Suswagatam! I am an MS student in the EE1- Communications & Signal Processing group under Prof. K. Giridhar and Prof. Abhishek Sinha in the Department of Electrical Engineering, IIT Madras. I joined here in July, 2016 and am working in the area of Wireless Communications, Online Learning and Network Theory.

Background

Education:

  • Indian Institute of Technology Madras- M.S Electrical Engineering, CGPA- 9/10 (2016-present)
  • Telecom ParisTech- Advanced Communication Network Diploma, CGPA- 4/4 with "Mention Tres Bien" (2018-2019)
  • B.P. Poddar Institute of Management and Technology- B.Tech Electronics & Communication Engineering, CGPA- 8.72/10 (2011-2015)

Research Papers on Wireless Communication:

  • Subhankar Banerjee, K.Giridhar," A Novel Method for Non-Stationary CFO Estimation and Tracking in Inter-UAV OFDM Links". Published in VTC fall 2019 workshop for Swarm Intelligence: Autonomous and Connected Unmanned Aircraft Systems, Hawaii, USA
  • Subhankar Banerjee, Manideep Dunna, K.Giridhar, " Channel Estimation for SM-MIMO Systems", Submitted to IEEE Communication Letters
  • Subhankar Banerjee, Krishna Madan, K.Giridhar, " Downlink Preamble Design for Non-Minimum phase HETNET Channels", under preparation for submission in IEEE Transactions on Vehicular Technology
  • Subhankar Banerjee, Chung Shue Chen, Marceau Coupechoux, K.Giridhar, "Joint Power and Sub-Carrier Allocation in Multi-Cell NOMA", under preparation for submission in IEEE Transactions on Wireless Communication
  • Subhankar Banerjee, K.Giridhar, "A Novel Method for fast time-varying CFO Tracking", Under Preparation

Research Papers on Online Learning and Network Theory:

  • Subhankar Banerjee, Rajarshi Bhattacharjee, Abhishek Sinha, "Fundamental Limits of Age-of-Information in Stationary and Non-stationary Environments" submitted to IEEE ISIT 2020
  • Rajarshi Bhattacharjee, Subhankar Banerjee, Abhishek Sinha,"Regret Analysis for Online Caching Problem" Preparing for submission in ACM SIGMETRICS 2020

Research Presentations:

  • Subhankar Banerjee, Krishna Madan, C.R. Venkatesh and K.Giridhar, "Downlink Preamble Design For Accurate Timing Synchronization in Ultra-Dense Cellular Network", presented at Wireless World Research Forum Meeting 39, 2017, Barcelona, Spain
  • Subhankar Banerjee, K.Giridhar, "Near Optimal Channel Estimation for SM-MIMO systems", Poster presented at JTG summer school 2019, held at IIT Madras

Research Experience on Wireless Communication:

  • Time-Varying CFO Estimation and Tracking
  • Channel Estimation for Spatially Modulated MIMO System
  • Timing Synchronization in Ultra-Dense HETNET Cellular Network for OFDM Based Systems
  • Joint Power and Sub-Carrier Allocation in Multi-Cell NOMA systems
  • Link abstraction for ML Receiver for MIMO and Interference Channels

Research Experience on Online Learning and Networking:

  • Regret Analysis for Online Caching Problem
  • Minimizing Age of Information in Adversarial Setting

Projects:

  • Multi-Target Shrinkage Estimation- as a part of the course 'Detection & Estimation Theory'
  • Transient Behavior of LMS Algorithm- as a part of the course 'Adaptive Signal Processing'
  • Blind Channel Estimation for OFDM systems- as a part of the course 'Multi-Carrier Communication'
  • Image Steganography using Wavelet Transform- B.Tech Final Year Project

Industrial Project Experience:

  • Block Modulated Strategic Communication- Funded by Bharat Electronics Limited (BEL)
  • Data Link Project- Funded by Defence Research and Development Organization (DRDO)

Teaching Experience:

  • Worked as a Teaching Assistant for several courses at IIT Madras

Courses:

  • Communications & Signal Processing: Introduction to Wireless Communications, Multicarrier Communications, Detection and Estimation Theory, Digital Modulation and Coding, Analog Communication, Information Theory and Coding, Signals and Systems, Digital Communications, Digital Signal Processing, Adaptive Signal Processing, Arcitecture of 4G network
  • Mathematics: Probability and Statistics, Applied Linear Algebra, Propagation in Graph


G.O.A.T

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