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Data Link Layer: Framing Techniques; Error Detection/Correction Techniques;

ARQ Error Control (Stop-and-Wait, Go-Back-N, Selective Repeat Request); Error detection( check sum, CRC); Bit stuffing; Examples of Data Link Layer Protocols; High Level Data Link Control Protocol; Multiple-access protocols: ALOHA, Slotted ALOHA, Ethernet (802.3), CSMA/CD, Logical link control, Wireless LAN (802.11), CSMA/CA; Throughput analysis of various MAC protocol.

(7 L)

Unit V: Network Layer: Overview of Network Layer-Data Plane and Control Plane : IP: Internet Protocol, Datagram format, Fragmentation, IPv4 addressing, Network address translation, IPv6;

Software defined networking (SDN), Address Resolution protocols (ARP, RARP); Sub-netting, Classless Routing(CIDR), ICMP, IGMP, DHCP; Virtual LAN, Networking devices ( Hubs, Bridges &

Switches); Routing: Routing and Forwarding, Static routing and Dynamic routing, Routing Algorithms:

Distance vector routing algorithm, Link state routing (Dijkstra’s algorithm); Routing Protocols:

Routing Information protocol (RIP), Open Shortest Path First (OSPF), Border Gateway Protocol

(BGP), The SDN control plane. (7 L)

Unit VI: Transport Layer –UDP, TCP, Congestion Control & Quality of Service – Data traffic, Congestion, Congestion Control, QoS and Flow Characteristics; Application Layer – DNS, Remote Logging (Telnet), SMTP, FTP, WWW, HTTP, POP3, MIME, SNMP. (6 L)

Unit VII: Local Area Networks -IEEE 802.3: Bus with CSMA/CD Protocol; IEEE 802.5: Token Ring; Fiber Distributed Data Interface (FDDI); Distributed Queue Dual Bus (DQDB);

Fast Ethernet; ATM Networks: Basic Concepts of ATM, Multiplexing, Broadband Switching, ATM Cell Structure, ATM Layer, ATM Adaptation Layers, Applications, MPLS; (? L)

Text Books:

1. William Stallings, ‘Data and Computer Communication’, 8th Edition, Pearson Education, 2003 / PHI.

2. R. Gallager and D. P. Bertsekas, ‘Data Networks’, 2nd edition, Prentice-Hall, Inc., 1991.

3. Behrouz A. Forouzan, Cryptography & Network Security ,IV Edition, Tata McGraw-Hill, 2008.

4. J F Kurose and K W Ross, Computer Network A Top-down Approach Featuring the Internet, 3/e, Pearson Education, 2010.


1. Peterson and Davie, ‘Computer Networks: A Systems Approach’, 5th Ed, Morgan Kaufmann Publishers, 1999.

2. Kleinrock, Leonard, ‘Queueing Systems, Vol 1: Theory’, Wiley J., 1975.

Course Outcomes: Upon successful completion of the course, students would be able to –

CO1: Understand the facts about the physical arrangement of networks, types and modes of networks, data conversions and transmission medium

CO2: Understand the detection and correction of errors, link control and link protocols of data link layer;

CO3: Understand the study of queuing theory and its application in networking CO4: Analyse the performance of communication network.

CO5: Simulate different routing protocols and analyse their performance.

CO6: Understand security aspects in designing a trusted computer communication system ECx5119 Statistical Signal Processing L-T-P: 3-0-0; Cr: 03

Prerequisite: (i) Digital Signal Processing (ii) Probability, Random Variable and Stochastic Process

Department of Electronics and Communication Engineering National Institute of Technology, Patna.

78 and (iii) Linear Algebra

Course Objective : Objective of this course is to deal with processing of signals where the processing parameters are adjusted continuously to suit the time varying environmental conditions.

Course Content :

Unit-I : Review of Linear Algebra relevant to the course, Review of Random Processes: power spectral density, Autocorrelation and auto-covariance structures of discrete time random processes, Linear shift- invariant (LSI) systems with random input signal, Spectral factorization theorem, Wold‘s decomposition, Random signal modeling: White Noise Sequence, Moving Average (MA), Autoregressive (AR), ARMA models.

Unit-II: Parameter Estimation: Necessary and sufficient statistic for parameter estimation, Cramer–

Rao theorem, Maximum likelihood and Bayesian estimation.

Unit-III: Optimal linear filter: Linear minimum mean square error estimator (LMMSE), Winer Hopf equations, FIR and IIR Wiener filters both for causal and noncausal case, Noise filtering.

Unit-IV: Linear Prediction of the signal: Forward and Backward prediction, Prediction error, Yule- Walker equations, Levinson-Durbin Algorithm, Lattice filer realization.

Unit-V: Adaptive Filters: Steepest Descent method, convergence of the steepest descent method Least Mean Square ( LMS) algorithm, convergence of the LMS algorithm, excess mean square error, Recursive Least Squares (RLS) filters; Kalman filters: signal modeling, estimation of the filter- parameters, scalar and vector Kalman filters.

Unit-VI: Spectral estimation: periodograms, modified periodograms, minimum variance, maximum entropy and parametric methods for spectral estimation.

Text Books:

1. Monson H. Hayes, Statistical Digital Signal Processing and Modeling, John Wiley.

2. S. Haykin, Adaptive Filter Theory, PHI, 2001.

Reference Books :

1. D G Manolakis, V K Ingle, S M Kogon, Statistical and Adaptive Signal Processing, Artech House.

Course Outcomes : After successful completion of the course, students would be able to – CO1: Carryout modelling of random signal

CO2: Understand approaches for parameter estimation and it's need for real world applications CO3: Carryout design and analysis of optimal filters

CO4: Understand linear prediction analysis of the signal and it's applications

CO5: Carryout design and analysis of adaptive filters and apply it in real world signal processing CO6: Understand different spectral estimation method and their applications

ECx5120 Internet of Things L-T-P: 3-0-0; Cr: 03

Pre-requisite: Communication Engineering, Microprocessor & Microcontroller, knowledge of Sensor.

Objectives: To discuss about the basics, architecture and layering analysis of various protocols in IoT and its various IoT applications.

Course Contents:

Department of Electronics and Communication Engineering National Institute of Technology, Patna.

79 Unit I: Introduction: Basics of IoT, IoT applications in different domains, Trends in IoT Market, Recap of Embedded system: Basic Concepts of Sensors, Actuators and Microcontroller. Four Pillars of IoT, DNA of IoT - The Toolkit Approach for End-user Participation in the Internet of Things. Basic for

IoT Information Security. (7 L)

Unit II: IoT Protocols: Middleware for IoT: Overview – Communication middleware for IoT , Protocol Standardization for IoT – Efforts – M2M and WSN Protocols – SCADA and RFID Protocols –Issues with IoT Standardization – Unified Data Standards – Protocols – IEEE 802.15.4 – BACNet Protocol – Modbus – KNX – Zigbee Architecture – Network layer – APS layer – Security.

(9 L)

Unit III - Web of Things: Web of Things versus Internet of Things – Two Pillars of the Web – Architecture Standardization for WoT– Platform Middleware for WoT – Unified Multitier WoT

Architecture – WoT Portals. (9 L)

Unit IV: Introduction of Cloud Computing: Cloud of Things: Grid/SOA and Cloud Computing – Cloud Middleware – Cloud Standards – Cloud Providers and Systems – Mobile Cloud Computing –

The Cloud of Things Architecture. (9 L)

Unit V: IOT Physical Devices & Endpoints and Applications:: What is an IOT Device, Exemplary Device, Board, Hand’s on Mini project, Applications – Smart home, Wearables, Health care, Smart

retail, and Smart city. (8 L)

Text Books:

1. Internet of Things in the clouds: A Middle Perspective, Honbo Zhou, CRC Press, Taylor &

Francis Group.

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.

Reference Books:

1. Vijay Madisetti , Arshdeep Bahga, “Internet of Things (A Hands-on-Approach)” , 2014.

2. Adrian McEwen , Hakim Cassimally , “Designing the Internet of Things” , Wiley,2013.

3. 6LoWPAN: The Wireless Embedded Internet, Zach Shelby, Carsten Bormann, Wiley

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

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

6. Computer Networks; By: Tanenbaum, Andrew S; Pearson Education Pte. Ltd., Delhi, 4th Edition 7. Lu Yan, Yan Zhang, Laurence T. Yang, Huansheng Ning, “The Internet of Things: From RFID to

the Next-Generation Pervasive Network”, ed. 2008.

Course Outcomes: After successful completion of the course, students would be able to : CO1: Understand the application areas of IOT

CO2: Realize the revolution of Internet in Mobile Devices, Cloud & Sensor Networks CO3: Understand building blocks of Internet of Things and characteristics

Department of Electronics and Communication Engineering National Institute of Technology, Patna.


ECX5121 Wireless Sensor Networks L-T-P: 3-0-0; Cr: 03

Prerequisite: Communication Engineering, Computer Communication Network Course Objective:

Wide range of applications such as disaster management, military and security have fueled the interest in sensor networks during the past few years. Sensors are typically capable of wireless communication and are significantly constrained in the amount of available resources such as energy, storage and computation. Such constraints make the design and operation of sensor networks considerably different from contemporary wireless networks, and necessitate the development of resource conscious protocols and management techniques. This course provides a broad coverage of challenges and latest research results related to the design and management of wireless sensor networks. Covered topics include network architectures, node discovery and localization, deployment strategies, node coverage, routing protocols, medium access arbitration, fault-tolerance, and network security.

Course Content:

Unit-I: Introduction Examples of available sensor nodes; Sample sensor networks applications; Design challenges

Unit-II: Design Model Contemporary network architectures; Operational and computational models;

Performance metrics; Software and hardware setups.

Unit-III: Network Bootstrapping Sensor deployment mechanisms; Issues of coverage; Node discovery protocols; Localization schemes; Network clustering

Unit-IV: Data dissemination and routing Query models; In-network data aggregation; Robust route setup; Coping with energy constraints

Unit-V: Physical and Link layers Radio energy consumption model; Power management; Medium access arbitration; Optimization mechanisms

Unit-VI: Dependability Issues Security challenges; Threat and attack models; Quality of service provisioning; Clock synchronization; Supporting fault tolerant operation

Text Books:

1. Protocols and Architectures for Wireless Sensor Networks, Holger Karl and Andreas Willig, Wiley, 2005.

2. Wireless Sensor Networks, Cauligi S. Raghavendra, Krishna Sivalingam, and Taieb M. Znati, Springer, 2005.

Course Outcomes: After successful completion of the course, students would be able to - Students would be able to –

CO1: Architect sensor networks for various application setups.

CO2: Explore the design space and conduct trade-off analysis between performance and resources.

CO3: Assess coverage and conduct node deployment planning.

CO4: Devise appropriate data dissemination protocols and model links cost.

CO5: Determine suitable medium access protocols and radio hardware.

CO6: Design understanding prototype sensor networks using commercial components.

CO7: Design understanding provision quality of service, fault-tolerance, security and other dependability requirements while coping with resource constraints.

CO8: Evaluate the performance of sensor networks and identify bottlenecks.

Department of Electronics and Communication Engineering National Institute of Technology, Patna.


ECx5122 Optoelectronics L-T-P: 3-0-0; Cr: 03

Pre-requisite: Communication Engineering (EC4502), Analog Electronics.

Objectives: Learning the basic concepts of Optoelectronics and related devices/systems.

Course Contents:

Unit-I: Overview of Optical fibres and waveguides: Basics of Optical Fibers (Single/Multi-mode, Step/Graded index), Normalized Frequency, Description of Modes, Distortions in Optical Fibers (Attenuation & Dispersion), Dispersion Shifted and Dispersion flattened fibers, Fiber birefringence, Concepts of solitons, Loss mechanism in Fiber (Losses - Insertion, Return, Intrinsic, Reflection, etc.), Dielectric Slab Waveguide (Modes in symmetric slab waveguide, Mode condition, TE & TM polarization, Higher Order modes, Mode Pattern, Description of Fiber cable and Fiber splicing. (7 L) Unit-II: Optical Source 1 – LASER: Major requirements for an optical sources, Direct & Indirect bandgap semiconductors, Description of different efficiencies in optical sources, Introduction to LASERs, Population Inversion, Einstein Coefficients for Absorption and Emission, Laser Oscillation

& its threshold condition, Semiconductor materials for optical sources, Semiconductor Injection Laser:

Structures & characteristics, Modulation of Laser diodes, Impact of temperature, Noise in Laser (Modal noise, Mode-partition noise, and Reflection noise), Non-semiconductor Lasers (Nd-YAG Laser

& Glass fiber Lasers). (7 L)

Unit-III: Optical Source 2 – Light Emitting Diode: Introduction to Light Emitting Diodes, LED Power and Efficiencies, Description of different efficiencies in optical sources, Double hetero-junction LED, LED structures: Planar LED, Dome LED, Burrus-type LED, Surface emitting LED, Edge emitting LED, Super-luminescent LED, Quantum dot LEDs; LED characteristics (optical output power and spectrum, modulation capability, Transient Response, Power-Bandwidth product).

(6 L)

Unit-IV: Optical Detectors: Major requirements for optical detectors, Device types, Principle of Optical detection, Quantum efficiency & Responsivity, Absorption, Long-wavelength cutoff, Photo detectors without internal gain (p-n photodiode, PIN photodiode), Photo detectors with internal gain (Avalanche photodiode, etc.), Benefits & drawbacks with APD, Photo-detector noise (noise source, Signal-to-Noise ratio), Avalanche Multiplication Noise, Temperature effect on Avalanche Gain, Major factors limit the speed of response of photodiode. (6 L)

Unit-V: Optical Devices based on Electro-Optic effects: Electro-Optic effects (Kerr, Pockels, and Faraday effects), Q-switching, Electo-Optic Modulators, Kerr Modulators, Magneto-Optic Devices, Electro-Optic amplitude modulation, Acousto-Optic effect and devices. (5 L)

Unit-VI: Optoelectronic Devices and Systems: Overview of Optical sensors and its advantage over conventional sensors, Intensity modulated optical fiber sensors, Interferometric optical fiber sensors;

Overview of WDM – Principle of operation, WDM standards, Optical fiber couplers, Directional couplers; Optical isolators, Mach–Zehnder interferometer, Semiconductor quantum well structures, Quantum wires and dots. Optical Amplifiers - types and applications, Semiconductor optical

amplifiers, Erbium-doped fiber amplifiers. (8 L)

Unit-VII: Materials for Optoelectronic devices: Growth and characterization of III-V and II-VI semiconductor materials, Ternary and quaternary semiconductors. (3 L)

Text Books:

1. John M. Senior, “Optical Fiber Communications”, PEARSON, 3rd Edition, 2010.

2. Gerd Keiser, “Optical Fiber Communications”, TMH, 5th Edition, 2013.

Department of Electronics and Communication Engineering National Institute of Technology, Patna.

82 3. R. P. Khare, Fiber Optics and Optoelectronics, Oxford University Press, 2004.

4. S. C. Gupta, Optoelectronic Devices and Systems, PHI Learning Pvt. Ltd., 2015.

5. Edited by V. P. Pal, Fundamentals of Fibre Optics in Telecommunication and Sensor Systems, Second edition, New Age International Publishers.

Reference Books:

1. Govind P. Agrawal, “Fiber Optic Communication Systems”, John Wiley, 3rd Edition, 2004.

2. Joseph C. Plais, “Fiber Optic Communication”, Pearson Education, 5th Ed., YP-2004

3. D. K. Mynbaev, and L. L. Scheiner, Fibre-Optics Communications Technology, 1st Edition, Pearson. YP-2002.

Course Outcome: Upon successful completion of this course, students should be able to:

CO1 Analyze the basic concepts of optical fibers and optical waveguides.

CO2 Analyze the issues related with signal distortions in optical fiber/waveguide

CO3 Learn the different optical sources and optical detectors for various optical communications.

CO4 Learn different optoelectronic devices based Electro-optic effect.

CO5 Understand the basic idea of other optoelectronic devices, such as optical sensors, couplers, WDM systems, optical amplifiers, etc.

CO6 Learn about the essential materials used for realization of various optoelectronic devices and systems.

ECx5123 Biomedical Signal Processing L-T-P: 3-0-0; Cr: 03

Pre Requisites: Signals and Systems, Digital Signal Processing Course Objectives:

1. Being able to understand the basic techniques in biomedical signal processing, analysis and pattern recognition. These include understanding of physiological signals and their processing challenges; preprocessing (filtering and artefact removal), event detection and (linear) feature definition, signal transforms (Fourier, wavelets, etc.), waveform analysis, parametric and nonparametric signal representation, blind source separation; classification and decision support 2. Being able to apply these methods to solving real-life biomedical data processing problems;

3. Being able to interpret, analyse, and critically compare the potential and limitations of various approaches for the biomedical problem at hand;


Unit I: Introduction to Biomedical Signals: Preliminaries; Biomedical signal origin & dynamics

(ECG, EEG, EMG, etc.) (6 L)

Unit II: Filtering for Removal of Artifacts : Statistical Preliminaries; Time domain filtering (Synchronized Averaging, Moving Average, Derivative-based operator); Frequency Domain Filtering (Notch Filter); Optimal Filtering: The Weiner Filter, Adaptive Filtering Selecting Appropriate Filter.

(8 L)

Unit III: Event Detection and Feature Definition : Signal segmentation; Envelop extraction and analysis, temporal, spectral, statistical, information theoretic and cross spectral features; Waveshape

and Waveform complexity. (8 L)

Unit IV: Time-Frequency Domain Analysis : Fourier spectrum of biosignals; short-time Fourier transform and spectrogram; DCT and its Applications; Wavelet transform and time frequency analysis;

Hilbert transform and its Applications; Empirical mode decomposition and empirical wavelet transform; Correlation Analysis and power spectral estimation. (8 L)

Department of Electronics and Communication Engineering National Institute of Technology, Patna.

83 Unit V: Pattern Classification and Diagnostic Decision : Pattern classification; Linear and non- linear pattern recognition techniques; Supervised and Unsupervised Pattern Classification; Training and Test Procedure; Case Studies: Diagnosis of bundle-branch block, normal vs ectopic ECG beats, EEG wave classification such as presence of alpha rhythm, etc. (6 L)

Unit VI: Multichannel Biosignal Processing : Principal Component Analysis for dimensionality reduction and Independent Component Analysis to split the multichannel signal into separate source signals (such as muscle artefacts, ECG, breathing…) (6 L)

Books and References:

1. R M Rangayyan “Biomedical Signal Analysis: A case Based Approach”, IEEE Press, John Wiley & Sons. Inc, 2002.

2. E.N. Bruce, Biomedical Signal Processing and Signal Modelling, John Wiley and Sons, 2001.

3. Willis J. Tompkins “Biomedical Digital Signal Processing”, EEE, PHI, 2004

4. D C Reddy “Biomedical Signal Processing: Principles and Techniques”, Tata McGraw-Hill Publishing Co. Ltd, 2005

5. John L. Semmlow and Benjamin Griffel “Biosignal and Medical Image Processing”, 2014, 3rd Ed. CRC Press, USA

6. John L. Semmlow, “Biosignal and Biomedical Image Processing MATLAB based Applications”, 2008, CRC Press, USA

Course Outcome: Upon successful completion of the course, students would be able to :

CO1 Comprehend the common biomedical signals like ECG, EEG, EMG including physiology CO2 Comprehend and analyse the signals in different statistical methods

CO3 Comprehend the implementations of filters in bio signals CO4 ECG and EEG signals.

CO5 Analyze and model to acquaint the transforms enactments on bio signal CO6 Acquaint the ECG and EEG processing and pattern recognition

CO7 Acquaint data driven techniques like PCA and ICA on biosignals.

Prerequisites:(i) Digital Signal Processing, (ii) Signals and Systems and (iii) Linear Algebra


1. To introduce the origin and formation of digital imaging.

2. To develop the understanding of different types of imaging techniques for different purposes.

3. To equip the students with various possible applications of the image analysis.


Unit-I: Digital Image Fundamentals: Image modeling, Sampling and Quantization, Imaging Geometry, Digital Geometry, Image Acquisition Systems, Different types of digital images.

Unit-II: Bi-level Image Processing: Basic concepts of digital distances, distance transform, medial axis transform, component labeling, Histogram of grey level images, Optimal thresh holding.

Unit-III: Images Enhancement: Point processing, enhancement in spatial domain, enhancement in frequency domain.

Unit-IV: Detection of edges and lines in 2D images: First order and second order edge operators, multi-scale edge detection, Canny's edge detection algorithm, Hough transform for detecting lines and curves.

Unit-V: Color Image Processing: Color Representation, Laws of color matching, chromaticity ECx5124 Digital Image Processing L-T-P: 3-0-0; Credit: 3; Cr: 03

Department of Electronics and Communication Engineering National Institute of Technology, Patna.

84 diagram, color enhancement, color image segmentation, color edge detection.

Unit-VI: Image compression: Lossy and lossless compression schemes, prediction based compression schemes, vector quantization, sub-band encoding schemes, JPEG compression standard.

Unit-VII: Segmentation: Segmentation of grey level images, Watershed algorithm for segmenting grey level image.

Unit-VIII: Morphology: Dilation, erosion, opening, closing, hit and miss transform, thinning, extension to grey scale morphology.

Unit-IX: Feature Detection: Fourier descriptors, shape features, object matching/features.

Texts Books:

1. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Pearson Education, 2008.

2. A. K. Jain, Fundamentals of Digital Image processing, Pearson Education, 2009.

References Books:

1. W. K. Pratt, Digital Image Processing, John Wiley & Sons, 2006.

2. S.J. Solari, Digital Video and Audio Compression, McGraw-Hill, 1997 Course Outcome: After successful completion of the course, students would be able :

1. Enhance image in spatial and frequency domain.

2. Implement various aspects of image segmentation and compression.

ECx5125 MIMO Communications L-T-P: 3-0-0; Cr: 03

Prerequisite: Digital Communication System, Wireless Communication, Information Theory Objectives:

1. To understand the importance of MIMO for next generation networks.

2. To identify the role of different diversity formats and spatial multiplexing in combating the effect of fading and maximizing transmission capacity.

3. To provide an introduction to advanced MIMO concepts like multi-user MIMO, massive MIMO and SM-MIMO for next generation communication.


Unit I: Introduction: Diversity-multiplexing trade-off, transmit diversity schemes, advantages and applications of MIMO systems.(4L)

Unit II: Analytical MIMO Channel Models : Uncorrelated, fully correlated, separately correlated and keyhole MIMO fading models, parallel decomposition of MIMO channel. (4L)

Unit III: Power Allocation in MIMO Systems : Uniform, adaptive and near optimal power allocation. (4L)

Unit IV: MIMO Channel Capacity: Capacity for deterministic and random MIMO channels, capacity of i.i.d., separately correlated and keyhole Rayleigh fading MIMO channels. (6L)

Unit V: Space-Time Codes: Advantages, code design criteria, Alamouti space-time codes, SER analysis of Alamouti space-time code over fading channels, space-time block codes,Space-time trellis codes, performance analysis of Space-time codes over separately correlated MIMO channel, Space- time turbo codes. (8L)

Unit VI: MIMO Detection: ML,ZF,MMSE,ZF-SIC,MMSE-SIC, LR based detection. (6L)