Principles of Communication Systems - I
Offered By: Indian Institute of Technology Kanpur via Swayam
Course Description
Overview
This course covers fundamental concepts of communication systems, which are essential for the understanding of advanced courses in digital/ wireless communication systems. Beginning with various basic tools such as Fourier Series/ Transform, the course will also cover several important modulation techniques such as Amplitude Modulation, Frequency Modulation, Phase Modulation etc. Sampling process and Quatization, including Nyquist criterion and reconstruction of the original signal from the sampled signal will be dealt with in the later parts of the course. Further, the course will also cover concepts in probability and random variables/ processes and is designed to serve as a basic course towards introducing the students to various aspects of probability from the perspective of modern digital and wireless communications. Thus, it will focus on basic concepts in probability, random variables and random processes, while also illustrating digital/ wireless communication specific examples to better bridge the gap between theory and application.This course is suitable for all UG/PG students and practicing engineers/ managers who are looking to enhance their knowledge of the fundamental principles underlying various communication systems as well as students preparing for their college/ university/ competitive exams.INTENDED AUDIENCE : Intended audience is students, practicing engineers, technical and non-technical managers of telecom companies, students preparing for competitive exams with communication engineering subjectPRE-REQUISITES : Basic knowledge of Probability, CalculusINDUSTRY SUPPORT : Most companies in wireless communications area should find this useful. Examples are Qualcomm, Broadcom, Intel etc.
Syllabus
Week 1: Basic tools for communication, Fourier Series/Transform, Properties, Autocorrelation, Energy Spectral Density, Parsevals Relation
Week 2: Amplitude Modulation (AM), Spectrum of AM, Envelope Detection, Power Efficiency, Modulation Index
Week 3: Double Sideband Suppressed Carrier (DSB-SC) Modulation, Quadrature Carrier Multiplexing (QCM), Demodulation, Costas Receiver
Week 4: Single Sideband Modulation (SSB), Hilbert Transform, Complex Pre-envelope/ Envelope, Demodulation of SSB, Vestigial Sideband Modulation (VSB)
Week 5: Angle Modulation, Frequency Modulation (FM), Phase Modulation (PM), Modulation Index, Instantaneous Frequency
Week 6: Spectrum of FM Signals, Carsons Rule for FM Bandwidth, Narrowband FM Generation, Wideband FM Generation via Indirect Method, FM Demodulation
Week 7: Introduction to Sampling, Spectrum of Sampled Signal, Aliasing, Nyquist Criterion, Signal Reconstruction from Sampled Signal, Pulse Amplitude Modulation
Week 8 :Quantization, Uniform Quantizers – Midrise and Midtread, Quantization noise, Lloyd Max Quantization Algorithm, Non uniform Quantizers, Delta Modulation, Differential Pulse Code Modulation (DPCM)
Week 9: Basics of Probability, Conditional Probability, MAP Principle
Week 10: Random Variables, Probability Density Functions, Applications in Wireless Channels
Week 11: Basics of Random Processes, Wireless Fading Channel Modeling
Week 12: Gaussian Random Process, Noise, Bit-Error and Impact on Wireless Systems
Week 2: Amplitude Modulation (AM), Spectrum of AM, Envelope Detection, Power Efficiency, Modulation Index
Week 3: Double Sideband Suppressed Carrier (DSB-SC) Modulation, Quadrature Carrier Multiplexing (QCM), Demodulation, Costas Receiver
Week 4: Single Sideband Modulation (SSB), Hilbert Transform, Complex Pre-envelope/ Envelope, Demodulation of SSB, Vestigial Sideband Modulation (VSB)
Week 5: Angle Modulation, Frequency Modulation (FM), Phase Modulation (PM), Modulation Index, Instantaneous Frequency
Week 6: Spectrum of FM Signals, Carsons Rule for FM Bandwidth, Narrowband FM Generation, Wideband FM Generation via Indirect Method, FM Demodulation
Week 7: Introduction to Sampling, Spectrum of Sampled Signal, Aliasing, Nyquist Criterion, Signal Reconstruction from Sampled Signal, Pulse Amplitude Modulation
Week 8 :Quantization, Uniform Quantizers – Midrise and Midtread, Quantization noise, Lloyd Max Quantization Algorithm, Non uniform Quantizers, Delta Modulation, Differential Pulse Code Modulation (DPCM)
Week 9: Basics of Probability, Conditional Probability, MAP Principle
Week 10: Random Variables, Probability Density Functions, Applications in Wireless Channels
Week 11: Basics of Random Processes, Wireless Fading Channel Modeling
Week 12: Gaussian Random Process, Noise, Bit-Error and Impact on Wireless Systems
Tags
Related Courses
Preparing for the AP* Statistics ExamUniversity of Houston System via Coursera Exploration et production de données pour les entreprises
University of Illinois at Urbana-Champaign via Coursera Исследование и генерация данных для принятия бизн.-реш.
University of Illinois at Urbana-Champaign via Coursera Ableton Tips and Tricks
CreativeLive Sampling in R
DataCamp