S. S. Krishna Chaitanya Bulusu

S. S. Krishna Chaitanya Bulusu

Associate Professor
krishnachaitanya.bulusu@mahindrauniversity.edu.in

Dr. Krishna Chaitanya Bulusu is an Associate Professor at École Centrale School of Engineering, Mahindra University, India. He holds a Ph.D. in 5G Radiocommunications from CNAM, Paris, and an M.S. in Mobile communication from Télécom Paris, Paris. He has over 15 years of experience in wireless communications, signal processing, and applied AI/ML. His research focuses on digital predistortion, behavioral modeling of nonlinear RF systems, joint communication, and sensing, and ultrawideband transmitter linearization. He has held postdoctoral positions at INSA Rennes and the University of Oulu, where he contributed significantly to 6G RF architectures and interdisciplinary collaborations. Dr. Bulusu is also a patent-holder and IEEE Senior Member, and he has published extensively in top-tier journals and conferences.

2013–2016

  • 2013–2016 Doctorate in 5G Radiocommunications, Conservatoire National des Arts et Métiers, Paris, France (Felicitations of the jury)

2007–2009

  • 2007–2009 M.Sc. Mobile Communications, Eurecom/Telecom ParisTech, Sophia Antipolis, France (3.74/4 GPA)

2001–2005

  • 2001–2005 B.Tech. Electronics and Communications Engineering, Pondicherry Engineering College, Pondicherry, India (70%, First class)

1999–2001

  • 1999–2001 Higher Secondary Education, Pragati Junior College, Kakinada, India
    Mathematics, Physics and Chemistry (87.5%, First class)

2022

  • He is an Associate Professor in the department of Electrical and Computer Engineering at École Centrale School of Engineering, Mahindra University, Hyderabad, India (2025- present)
  • Post-doctorate, CWC, University of Oulu, Oulu, Finland (2022)
  • Fellow member of Institution of Electronics and Telecommunication Engineers since 2019
  • Fellow member of Institution of Engineers (India) since 2018
  • Assistant Professor, Mahindra École Centrale, Hyderabad, India (2018–2021)
  • Post-doctorate, INSA, Rennes, France (2016–2017)
  • Associate Member of CEDRIC/LAETITIA, CNAM (France) since 2016
  • Senior member of IEEE (Microwave Society, Communication, Broadcasting etc.) since 2015
  • 5G Researcher, CNAM, Paris, France (2013–2016)
  • Algorithm Development Engineer, Navtel Systems, Houville, France (2012-2013)
  • Electronics Engineer, CNRS, Villeneue d’Ascq, France (2011–2012)
  • Project Officer, IIT Madras, Chennai, India (2010–2011)
  • Intern, Thales Communications, Colombes, France (2008-2009)
  • Systems Engineer, Polaris Software Lab, Hyderabad, India (2005–2007)

JOURNALS

  • D. Lesthuruge, K.C. Bulusu, P. Rajatheva, and M. E. Leinonen, AI-based Block Structured Framework for Behavioral Modeling and Digital Predistortion of Power Amplifiers, IEEE Transactions on Machine Learning in Communications and Networking, 2024 (Under review).
  • A. Mukherjee, P. Susarla, P. Katragunta, K. C. Bulusu, O. Silvén, M. Juntti, D. B. Jayagopi, and M. B. Lopez, Indoor Localization with Multi-domain CSI-based Deep Attention Networks in Joint Communication and Sensing Systems, Eurasip Journal on Wireless Communications and Networking, 2024. (Under review)
  • K.C. Bulusu et al., Machine Learning-Based Methods for Piecewise Digital Predistortion in 5G NR Systems, Eurasip Journal on Advances in Signal Processing, vol. 2004, no. 97, Nov. 2024
  • S. Bhayani, P. Susarla, K.C. Bulusu, O. Silven, M. Juntti, and J. Heikkila, A Novel Application of Polynomial Solvers in mmWave Analog Radio Beamforming, ACM Communications in Computer Algebra, vol. 57, no. 3, Dec 2023.
  • K.C. Bulusu, H. Shaiek, and D. Roviras, Fast Convergence HPA Linearization for Next Generation Broadcasting Systems with Fast Convergence-Digital Predistortion, IEEE Transactions on Broadcasting, vol. 67, no. 3, May 2021.
  • N. Lahbabi, K.C. Bulusu, J.-F. Helard, and M. Crussiere, Very Efficient Tone Reservation PAPR Reduction Fully Compatible with ATSC 3.0 Standard: Performance and Complexity Analysis for Practical Implementation, IEEE Access, vol. 6, Oct. 2018.
  • K.C. Bulusu et al., Quasi-optimal Tone Reservation PAPR Reduction Algorithm for Next Generation Broadcasting Systems: A Performance/complexity/latency Trade-off with Testbed Implementation, IEEE Transactions on Broadcasting, vol. 64, no.4, pp. 883-899, Dec. 2018.
  • K.C. Bulusu, M. Renfors, J. Yli-Kaakinen, H. Shaiek, and D. Roviras, Enhanced Multicarrier Techniques for Narrowband and Broadband PMR Systems, Wiley Transactions on Emerging Telecommunications Technologies, vol. 28, no. 3, Mar. 2017.
  • K.C. Bulusu, H. Shaiek, and D. Roviras, Reducing the PAPR in FBMC-OQAM Signals with Low Complex Trellis-based SLM Technique, Eurasip Journal on Advances in Signal Processing, vol. 2016, no. 1, Dec. 2016.

CONFERENCE

  • L. Silva, K. C. Bulusu, N. Tervo, and P. Rajatheva, Simplified Augmented RealValued Time-Delay Neural Network for Digital Predistortion, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025. (Accepted)
  • K.C. Bulusu et al., Simplified Real-Valued Time-Delay Neural Network for Compensation of Power Amplifier Impairments, IEEE Radio and Wireless Symposium (RWS), San Juan, Puerto Rico, 2025. (Accepted)
  • P. Susarla, S. Bhayani, K. C. Bulusu, M. B. Lopez, J. Heikkila, M. Juntti, and O. Silvén, Polynomial Solvers for mmWave beamforming, IEEE International Conference on Communications (ICC), Denver, USA, Jun. 2024.
  • A. Mukherjee, P. Susarla, P. Katragunta, K. C. Bulusu, O. Silvén, M. Juntti, D. B. Jayagopi, and M. B. Lopez, Multi-domain CSI-based Indoor Localization with Deep Attention Networks for MIMO JCAS system, IEEE International Symposium on Joint Communications and Sensing (JCAS), Oulu, Finland, 2024. (Accepted)
  • K.C. Bulusu, S. Zampato, P. Susarla, N. Tervo, A. Pärssinen, and O. Silvén, Hardware-friendly Power Amplifier Linearization in Next-Generation Broadcasting Systems, IEEE International Mediterranean Conference on Communications and Networking (MeditCom), Dubrovnik, Croatia, Sep. 2023.
  • K.C. Bulusu, B. Khan, N. Tervo, M.E. Leinonen, M.J. Sillanpää, O. Silvén, M. Juntti, and A. Pärssinen, Experimental Demonstration of a Machine Learning-based Piece-wise Digital Predistortion Method in 5G NR systems, IEEE International Microwave Symposium (IMS), San Diego, USA, Jun. 2023.
  • K.C. Bulusu, N. Tervo, P. Susarla, M.J. Sillanpää, O. Silvén, M. Juntti, and A. Pärssinen, Machine Learning-Aided Piece-wise Modeling Technique of Power Amplifier for Digital Predistortion, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Rhodes Island, Greece, Jun. 2023.
  • K.C. Bulusu, P. Susarla, H. Shaiek, D. Roviras and O. Silvén, Fast Convergence Joint Optimization of PAPR Reduction and Digital Predistortion in the Nextgeneration Broadcasting Systems, IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Beijing, China, Jun. 2023.
  • S. Chennamsetty, S. Boddu, P. Chandhar, and K. C. Bulusu, Analysis of PAPR in OTFS Modulation with Classical Selected Mapping Technique, IEEE International Conference on COMmunication Systems & NETworkS (COMSNETS), Bangalore, India, Jan. 2023.
  • K.C. Bulusu, S.S. Maddila, H. Shaiek, and D. Roviras, HPA Linearization of FBMC-OQAM Signals with Fast Convergence-Digital Predistortion, IEEE International Symposium on Wireless Communication Systems (ISWCS), Oulu, Finland, Aug. 2019.
  • K.C. Bulusu, M. Crussiere, and J.-F. Helard, A Low Complexity PAPR Reduction Algorithm for ATSC 3.0 Transmitters, IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Valencia, Spain, 2018.
  • K.C. Bulusu et al., A Low Latency Algorithm for Efficient PAPR Reduction for DVB-T2 and ATSC 3.0 Broadcast, IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Cagliari, Italy, 2017.
  • K.C. Bulusu, H. Shaiek, and D. Roviras, Linearization of FBMC-OQAM Signals with Overlapped Recursive Error Correcting Predistortion, IEEE International Symposium on Wireless Communication Systems (ISWCS), Poznan, Poland, 2016.
  • K.C. Bulusu, H. Shaiek, and D. Roviras, Impact of HPA Non-linearity on Coexistence of FBMC-OQAM Systems with PMR/PPDR System, IEEE Vehicular Technology Conference (VTC), Nanjing, China, 2016.
  • K.C. Bulusu, H. Shaiek, and D. Roviras, Reduction of PAPR of FBMC-OQAM Systems by Dispersive Tone Reservation Technique, IEEE International Symposium on Wireless Communication Systems (ISWCS), Brussels, Belgium, 2015.
  • K.C. Bulusu, H. Shaiek, and D. Roviras, Potency of Trellis-based SLM over symbol-by-symbol approach in reducing PAPR for FBMC-OQAM Signals, IEEE International Conference on Communications (ICC), London, UK, 2015.
  • K.C. Bulusu, H. Shaiek, and D. Roviras, Prediction of Spectral Regrowth for FBMC-OQAM system using Cumulants, IEEE WiMob, Larnaca, Cyprus, 2014.
  • K.C. Bulusu, H. Shaiek, D. Roviras, and R. Zayani, Reduction of PAPR for FBMC-OQAM Systems using Dispersive SLM, IEEE International Symposium on Wireless Communication Systems (ISWCS), Barcelona, Spain, 2014

DELIVERABLES

  • K.C. Bulusu et al., Energy-efficient power controls and interference mitigation, Technical contribution report in the deliverable D2.1 - French ANR-14-CE28-0026-02 ACCENT5 project, pages 57, 2015.
  • K.C. Bulusu et al., Reduction of PAPR and non-linearities effects, Technical contribution report in the deliverable D3.3 - European ICT- 318362 EMPhAtiC FP7 project, pages 110, 2014.

BOOK CHAPTER

  • K.C. Bulusu et al., Chapter 18 - Power Amplifier Effects and Peak-to-Average Power Mitigation, Orthogonal Waveforms and Filter Banks for Future Communication Systems, Elsevier/Academic Press, 2017

PATENT

  • R. Zayani, H. Shaiek, D. Roviras, K. C. Bulusu, Reduction of the crest factor and joint predistortion for amplification of multi-carrier systems, Published date: 03/05/2018, Organisation: "CNAM", Patent Nâ—¦ : WO2018078240, France

Krishna Chaitanya’s research interests lie at the intersection of AI/ML, signal processing, communications, and applied mathematics, with focus areas including:

  • AI/ML for 5G/6G RF Signal Processing: Data-driven learning for wireless system design, optimization, and adaptive signal processing.
  • Behavioral Modeling of Dynamic Nonlinear Systems: Modeling and analysis of memory effects in nonlinear devices such as power amplifiers.
  • Ultrawideband Power Amplifier Linearization: Design of digital predistortion and compensation techniques for broadband RF front ends.
  • Integrated Sensing and Communication (ISAC): Design and analysis of systems that simultaneously support information transfer and environmental awareness, enabling resource-efficient and context-aware wireless applications.
  • Indoor Localization: RF-based positioning systems using channel estimation, fingerprinting, and AI models in complex environments.
  • RF Fingerprinting and 5G/6G Security: Physical-layer authentication and anomaly detection for wireless system integrity.
  • AI-powered Smart Systems:
    • Smart Farming: AI-driven sensor fusion and decision-making for precision agriculture.
    • Smart Healthcare: Machine learning models for diagnostics, monitoring, and personalized care.
    • Smart Home: Intelligent control, automation, and energy efficiency using embedded AI.
  • Applied Mathematics for Signal Processing, Communications, and AI:
    Fundamental research in estimation theory, learning theory, system identification, nonlinear systems, inverse problems, optimization, and information theory — with applications in signal modeling, learning algorithms, and communication system analysis.

ACHIEVEMENTS

  • One among 30 worldwide recipients of Thales-French Ministry of External Affairs Scholarship