Course Name: Probability and Random Variables/ Processes for Wireless Communications

Course abstract

Concepts in probability and random variables/ processes play a fundamental role in understanding various aspects of wireless communication systems. Characterizing several components of wireless systems such as the average transmit power, bit-error rate and behavior of the fading channel coefficient requires knowledge of principles of random variables and processes. This course 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.


Course Instructor

Media Object

Prof. Aditya K. Jagannatham

Prof. Aditya K. Jagannatham (http://home.iitk.ac.in/~adityaj/index.html) received his Bachelors degree from the Indian Institute of Technology, Bombay and M.S. and Ph.D. degrees from the University of California, San Diego, U.S.A.. From April 07 to May 09 he was employed as a senior wireless systems engineer at Qualcomm Inc., San Diego, California, where he worked on developing 3G UMTS/WCDMA/HSDPA mobile chipsets as part of the Qualcomm CDMA technologies division. His research interests are in the area of next-generation wireless communications and networking, sensor and ad-hoc networks, digital video processing for wireless systems, wireless 3G/4G cellular standards and CDMA/OFDM/MIMO wireless technologies. He has contributed to the 802.11n high throughput wireless LAN standard and has published extensively in leading international journals and conferences. He was awarded the CAL(IT)2 fellowship for pursuing graduate studies at the University of California San Diego and in 2009 he received the Upendra Patel Achievement Award for his efforts towards developing HSDPA/HSUPA/HSPA+ WCDMA technologies at Qualcomm. Since 2009 he has been a faculty member in the Electrical Engineering department at IIT Kanpur, where he is currently an Associate Professor, and is also associated with the BSNL-IITK Telecom Center of Excellence (BITCOE). At IIT Kanpur he has been awarded the P.K. Kelkar Young Faculty Research Fellowship (June 2012 to May 2015) for excellence in research. His popular video lectures for the NPTEL (National Programme on Technology Enhanced Learning) course on Advanced 3G and 4G Wireless Mobile Communications can found at the following YouTube link ( NPTEL 3G/4G ).
More info

Teaching Assistant(s)

NEERAJ VARSHNEY

Doctor of Philosophy
DEPARTMENT OF ELECTRICAL ENGINEERING
IIT Kanpur

ANKIT KUDESHIA

Doctor of Philosophy
DEPARTMENT OF ELECTRICAL ENGINEERING
IIT Kanpur

 Course Duration : Jan-Feb 2017

  View Course

 Enrollment : 01-Jan-2017 to 23-Jan-2017

 Exam registration : 30-Jan-2017 to 27-Feb-2017

 Exam Date : 26-Mar-2017

Enrolled

3336

Registered

216

Certificate Eligible

133

Certified Category Count

Gold

1

Silver

0

Elite

35

Successfully completed

97

Participation

58

Success

Elite

Gold





Legend

>=90 - Elite + Gold
60-89 - Elite
40-59 - Successfully Completed
<40 - No Certificate

Final Score Calculation Logic

  • Assignment Score = Average of best 3 out of 4 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score.
Probability and Random Variables/ Processes for Wireless Communications - Toppers list
Top 1 % of Certified Candidates

SMITH SUDHAKARAN THAVALAPILL 97%

BIRLA VISHVAKARMA MAHAVIDYALAYA ENGINEERING COLLEGE


Top 2 % of Certified Candidates

BISWARUP DEBNATH 85%

INSTITUTE OF ENGINEERING & MANAGEMENT

P KAVITHA 83%

NATIONAL ENGINEERING COLLEGE


Top 5 % of Certified Candidates

ANMOAL PORWAL 82%

ARMY INSTITUTE OF TECHNOLOGY

MRITYUNJAY KUMAR 80%

BIRLA INSTITUTE OF TECHNOLOGY

GUDIVADA BUDHARCHITHA 78%

R.V.R. & J.C. COLLEGE OF ENGINEERING

MANDAR RAVINDRA NALAVADE 77%

MIT ACADEMY OF ENGINEERING

Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.