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Speakers

Prof. Aditya K. Jagannatham

Prof. Aditya K. Jagannatham is a Professor in the Electrical Engineering department at IIT Kanpur, where he holds the Arun Kumar Chair Professorship. He is one of India’s best-known experts and trainers on 5G technology. He 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, San Diego, California, where he was a part of the Qualcomm CDMA technologies (QCT) division. His research interests are in the area of next generation wireless networks, with a special emphasis on various 5G technologies such as massive MIMO, mmWave MIMO, FBMC, NOMA, Full Duplex and others.

His research articles have been published extensively in leading international IEEE journals and conferences. He has successfully conducted several Massive Open Online Courses (MOOCs) on various topics such as MIMO OFDM Wireless Systems, Probability and Random Processes, Signals and Systems, Principles of Communication Systems, Optimization, Machine Learning, which have been widely adopted and appreciated. A book authored by him titled Principles of Modern Wireless Communications Systems has been published by McGraw Hill Education and comprehensively covers several key aspects of modern wireless technologies. He has been recognized with several awards described below.

List of Awards of Prof. Aditya K. Jagannatham

  • CAL(IT)2 fellowship at the University of California San Diego
  • Upendra Patel Achievement Award at Qualcomm
  • P.K. Kelkar Young Faculty Research Fellowship-I (2012-2015)
  • P.K. Kelkar Young Faculty Research Fellowship-I (2015-2018)
  • Qualcomm Innovation Fellowship (QInF)-2018
  • Arun Kumar Chair (2019-2022)
  • IITK Excellence in Teaching Award (2019)

List of MOOCs by Prof. Aditya K. Jagannatham

List of Recent Training Programs Conducted by Prof. Aditya K. Jagannatham

Associate Instructors

Suraj Srivastava

Suraj Srivastava received the M.Tech. degree in Communication, Network & Signal Processing from Indian Institute of Technology (IIT) Roorkee. After completion he was employed as a Staff-I Systems Design Engineer with Broadcom Research India Pvt. Ltd., Bangalore. He was also employed as a Lead Engineer with Samsung Research India, Bangalore, where he worked on developing layer-2 of the 3G UMTS/ WCDMA/ HSDPA modem. He is currently working toward the Ph.D. degree with the Department of Electrical Engineering, Indian Institute of Technology, Kanpur, India. His research interests include 5G mmWave and Terahertz MIMO Wireless Technology, OTFS, Sparse Signal Processing, Distributed Signal Processing for Wireless Sensor Networks (WSNs) for IoT. He was awarded Qualcomm Innovation Fellowship in (QIF)-2018. He has been a QIF finalist in two consecutive other years (2020 & 2021), and was the topper of his M.Tech batch at IIT Roorkee. He has several high impact publications in IEEE Transactions at the intersection of ML and 5G. Some of his key recent publications are below

List salient publications of Suraj Srivastava


  • S. Srivastava, R. K. Singh, A. K. Jagannatham and L. Hanzo "Bayesian Learning Aided Simultaneous Row and Group Sparse Channel Estimation in Orthogonal Time Frequency Space Modulated MIMO systems", Accepted in IEEE Transactions on Communications, 2022

  • S. Srivastava, C. S. K. Patro, A. K. Jagannatham and L. Hanzo, "Sparse, Group-Sparse and Online Bayesian Learning Aided Channel Estimation for Doubly-Selective mmWave Hybrid MIMO OFDM Systems", IEEE Transactions on Communications, vol. 69, pp. 5843-5858, Sept. 2021

  • S. Srivastava, R. K. Singh, A. K. Jagannatham and L. Hanzo "Bayesian Learning Aided Sparse Channel Estimation for Orthogonal Time Frequency Space Modulated Systems", IEEE Transactions on Vehicular Technology, vol. 70, pp. 8343-8348, Aug. 2021

  • S. Srivastava, J. Nath and A. K. Jagannatham, "Data Aided Doubly-Selective CSI Estimation using Affine-Precoded Superimposed Pilots in Millimeter Wave MIMO-OFDM Systems", IEEE Transactions on Vehicular Technology, vol. 70, pp. 6983-6998, July 2021

  • M. Majumder, H. Saxena, S. Srivastava, and A. K. Jagannatham, "Optimal Bit Allocation-Based Hybrid Precoder-Combiner Design Techniques for mmWave MIMO-OFDM Systems", IEEE Access, vol. 9, pp. 54109-54125, April 2021

  • S. Srivastava, P. Singh, A. K. Jagannatham, A. Karandikar and L. Hanzo, "Bayesian Learning-Based Doubly-Selective Sparse Channel Estimation for Millimeter Wave Hybrid MIMO-FBMC-OQAM", IEEE Transactions on Communications, vol. 69, pp. 529-543, Jan. 2021

  • S. Srivastava, P. Sharma, S. Dwivedi, A. K. Jagannatham and L. Hanzo, "Fast Block LMS Based Estimation of Angularly Sparse Channels for Hybrid Wideband Millimeter Wave MIMO Systems", IEEE Transactions on Vehicular Technology, vol. 70, pp. 666-681, Jan. 2021

  • K. P. Rajput, A. Kumar, S. Srivastava, A. K. Jagannatham and L. Hanzo, "Bayesian Learning-based Linear Decentralized Sparse Parameter Estimation in MIMO Wireless Sensor Networks with Perfect and Imperfect CSI", IEEE Transactions on Communications, vol. 69, pp. 6236-6250, Sept. 2021

  • P. Singh, S. Srivastava, A. K. Jagannatham and L. Hanzo, "Second-Order Statistics-Based Semi-Blind Techniques for Channel Estimation in Millimeter-Wave MIMO Analog and Hybrid Beamforming", IEEE Transactions on Communications, vol. 68, pp. 6886-6901, Nov. 2020

  • S. Srivastava, M. S. Kumar, A. Mishra, S. Chopra, A. K. Jagannatham and L. Hanzo, "Sparse Doubly-Selective Channel Estimation Techniques for OSTBC MIMO-OFDM Systems: A Hierarchical Bayesian Kalman Filter Based Approach", IEEE Transactions on Communications, vol. 68, pp. 4844-4858, Aug. 2020

  • A. Chawla, P. S. Kumar, S. Srivastava and A. K. Jagannatham "Centralized and Distributed Millimeter Wave Massive MIMO based Data Fusion with Perfect and Bayesian Learning (BL)-based Imperfect CSI", Accepted in IEEE Transactions on Communications

  • S. Srivastava, A. Mishra, A. Rajoriya, A. K. Jagannatham and G. Ascheid, "Quasi-Static and Time-Selective Channel Estimation for Block-Sparse Millimeter Wave Hybrid MIMO Systems: Sparse Bayesian Learning (SBL) Based Approaches", IEEE Transactions on Signal Processing, vol. 67, pp. 1251-1266, Mar. 2019
































































Prem Singh

Prem Singh received M. Tech and PhD degrees in Electrical Engineering from the Indian Institute of Technology Kanpur, India, in 2011 and 2020 respectively. He worked as Project Executive Officer on the Indigenous 5G TestBed project, where he developed hardware and software algorithms for an end-to-end 3GPP compliant 5G-NR Testbed. He was one of the finalists (top two) for the Indian National Academy of Engineering (INAE) Innovative Student Project Award 2021 at the doctoral level. He was awarded the Best PhD Thesis award in the 4th IEEE International Conference on Information and Communication Technology (CICT) 2020 organized by IIIT Kancheepuram, India. His research interests lie in the area of parameter estimation and transceiver design for 5G and beyond wireless technologies including Filter Bank Multicarrier (FBMC), Orthogonal Time-Frequency space (OTFS), massive MIMO and Millimeter-wave. His interests also lie in the area of designing practical 5G wireless systems using 3GPP standards. He is currently working as an assistant professor at IIIT Bangalore. Some of his key recent publications are below

List salient publications of Prem Singh

  • Prem Singh, Khushboo Yadav, Himanshu B. Mishra, and Rohit Budhiraja, "BER Analysis for OTFS Zero-Forcing Receiver.” IEEE Transactions on Communications, 2022 [to appear].

  • Himanshu B. Mishra, Prem Singh, Abhishek K. Prasad, and Rohit Budhiraja, "Iterative Joint Channel Estimation and Data Detection for OTFS Using Superimposed Pilots.” IEEE Transactions on Wireless Communications, 2021.

  • Suraj Srivastava, Prem Singh, Aditya K Jagannatham, Abhay Karandikar and Lajos Hanzo, "Bayesian Learning-Based Doubly-Selective Sparse Channel Estimation for Millimeter Wave Hybrid MIMO-FBMC-OQAM” IEEE Transactions on Communications, vol. 69, no. 1, pp. 529--543, 2021.

  • Prem Singh, Suraj Srivastava, Aditya K Jagannatham and Lajos Hanzo, "Second-Order Statistics-Based Semi-Blind Techniques for Channel Estimation in Millimeter-Wave MIMO Analog and Hybrid Beamforming.” IEEE Transactions on Communications, vol. 68, no. 11, pp. 6886--6901, 2020.

  • Prem Singh, H. B. Mishra, A. K. Jagannatham, K. Vasudevan, and L. Hanzo. "Uplink sum-rate and power scaling laws for multi-user massive MIMO-FBMC systems," IEEE Transactions on Communications, vol. 68, no. 1, pp. 161--176, 2020.

  • Prem Singh, R. Budhiraja, and K. Vasudevan. "Receivers for VBLAST FBMC-OQAM Systems," IEEE Communications Letters, vol. 24, no. 4, pp. 767--771, 2020.

  • Prem Singh, H. B. Mishra, A. K. Jagannatham, and K. Vasudevan, "Semi-blind, training, and data-aided channel estimation schemes for MIMO-FBMC-OQAM systems," IEEE Transactions on Signal Processing, vol. 67, no. 18, pp. 4668--4682, 2019.

  • Prem Singh, R. Budhiraja, and K. Vasudevan, "Probability of error in MMSE detection for MIMO-FBMC-OQAM systems," IEEE Transactions on Vehicular Technology, vol. 68, no. 8, pp. 8196--8200, 2019.

  • Prem Singh, R. Budhiraja, and K. Vasudevan, "SER analysis of MMSE combining for MIMO FBMC-OQAM systems with imperfect CSI," IEEE Communications Letters, vol. 23, no. 2, pp. 226--229, 2019.

  • Prem Singh, E. Sharma, R. Budhiraja, and K. Vasudevan, "CFO and channel estimation for frequency selective MIMO-FBMC/OQAM systems." IEEE Wireless Communications Letters, vol. 7, no. 5, pp. 844--847, 2018.
Recent Book Chapters:
  • Prem Singh and Ekant Sharma, Chapter Title: "FBMC: A Waveform Candidate for Beyond 5G", accepted for publication in Springer Nature, Book Title: "A Glimpse Beyond 5G in Wireless Networks", Publisher: Springer Nature [to appear].

  • Ekant Sharma and Prem Singh, Chapter title: "Full-duplex Multi-hop Communication for Beyond 5G ", accepted for publication in Springer Nature, Book Title: "A Glimpse Beyond 5G in Wireless Networks", Publisher: Springer Nature [to appear].