1.Database System Concepts, Abraham Silberschatz, Henry Korth and S. Sudarshan, McGrawHill.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Adopt basic concepts of relational database and construct algebraic expressions.

PO1

Cognitive (Comprehension)

Written exam

Class Lectures

CO2

Analyze different query operations for data manipulation.

PO2

Cognitive (Analysis)

Written exam

Class lectures

CO3

Examine different models and optimization techniques to design efficient relational database system.

PO2

Cognitive (Analysis),

Written exam, Assignment

Class lectures and brainstorming sessions

CO4

Use software tools to build and test real life database.

PO5

Cognitive (Analysis),
Psychomotor

Lab Performance, Openended Lab Project, Lab report & Viva

Lab Demonstration

ICE310: Electromagnetic Theory
Credit Hours and Teaching Scheme:

Theory

Credit Hours

3

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: PHY 209
Course Contents:
Electrostatics: Review of vector analysis & coordinate systems (Rectangular, Cylindrical and Spherical), Divergence and curl concepts, Divergence theorem, Stoke’s theorem, Gauss’s theorem and its application, electrostatic potential, Laplace’s and Poisson’s equations, energy of an electrostatics system, conductor and dielectrics.
Magnetostatics: Concept of magnetic fields, Ampere’s law, BiotSavart’s law, Vector magnetic potential, energy of magnetostatic system, Mechanical forces and torques in electric and magnetic fields.
Maxwell’s equations: their derivations, and continuity of charges, concept of displacement current, Boundary conditions, Timevarying and timeharmonic electromagnetic fields, Wave equations and its solutions, & Poynting’s theorem, Propagation of uniform plane waves in lossy and lossless media.
Recommended Textbook:
1. Fundamental of electromagnetics, David K Cheng, Pearson.
Reference Books:
1. Advanced Engineering Electromagnetics, Constantine A Balanis, Wiley and Sons.
Course Outcomes: After successful completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Apply essential electrostatic theorems in solving various analytical & practical problems

PO2

Cognitive (Application)

Written Exam
Assignments

Class Lectures,
Brainstorming Sessions

CO2

Analyze the concepts of magnetostatic fields and the relevant laws along with their applications for different structures.

PO2

Cognitive (Analysis)

Written Exam

Class Lectures, Brainstorming sessions

CO3

Analyze Maxwell’s equations & EM Wave equations to demonstrate the propagation of EM wave along with its basic properties, polarization states and birefringence.

PO2

Cognitive (Analysis)

Written Exam
Assignments

Class Lectures
Brainstorming Sessions

CO4

Comprehend timeharmonic EM fields and the properties of timeharmonic EM waves in different types of media such as lossy and lossless dielectrics, freespace & conductors.

PO1

Cognitive (Comprehension)

Written Exam
Assignments

Class Lectures
Brainstorming Sessions

ICE312: Communications Theory
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week


3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: ICE209 Signal & Systems
Course Contents: Stochastic Processes and Signals: Introduction; Definition of random processes and signals; Autocorrelation and cross correlation of random signals; Transmission of a random signal through a linear filter; Power spectral density functions of random signals; White noise; Stationarity; Ergodicity; Gaussian and Poisson processes; Narrowband noise; Sine wave plus narrowband noise. Continuous Wave Modulation and Noise: Introduction, Amplitude modulation and demodulation; frequency modulation and demodulation; Frequencydivision multiplexing (FDM); Angle modulation; Noise in CW modulation systems; Noise in linear receivers; Noise in AM receivers; Noise in FM receivers; Phaselocked loop; Nonlinear effects in FM systems; Receiver model; Noise in DSBSC receivers; Noise in SSB receivers; Noise in AM receivers; Noise in FM receivers. Pulse Modulation: Sampling process; Pulseamplitude modulation; Time division multiplexing; Pulseposition modulation; Bandwidthnoise tradeoff; The quantization process; Pulsecode modulation; Noise consideration in PCM systems; Digital multiplexers; Linear prediction; Differential PCM; Delta modulation; Adaptive DPCM.
Recommended Textbook:
1. Communications System, Simon Haykin, Wiley.
2. Modern Digital & Analog Communication Systems, Lathi.
Reference Book:
1. Digital Communications, John J. Proakis, McGraw Hill.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Explain various fields of communication by using random process, auto correlation, crosscorrelation and PSD.

PO1

Cognitive (Comprehension)

Written test

Class Lectures

CO2

Explain different base band and pass band modulation and demodulation techniques.

PO1

Cognitive (Comprehension)

Written test

Class Lectures
and
Group Activity

CO3

Analyze noise affect in AM and FM modulation and understand PCM.

PO2

Cognitive (Analysis)

Written test or Assignment

Class Lectures

ICE313: Microprocessors & Interfacing
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: ICE217
Course Contents:
Microprocessor: Evolution and internal architecture of Intel8086 microprocessor. Addressing Modes. Data Movement Instructions, Arithmetic and Logic Instructions, Program Control Instructions. Intel 8086 Hardware Specifications: Pin outs and pin functions, clock generators, bus buffering and latching, bus timing, minimum and maximum mode operation. Memory Interfacing. Basic I/O Interfacing, Programmable Peripheral Interfaces (8255, 8254, 8279, ADC, DAC controllers). 8259 Programmable Interrupt Controller. DMA controller. Introduction to Pentium and upgraded processors. Introduction to Microcontrollers.
The course includes lab work based on theory taught.
Recommended Textbook:
1. The Inter Microprocessors 8088/8088, 80186, 80286, 80386 and 80486: Architecture, Programming and Interfacing, Barry B. Brey, PrenticeHall.
Reference Book:
1. Microprocessor and Interfacing, Douglas Hall, McGraw Hill.
Course Outcomes: After successful completion of this course students will be able to
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Explain the architecture and different modes of microprocessor.

PO1

Cognitive (Knowledge)

Written Exam

Class Lectures
and
Classwork

CO2

Explain instruction set, ALP & illustrate the use of emulator.

PO1

Cognitive (Comprehension),
Psychomotor (Origination + Guided & Complex Response)

Written Exam, Practical Assessment

Class Lectures and onspot simulation tasks

CO3

Analyze the interfacing of memory and I/O devices, interface of microprocessor with PPI.

PO2

Cognitive (Analysis)

Written Exam

Class lectures
And Brainstorming session

CO4

Comprehend DMA controller, Programmable Interrupt Controller and Advanced microprocessor.

PO1

Cognitive (Comprehension)

Written Exam

Class lectures

CO5

Design microcontroller based mini projects.

PO3

Cognitive (Synthesis),
Psychomotor (Origination + Guided & Complex Response)

Project Work

Individual or Group Project

ICE314: Digital Communications
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: ICE312 Communications Theory
Course Contents: Idea of baseband signal, Nyquist theorem of baseband signal and impulse response of such communication system, raisedcosine pulse in baseband communication, intersymbol interference, eye diagram, power spectral density of different line codes, onoff binary transmission, the matched filter, properties of matched filter, linear and nonlinear distortion channel, design of equalizer, concept of passband signal, digital modulation schemes (basic principle, modulator and demodulator, BER and constellation diagram): BFSK, BPSK, MPSK, QPSK and QAM, basic principle of OFDMA, PSD of analog bandpass and digital signals.
Recommended Textbook:
1. Digital and Analog Communication Systems, Leon W. Couch; Pearson Education
2. Digital Modulation Techniques; Fuqin Xiong, Artech House, Boston, London
Reference Book:
1. Communication Systems, Simon Haykin, Wiley.
2. Modern Digital & Analog Communication Systems, Lathi.
Course Outcomes:
After successful completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Discuss the desired properties of line codes and calculate their bandwidth from the generalized PSD of the digital signal.

PO1

Cognitive (Comprehension+ Analysis)

Written Exam

Class Lecture

CO2

Analyze and design optimum receiver to mitigate digital communication impairments.

PO1

Cognitive (Analysis+ Synthesis)

Written Exam

Class Lecture

CO3

Classify and analyze digital modulation techniques and compare their performance based on BER and bandwidth.

PO1

Cognitive (Comprehension+ Analysis)

Written Exam

Class Lecture

CO4

Design digital communication systems that meet specifications and evaluate the performance of the systems within realistic constraints.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE322: Digital Signal Processing
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: ICE209 Signals & Systems
Course Contents: The ztransform: ztransform and ROC, properties of ztransform, analysis of LTI systems using ztransform; Discrete Fourier Transform: DFT and its inverse operation, circular and linear convolution using DFT; Fast Fourier Transform (FFT); IIR filter: Realization of IIR filters, direct form I and II, cascade and parallel, polyphase decomposition, digital IIR filter design by bilinear transformation; FIR filter: frequency sampling structure, digital FIR filter design using window functions; Finite word length effect in digital filter; Multirate digital signal processing; Concept of adaptive filter.
Recommended Textbook:
1. Digital Signal Processing, John G. Proakis, Prentice Hall.
Reference Book:
1. Digital Signal Processing, Tarun Kumar Rawat, Oxford University Press.
2. Digital Signal Processing a Practical Approach, Emmanuel C. Ifeachor. Barrie W. Jervis; AddisionWesley.
3. Digital Signal Processing a Computer Based Approach, Sanjit K. Mitra; Tata McGrawHill.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Adopt methodologies and properties of DT signals and LTI systems to analyze LTI systems in frequency and zdomain.

PO1

Cognitive (Application)

Written exam

Class Lecture

CO2

Implement different discretetime LTI system by various structures.

PO1

Cognitive (Application)

Written exam

Class Lecture

CO3

Design filters of given specification under certain constraints.

PO3

Cognitive (Analysis),
Affective (Responding)

Assignment or project report and presentation

Class Lecture and demonstration in the lab.

CO4

Analyze the effect of finite precision in DSP

PO1

Cognitive (Analysis)

Written exam

Class lecture

CO5

Use suitable tools to simulate DT signal and LTI systems and filter design.

PO5

Cognitive (Analysis),
Psychomotor

Designed and/or openended lab performance and/or report

Class Lecture and demonstration in the lab.

ICE370: Applied Numerical Methods
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3


3

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week


3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: MAT205
Course Contents:
Basic Concept: Approximations and roundoff errors, truncation errors.
Root of Equations: Bracketing methods – Bisection methods, Open methods – NewtonRaphson method.
Linear Algebraic Equations: Gauss Elimination – Naive Gauss, GaussJordan. LUdecomposition, GaussSeidal method.
Curve Fitting: Leastsquare regression – Linear regression, polynomial regression. Interpolation – Newton divideddifference interpolating polynomials, Spline interpolation.
Numerical Differentiation and Integration: Newtoncotes integration formulae – Trapezoidal rule, Simpson’s rules, Numerical differentiation – Richardson Extrapolation, Derivatives of unequal spaced data.
Ordinary Differential Equation: RungaKutta Methods – Euler’s method.
The course includes lab work based on theory taught.
Recommended Textbook:
1. Advanced Engineering Mathematics, E. Kreyszig, John Wiley.
Reference Book:
1. Numerical Methods for Engineers, Steven C. Chopra and Raymond P. Canale.
2. Engineering Mathematics, Neil, Thomson Learning.
Course Outcomes: After successful completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Report comparative analysis among different algorithms through error analysis of existing numerical techniques.

PO1

Affective (Valuing)

Term Paper

Lecture and literature review

CO2

Formulate methods to represent engineering problems numerically.

PO2

Cognitive (Synthesis)

Assignment

Class lecture and Assignments

CO3

Identify the implications of approximations.

PO2

Cognitive (Comprehension)

Written Exam, Assignment

Class lecture and Assignments

CO4

Design numerical solutions using different techniques and simulation tools to analyze various engineering and practical problems.

PO5

Cognitive (Application), Psychomotor

Lab Experiments, Lab test,
Openended Lab Project & Lab Report

Lab Experiments, Python Simulation, Projects Supervision
and
Elearning

ICE 439: Engineering Ethics
Credit Hours and Teaching Scheme:

Theory

Credit Hours

3

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: ENG102
Course Contents:
Introduction: Engineering philosophy, engineering ethics and professionalism, ethical terminology. Ethical Issues in Engineering: Understanding ethical problems, qualities of engineers, moral codes. Responsibilities of Engineers: Commitment to society, sustainable development, technology and society, risk, safety, and liability. Institutional Ethics: Code of ethics, key concepts, importance, limitations. Rights of Engineers: Workplace rights, whistle blowing. Professionalism for International Engineers: Challenges of globalization.
Recommended Textbook:
1. Engineering Ethics, Charles B. Fleddermann, Pearson.
Reference Book:
1. Introduction to Engineering Ethics (Basic Engineering Series and Tools), Mike Martin and Roland Schinzinger.
Course Outcomes:
After successful completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Adopt the professional codes of conduct in ethical frameworks as an Information and communication Engineer.

PO8

Affective (Valuing),
Affective
(Responding)

Written exam,
Role play

Class Lecture,
Onspot tasks

CO2

Demonstrate and evaluate the compatibility of professional engineering work with the ethical and legal framework related to ICE.

PO7

Cognitive (Comprehension), Affective (Valuing)

Assignment,
Case study

Class Lecture,
Roleplay

CO3

Formulate documents, terms and policies related to ICE profession, in accordance with the legal frameworks.

PO
10

Cognitive (Analysis), Affective (Responding), Psychomotor

Term paper

Class Lecture

CO4

Analyze and justify the policies related to ICE, in accordance with the Local and International legislature and its impact on society and culture.

PO6

Affective (Valuing)

Written exam

Class lecture, Brainstorming

CO5

Perform effective oral presentation on terms and policies related to ICE profession, in accordance with the legal frameworks.

PO9

Affective (Responding)

Oral Presentation

Group Activity

ICE 441: Wireless & Mobile Communications
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week


3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE314 Digital Communications
Course contents: Radio propagation characteristics: models for path loss, shadowing and multipath fading, delay spread, coherence bandwidth, coherence time, Doppler Spread, Jake's channel model. Digital modulation for mobile radio: analysis under fading channels, diversity techniques and RAKE demodulator. Introduction to spread spectrum communication. Multiple Access Techniques: FDMA/TDMA/CDMA. The cellular concept: frequency reuse, basic theory of hexagonal cell layout, spectrum efficiency. FDMA/TDMA cellular system; channel allocation schemes. Handover analysis. Cellular CDMA; soft capacity. Erlang capacity comparison of FDM/TDM systems and CDMA. Discussion of GSM standards, signaling and call control, mobility management, location tracing. Wireless data networking, packet error modeling on fading channels, performance analysis of link and transport layer protocols over wireless channels, wireless data in GSM, IS95, GPRS and EDGE.
Recommended Textbook:
 Wireless Communications & Networking, J.W. Mark and W. Zhauang
Reference Books:
 1. Modern Wireless Communications, Simon Haykin and Michael Moher
 2. Wireless Communications: Principles and Practice, Theodore S. Rappaport
Course Outcomes:
After successful completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Calculate the path loss, fading profiles and effects of multipath propagation in the wireless channel.

PO2

Cognitive (Analysis)

Written Exam

Class Lecture

CO2

Analyze and model receiver and transmitter diversity techniques.

PO2

Cognitive (Analysis)

Written Exam

Class Lecture

CO3

Analyze the effect of wireless path loss and channel fading on digital modulation techniques using computer simulation.

PO4

Cognitive (Analysis)

Report+ Oral Presentation

Simulation

CO4

Design cellular network with given quality of service (QoS) constraints.

PO2

Cognitive (Application)

Written Exam

Class Lecture

CO5

Report differences between cellular generations and propose future development in cellular systems on the basis of a thorough understanding of existing systems and of systems under development.

PO
12

Affective (Valuing)

Term Paper,
Presentation

Demonstration, Brainstorming, Group Discussion and Feedback

ICE473: Project Management, Entrepreneurship and Industry Interaction
Credit Hours and Teaching Scheme:

Theory

Credit Hours

3

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: All 300 level courses
Course Contents:
General principles, process, and tools of project management. Teamwork and communication. Strategic issues in project management, cost analysis, risk and crisis management. Practical consideration in implementing project management in the industry. Project monitoring and evaluation. Project documentation and reporting. Role of entrepreneurship in the society, personality characteristics of successful entrepreneurs, sources of ideas for new ventures, sources of funding, development of the business plan.
Recommended Textbook:
1. A Guide to the Project Management Body of Knowledge, Project Management Institute.
Reference Book:
1. An introduction to Project Management, Kathy Schwalbe.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Explain the principles, process, and tools of project management.

PO
11

Cognitive (Comprehension+ Synthesis)

Written Exam

Class Lecture

CO2

Understand budgeting and risk management and demonstrate the ethical principles and responsibilities and other practical considerations in project management.

PO8

Affective (Characterization by a value or value complex)

Project Report, Group Discussion

Class Lecture,
Group discussion

CO3

Conduct project meetings, report progress, prepare documents.

PO
10

Cognitive (Comprehension+ Analysis)

Project Report

Class Lecture,
Onspot Classroom tasks

CO4

Value the importance of entrepreneurship in the society

PO6

Cognitive (Application)

Project Report

Class Lecture,
Brainstorming

CO5

Describe and demonstrate the basic requirements to become an entrepreneur with ability to evaluate the sustainability and the impact of professional engineering work in societal and environmental contexts.

PO7

Cognitive (Comprehension+ Application)

Written Exam,
Assignment

Class Lecture

CO6

Communicate effectively sources of ideas for new ventures, sources of funding, and development of the business plan.

PO9

Affective (Characterization by a value or value complex)

Oral Presentation

Group Discussion & RolePlay

ICE496: Capstone Project
Credit Hours: 6
Prerequisite: Students must complete at least 100 credits hours.
Course Contents:
The Capstone project provides opportunity to the students to apply and integrate the knowledge and skills gathered through the earlier course works. Students will take the primary responsibility to identify, organize, plan and execute different tasks associated with the designing of a practical Information and Communication Engineering System or Component. Students will work on the projects in teams.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Identify an appropriate topic that can be simulated and verified

PO
12

Affective (Characterization),
Psychomotor

Preliminary report based on the literature research mentioning identified problem (At the end of the first semester.)

Literature Review,
Brainstorming

CO2

Critically review and analyze the problem to identify theoretical possible solutions

PO2

Cognitive (Analysis)

Preliminary report based on the literature research mentioning possible theoretical solutions to the identified problem (At the end of the first semester.)

Literature Review,
Brainstorming

CO3

Investigate the feasibility of the different solutions to select the most suitable one

PO4

Cognitive (Synthesis),
Psychomotor

Presentation and/or preliminary report to deliver different possible identified solutions and justify the most suitable solution for the identified problem (At the end of the first semester.)

Literature Review,
Group discussion & feedback based on the available solutions of the similar problems

CO4

Plan a project and perform different tasks of project management

PO
11

Cognitive (Application),
Psychomotor

Presentation and/or written report to deliver viable project planning including financial aspect to implement the solution at the end of first semester
(Each of the members should demonstrate skill of individual and group collaboration to convince the evaluator about the success of the project.)

Supervision of projectworks

CO5

Design a solution (algorithm and flow chart) that meets the specifications

PO3

Cognitive (Evaluation), Affective (Responding)

Design the project in pen and paper to meet the specification and present the design in the group presentation at the end of the second semester.

Supervision of
The Project Design

CO6

Incorporate the use of modern engineering tools (programming language) in the design, and verification processes

PO5

Cognitive (Evaluation),
Psychomotor

Use suitable simulating tool to simulate the design and provide a group presentation at the end of the second semester.

Supervision of the design, and the verification processes

CO7

Work effectively in a team

PO9

Affective (Organization), Psychomotor

Peer level review (end of the second semester.)

Supervision of the teamwork

CO8

Understand ethical and professional responsibilities in the practice of information and communications engineering related to the project.

PO8

Affective (Valuing)

Peer level group discussion.
(Identification and discussion on values related to the ethical issues of the project, these should be mentioned in the final thesis/report.)

Necessary Supervision

CO9

Asses societal, health, safety, legal and cultural issues related to the project

PO6

Affective (Valuing)

Peer level group discussion.
(Identification and discussion on societal, health, safety, legal and cultural issues related to the project, these should be mentioned in the final thesis/report.)

Necessary Supervision & Feedback

CO
10

Demonstrate the understanding of the impact of the project on environment and sustainability

PO7

Cognitive (Comprehension), Affective (responding)

Final presentation

Necessary Supervision & Feedback

CO
11

Write professional technical documents related to the project and orally present project results

PO
10

Affective (Responding)Psychomotor

Final report and final presentation

Supervision of the Project Outcomes

D. Technical Electives
These upperclass elective courses stress the rigorous analysis and design principles practiced in the subdisciplines of Information & Communication Engineering. A student has to take total four courses, taking at least one course from each group.
Group A (Information Technology)
Course Number & Name Credit Hours ICE 453 Computer and Cyber Security 3 ICE 469 Computer Architecture 3 ICE 471 Network Programming 4 ICE 472 Speech & Image Processing 4 ICE 474 Computer Graphics & Visualizations 3 ICE 476 Artificial Intelligence 3 ICE 478 Machine Learning 3 ICE 479 Robotic Engineering 3 ICE 483 Data Science 3 ICE 484 Cyber Ethics and Legal Framework 3 ICE 485 Internet of Things 3 Group B (Communication) Course Number & Name Credit Hours ICE 401 VLSI Circuit Design 4 ICE 434 Microwave Engineering 4 ICE 442 Optical Fiber Communications 4 ICE 446 Satellite Communications 3 ICE 448 Information Theory and Coding 3 ICE 452 Multimedia Communications 3 
Group A (Information Technology)
ICE453: Computer and Cyber Security
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week


3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: ICE 302 Computer Communications and Networks
Course Contents: Fundamental concepts of computer security. Well known attack types and vulnerabilities. Social engineering attacks. Cryptography and classical cryptosystems. Authentication protocols and public key infrastructure. IPSec, VPNs, ECommerce issues. Security evaluation and auditing of networked system. Intrusion Detection, Prevention, Response, Containment (Digital forensic evidence) and Disaster Recovery. Network defense tools: Firewalls, VPNs, Intrusion Detection, and filters.
Recommended Textbook:
1. Computer Networks, Andrew S. Tanebaum, Pearson Education.
2. Data Communications and Network Security, Houston H. Carr and Charles Snyder, Mc Graw Hill.
Reference Book:
1. Cryptography and Network Security, William Stallings, Prentice Hall.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Interpret the basic concepts related to computer security, and identify security vulnerabilities of networked system.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Interpret and apply cryptographic algorithms for authentication, cryptanalysis and steganography.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO3

Interpret, use and analyze the security threats on networked systems, assess the existing state of security and deduce realistic security policies.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO4

Examine and justify realistic prevention and disaster recovery; demonstrate this knowledge and write report justifying the actions and policies.

PO4

Cognitive (Analysis)

Term paper, Assignment

Class lectures and brainstorming sessions

ICE469: Computer Architecture
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

0

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE 275 Operating System.
Course Contents: Computer arithmetic: ALU, Integer representation and arithmetic and floatingpoint representation, computer memory system: main memory, cache memory, Instruction sets: Machine instruction, operands, and operations, instruction sets: addressing modes and addressing format. RISC instruction set architecture, CPU design: hardwire control and microprogrammed control, Input/Output: external devices, I/O modules, Programmed I/O, Interrupt driven and DMA, pipelining, multiprocessors.
Recommended Textbook:
1. Computer Organization & Design, David A. Patterson and John L. Hennessy, Morgan Kaufmann.
Reference Book:
1.Structured Computer Organization, Andrew Tanenbaum, Prentice Hall
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Understand the architectural concept of digital computers.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Understand, determine and analyze performance of processor, memory, and I/O subsystems.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO3

Understand, implement, examine, and justify instruction set design for performance improvement, execute and demonstrate this knowledge, and write report for problem solving.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

CO4

Implement, examine, and justify processor and control unit design, execute and demonstrate this knowledge and write report to synthesize functional units of digital computers.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE471: Network Programming
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

2 hours/week for 13 weeks

5 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE 302Computer Communications & Networks.
Course Contents: Introduction to networking and internet protocols, Complete coverage of the Java networking and I/O APIs, Details of multithreading and exception handling, Byte, Character, Object and Message streams, IP, TCP, UDP, Multicast, HTTP, DNS, RMI, CORBA and Servlets, Fingers, DNS, HTTP, and ping, Clients and Servers, Multiprotocol chat systems and whiteboards
Recommended Textbook:
1. Java Network Programming, Elliotte Rusty Harold, O’REILLY Media.
Reference Book:
1. An Introduction to Network Programming with Java, Jan Graba.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Analyze the requirements of a networked programming environment and identify the issues to be solved.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO2

Create conceptual solutions to those issues and implement a programming solution.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

CO3

Understand the key protocols that support the internet and the use of TCP / UDP sockets.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO4

Apply advanced programming techniques such as broadcasting and multicasting.

PO1

Cognitive/
Apply

Written Exams

Class lectures

ICE472: Speech & Image Processing
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week


5 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE 322Digital Signal Processing.
Course Contents: Speech Processing: Human speech communication  Speech production/ perception/linguistics. TimeVarying Signal Analysis: Shorttime Fourier transform, Gabor transform, spectrograms. QuasiStationary Analysis: Cepstrum, linearprediction (AR) and ARMA models. Feature Space Formulation: MixtureGaussian model, Fischer discriminant measure, feature transformations  linear and nonlinear. Maximum likelihood classification and pattern matching through dynamic programming; Hidden Markov modeling of speech.
Image Processing: Why Image Processing? Digital image fundamentals, Image transform, Image enhancement, Image restoration, Image compression, Image segmentation, Representation and description, Recognition and interpretation. The course includes lab work based on theory taught.
Recommended Textbook:
1. Digital Image Processing, Rafael C. Gonzalez, Richard E, Prentice Hall
2. Circuits, Signals and Speech and Image Processing, Richard C. Dorf, CRC Press
Reference Book:
1.Digital Image Processing Algorithms and Applications, Ioannis Pitas, WileyInterscience.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Understand the digital image and speech fundamentals and apply different image and speech enhancement techniques for improving the quality of the image and speech.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Understand the basic color model and apply them for smoothing, sharpening, and/ or segmentation color image. Understand the basic speech signal and cepstrum coefficient, and apply linearpredictive coding for feature extraction.

PO1

Cognitive/
Apply

Written Exams

Class lectures and brainstorming sessions

CO3

Understand, choose, examine, and devaluate different image and speech processing techniques; perform and demonstrate these skills and write report for better representation and / or better storage of the image.

PO1

Cognitive/
Apply

Written Exams, Assignment

Class lectures and brainstorming sessions

CO4

Choose, compare, and justify appropriate object detection and techniques for understand complex reallife speech and images; perform and demonstrate these skills and write report for realistic problem solving.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE474: Computer Graphics & Visualization
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week


3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE 245 Algorithms.
Course Contents: Scientific Visualization: An Engineering Perspective; Overview of Computer Graphics for Visualization; Data Analysis for Visualization; Scalar Visualization Techniques; A Unified framework for flow Visualization; Continuous Volume Display; Animation and Examination of Behavior Over Time; System Aspects of Visualization Application, Visualization Geometry and Algorithm, Surface Extraction, Solid Representation Techniques, CSG, BRep, Octree, Modeling Complexity, Application of Visualization to design and Analysis, Research Issues using Solid Modeling for Visualization.
Recommended Textbook:
1. Graphics and Visualization: Principles & Algorithms, Georgios Papaioannou, Nicholas M. Patrikalakis, Nikolaos Platis, and Theoharis, CRC Press.
Reference Book:
1. Data Visualization, Principle and Practice, Alexandru Telea.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Understand computer graphics system and implement different graphics primitives for drawing a graphics scene.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Understand, apply, and examine different techniques of clipping, two dimensional transformations, and threedimensional transformations and viewing for manipulating complex graphics scenario using OpenGL; perform and demonstrate these skills and write report for realistic problem solving.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO3

Understand and apply the basics of color perception and different color models used in computer graphics.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO4

Apply and Analyze different modeling, rendering, shading and animation techniques; develop and justify program by integrating these techniques to create 3D objects using OpenGL; perform and demonstrate this knowledge and write report for realistic problem solving.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE476: Artificial Intelligence
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

0

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE 245Algorithms.
Course Contents: Intelligent agents: a discussion on what Artificial Intelligence is about and different types of AI agents Search: Searching as a problemsolving technique: a review of “conventional" searching methods including breadthfirst, depthfirst, bidirectional and bestfirst search. Heuristic functions and their effect on performance of search algorithms. Introduction to genetic algorithms. Knowledge Representation and Reasoning: Propositional Logic, FirstOrder Logic, Reasoning and Logical Inference. Firstorder logic as a basis for building intelligent agents capable of acting and reacting in a complex environment. Knowledge engineering: building knowledge bases and automated theorem proves. Production systems as an example of logical problem solving, Uncertain Knowledge: Bayes' Rule, Probabilistic Reasoning, Bayes Nets. Planning agents: representation of states, goals and actions. Learning: Supervised Learning, Unsupervised Learning, Reinforcement Learning.
Decision trees and the ID3 algorithm Applications of AI: Semantic Web. Philosophy of AI.
Recommended Textbook:
1. Computational Intelligence: An Introduction, Andries P. Engelbrecht, John Wiley
Reference Book:
1. Fuzzy Expert Systems and Fuzzy Reasoning, William Siler, James J. Buckley, John Wiley.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Interpret and apply the key components and classical algorithms of artificial intelligence for realistic problem solving.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Apply and examine game theoretical concepts and practices for solving nonconventional reallife situations.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

CO3

Apply and examine Genetic Algorithms and Artificial Neural Networks (ANN) for solving complex search and optimization problems

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO4

Use statistical methods and machine learning for solving complex AI related problems; perform and demonstrate skills and write report on complex AI related problems.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE478: Machine Learning
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

0

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE 476Artificial Intelligence
Course Contents: Introduction to machine learning, Supervised learning setup, Linear prediction: Regression, Classification: Decision tree, Logistic regression, Probabilistic modelling: Bayesian method, Naive bias, Unsupervised learning: Clustering, Apriori, Principal component analysis, Clustering: Partitioning, Hierarchical, Artificial Neural Networks: perceptron, MLPs, back propagation, introduction to Deep learning, Support vector machines, Reinforcement learning and control.
Recommended Textbook:
1. Understanding Machine Learning: From theory to algorithms, Shai Shalev and Shai BenDavid, Cambridge University Press.
Reference Book:
1. Deep learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville, MIT Press Book.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Formulate and use machine learning problems corresponding to different applications.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Understand and use a range of machine learning algorithms, both supervised and unsupervised along with their strengths and weakness.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO3

Understand, use, and determine appropriate machine learning methods / algorithms suitable for different types of learning problems, i.e., know about their most important weaknesses advantages.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

CO4

Examine and analyze appropriate software tools to implement algorithms in a range of realworld applications; implement and write report to represent the analysis results.

PO4

Cognitive (Analysis)

Term paper, Assignment

Class lectures and brainstorming sessions

ICE479: Robotic Engineering
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE 476Artificial Intelligence.
Course Contents: This course provides an overview of robot mechanisms, dynamics, and intelligent controls. Topics include planar and spatial kinematics, and motion planning; mechanism design for manipulators and mobile robots, multirigidbody dynamics, 3D graphic simulation; control design, actuators, and sensors; wireless networking, task modeling, humanmachine interface, and embedded software. Weekly laboratories provide experience with servo drives, realtime control, and embedded software. The course includes lab work based on theory taught.
Recommended Textbook:
1. Handbook of Industrial Robotics, Shimon Y. Nof, 2nd Edition, John Wiley.
Reference Book:
1. An Introduction to AI Robotics, Robin R. Murphy, MIT Press.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Learn fundamental mathematical and computational models; solve and analyze kinematic problems involving robot manipulators and mobile robots.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Familiarize with robot sensors, sensor processing algorithms and navigation planning approaches; use them and examine their engineering tradeoffs.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO3

Understand robot actuator movements and controlling managements; and explore the computational challenges within robotic tasks.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO4

Use, examine, and justify control programming strategies of industrial systems; demonstrate this knowledge and write report to develop simple mobile robot.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE483: Data Science
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

0

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE476Artificial Intelligence
Course Contents: Introduction to data mining, data mining goals, stages of the data mining process, data mining techniques, knowledge representation methods, data preprocessing: data cleaning, data transformation, data reduction, data mining knowledge representation, representing input data and output knowledge, association rules, correlation analysis, classification rules, correlation analysis, classification, basic learning/mining tasks, decision trees, covering rules, prediction, prediction task, statistical classification, distancebased methods, linear models, clustering system, hierarchical methods, conceptual clustering, advanced techniques, data mining software and applications, text mining, web mining.
Recommended Textbook:
1. Data Science from Scratch: First Principles with Python, Joel Grus, O’Reilly Media.
Reference Book:
1. Data Science (MIT Press Essential Knowledge series), John D. Kelleher, Brendan Tierney
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Process raw input data to provide suitable input for a range of data mining algorithms.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO2

Discover and measure interesting patterns from different kinds of databases.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO3

Evaluate and select appropriate datamining algorithms and apply, and interpret and report the output appropriately.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

CO4

Choose and justify software tools; perform and demonstrate skills, and write report to design and implement datamining application using sample, realistic data sets.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE484: Cyber Ethics and Legal Framework
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

0

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: None.
Course Contents: Computer and information ethics at Stanford Encyclopedia of Philosophy. ACM code of ethics and professional conduct. Software engineering code of ethics and professional practice. Data protection act, computer misuse act, impact of the computer misuse act. Copyright, designs and patents act, freedom of information act, security of internet communications. Bangladesh: Information and communication technology act of 2006 and its amendment in 2013. Bangladesh: copyright act of 2000. Bangladesh: telecommunication regulatory act of 2001. Pornography: pornography act of 2012.
Recommended Textbook:
1. Cyberethics, Spinello, Jones and Bartlett learning
Reference Book:
1. Investigating Cyber Law and Cyber Ethics: Issues, Impacts and Practices, Alfreada Dudley, James Bramen, and Giovanni Vincenti.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Interpret and comply with the professional codes of conduct and ethical frameworks as an ICT professional.

PO8

Affective (Valuing),
Affective
(Responding)

Written exam,
Role play

Class Lecture,
Onspot tasks

CO2

Describe and comply with the legislation related to Information and Communication Engineering.

PO8

Affective (Valuing),
Affective
(Responding)

Written exam,
Role play

Class Lecture,
Onspot tasks

CO3

Interpret, apply, and justify the standard ethical frameworks within computing.

PO8

Affective (Valuing),
Affective
(Responding)

Written exam,
Role play

Class Lecture,
Onspot tasks

CO4

Analyze, evaluate, and formulate documents, terms and policies related to computing profession, in accordance with legal frameworks; demonstrate this knowledge and write report justifying the actions and policies.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

ICE485: Internet of Things
Credit Hours and Teaching Scheme

Theory

LABORATORY

TOTAL

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

0

3 Hours/Week for 13 Weeks+
Final Exam in the 14th week

Prerequisite: ICE 302 Computer Communications & Networks.
Course Contents: Introduction to IoT, basics of networking, communication protocols, sensor networks: machinetomachine communications, interoperability in IoT: integration of sensor and actuators, implementation of IoT with programmable devices, software defined networking (SDN) for IoT: data handling and analytics, cloud computing, Fog computing: smart cities and smart homes, connected vehicles: smart grid, industrial IoT: agriculture, healthcare, activity monitoring, and related case studies.
Recommended Textbook:
1. Precision: Principles, Practices and Solutions for the Internet of Things, Timothy Chou, lulu.com
Reference Book:
1. Smart Internet of Things Projects, Agus Kurniawan
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Understand the building blocks of IoTs and their characteristics with realworld applications.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Understand, apply, and examine different architectures for different levels of complex IoT applications.

PO4

Cognitive (Analysis)

Term paper, Assignment

Class lectures and brainstorming sessions

CO3

Examine IoT data analytics and justify various tools for IoT; perform and demonstrate skills and write report on realistic data analytics.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO4

Choose and justify software and hardware tools, develop source code for various IoT domains, perform and demonstrate skills and write report on realistic IoT development.

PO5

Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response)

Lab Experiments, Lab Exam, Laboratory Project, Project Report

Lab Demonstration

Group B (Communication)
ICE401: VLSI Circuit Design
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: ICE313
Course Contents:
Review of semiconductor physics pertinent to VLSI design, NMOS and PMOS transistors, transistors as switches, CMOS inverters, NAND and NOR gates, cross section of an inverter, inverter mask sets, fabrication steps, simplified design rules, stick diagram, layout, CMOS circuit design, gate level and transmission gate based multiplexers, multiplexer based design, CMOS latches and flipflops as basic building blocks of sequential circuit, standard cell layout, area estimation from stick diagram and layout, VLSI design flow, logic design, circuit design, physical design, structured design approach, design partitioning, hierarchical design, Verilog code at behavioral and structural level, gate level and transistor level netlist, CMOS transistor theory, cutoff, linear, saturation, nonideal transistor behavior, mobility degradation, velocity saturation, channel length modulation, body effect on threshold voltage, subthreshold, gate and junction leakage, effect of process and environmental variation, pass transistor, dc and transient response, logic levels and noise margins, RC delay models, delay estimation, logical effort and parasitic delay, delay in multistage logic networks, dynamic and static power, activity factor, low power circuit design, pseudoNMOS, dynamic and domino logic family, adders, six transistor static and four transistor dynamic memory cell, sense amplifier.
The course includes lab work based on theory taught.
Recommended Textbook:
1. CMOS VLSI design: A Circuit and System Perspective by Neil H. E. Weste, David Harris & Ayan Banerjee, Pearson Education, 4th Edition.
Reference Book:
1. Basic VLSI Design (3rd Edition) by Douglas A. Pucknell and Kamran Eshragian, Prentice Hall.
Course Outcomes: After successful completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Draw the Schematic diagram, stick diagram and layout of basic combinational and sequential circuit, estimate the area from stick diagram and calculate the same from layout satisfying design rules.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Design for equal rise and fall time, simulate and obtain voltage and current waveforms, measure delays as well as get transfer characteristics and parametric analysis for power, delays etc.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

CO3

Draw the Schematic diagram using modern tools such as dsch, generate the Verilog code, compile in microwind to generate the layout.

PO5

Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response)

Lab Experiments, Lab Exam, Laboratory Project, Project Report

Lab Demonstration

CO4

Design a basic building block such as a 1bit full adder and use the block for implementing a structured, hierarchical design such as a 4bit binary parallel adder.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab DemonstrationSimulation and Feedback

CO5

Design low power circuits and memory elements.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE434: Microwave Engineering
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks +Final Exam in the 14th week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks +Final Exam in the 14th week

Prerequisite: ICE310 Electromagnetic Theory
Course Contents: Review of Maxwell's equations and transmission line theory, circuit models. Microwave network analysis: Scattering matrices and multiport analysis techniques. Impedance Matching: Design of matching networks including lumped elements, stubs and transmission line sections, circuit tuning. Passive Components: Theory of operation, practical design and implementation of power dividers, directional couplers and hybrids, resonators as well as system applications of these devices. Noise and distortion in RF Systems: Theory of noise in RF circuits, distortion of RF signals, dynamic range limitations, effects on channel capacity. Active Circuits: Theory of operation, practical design and implementation of amplifiers for lownoise or power applications, detectors, mixers; Overview of microwave tubes and solid state devices. Nonreciprocal Devices: Theory of operation and implementation of isolators, circulators and variable attenuators and phase shifters. Microwave Systems: Receiver and system performance calculations, RF link analysis, endtoend microwave system ("the physical channel") analysis. Applications: Antennas, propagation and microwave filter synthesis. The course includes lab work based on theory taught.
Recommended Textbook:
1. Foundations for Microwave Engineering, R. E. Collin. McGraw Hill.
Reference Book:
1. Fields and Waves in Communication Electronics, S. Ramo, J.R. Whinnery, Wiley.
Course Outcomes (COs):
After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Understand the propagation mechanism of RF and microwave signal through free space and guided medium.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Analyze the performance of transmission lines and determine the parameters of transmission lines.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO3

Solve transmission line problems and impedance matching problems using Smith chart.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO4

Design microwave filter, microwave links and understand the basics about different antenna for practical implementation.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

ICE 442: Optical Fiber Communications
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

1

4

Contact Hours

3 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

2 Hours/Week for 13 Weeks

5 Hours/Week for 13 Weeks + Final Exam in the 14^{th} week

Prerequisite: ICE310, ICE314
Course Contents:
Overview of fiber optic communication systems: evolution, nature of light, advantages and applications, Characteristics of optical transmission media. Optical fibers: propagation and transmission characteristics, loss and dispersion mechanisms. Nonlinear Characteristics.
Optical sources: principles of operation, modulation characteristics and driver circuits.
Photo detectors: principles of operation, circuits and performance.
Fiber optic connectors, couplers, multiplexers and splices, wavelength converters, routers, optical amplifiers, post detection amplifiers, Fiber optic communication systems and link budget using direct detection. Coherent and WDM systems.
This course includes lab works based on theory taught.
Recommended Textbook:
1. Optical Fiber Communications: Principle and Practice, John M. Senior, Prentice Hall.
Reference Books:
1. Gerd Keiser, Optical Fiber Communications, third edition, McGraw Hill, 2000
2. FiberOptic Communication Systems, 4th Ed., G. P. Agrawal, John Wiley & Sons, 2010.
3. Understanding Optical Fiber Communications, A.J. Rogers, Artech House Publishers.
Course Outcomes:
After successfully completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Understand the fundamentals of the operation and transmission characteristics of optical fiber.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Analyze and calculate power coupling losses due to connectors, splices, source output pattern and fiber numerical aperture.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO3

Understand the structure and operational properties of optical source and detectors.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO4

Comprehend the knowledge of essential elements of optical fiber links and design optical fiber link and power budgeting.

PO3

Cognitive (Application+ Evaluation)

Laboratory Project+ Project Report

Lab Demonstration, Simulation and Feedback

CO5

Simulate and analyze propagation and transmission characteristics of optical fiber and establish a practical link.

PO5

Cognitive (Application)
Psychomotor (Origination+ Guided & Complex Response)

Lab Experiments, Lab Exam, Laboratory Project, Project Report

Lab Demonstration

ICE446: Satellite Communication
Credit Hours and Teaching Scheme:

Theory

Laboratory

Total

Credit Hours

3

0

3

Contact Hours

3 Hours/Week for 13 Weeks +
Final Exam in the 14th week


3 Hours/Week for 13 Weeks +
Final Exam in the 14th week

Prerequisite: ICE 441 Wireless and Mobile Communications
Course Contents: Orbits: Kepler's laws, Newton's law, orbital parameters, inclined orbits, geostationary orbit. space environment: mechanical effects, atmospheric effects (radiation, ionospheric effects, rain attenuation), polarization, propagation. link analysis: equivalent isotropic radiated power, received signal power, noise power at the receiver input, the uplink, the downlink, stationtostation link. Satellite access: FDMA, TDMA, CDMA, fixed and ondemand assignment, random access, intersatellite links. Earth stations: standards, antennas, radio frequency subsystem, communication subsystem, network interface subsystem. the payload: transparent repeaters, multibeam satellite repeater, regenerative repeater, antenna characteristics. The platform: the propulsion system, the power supply (solar power satellites), telemetry, tracking and command, thermal control. Satellite installation: installation in orbit, launch vehicles, reliability issues, cost issues and network.
Recommended Textbook:
1. Satellite Communications, D. Roddy, McGrawHill Professional.
Reference Book:
1. Satellite Communication System, M. Richharia, McGrawHill.
Course Outcomes (COs): After completion of this course students will be able to:
COs

CO Statements

POs

Domain

Assessment Strategy

TeachingLearning Strategy

CO1

Understand the basics of satellite communications with their applications.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO2

Explain the working principles of orbits, satellite access, satellite installation, satellite payload, satellite services and link analysis of GEO, MEO and LEO.

PO1

Cognitive/
Apply

Written Exams

Class lectures

CO3

Evaluate uplink and down link power budget.

PO2

Cognitive (Analysis)

Written exam and/or assignment

Class lectures and
Assignments

CO4

Investigate and compare different types of satellite system with other communication systems.

PO4

Cognitive (Analysis)

Term paper, Assignment

Class lectures and brainstorming sessions
