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Pavan Srinath

Pavan Srinath

Software Engineer

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location of Pavan SrinathOrsay, Île-de-France, France

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  • Timeline

  • About me

    6G Research Engineer at Nokia Bell Labs France

  • Education

    • B.M.S. College of Engineering

      2001 - 2005
      Bachelor of Engineering (B.E.) Electronics and Communications

    • Indian Institute of Science

      2006 - 2008
      Master of Engineering (M.Eng.) Telecommunication

      Relevant coursework (Credit): Digital Communication, Space-Time Coding, Information Theory and Coding–I and II, Matrix Theory, Random Processes, Communication Networks, TCP/IP Networking, Advanced Digital Communication, Advanced Coding Theory, CDMA and Multi-user Detection, Stochastic Process and Queuing Theory, Wireless Networks, Algebra-I

    • Indian Institute of Science (IISc)

      2008 - 2012
      PhD Wireless Communications

      Activities and Societies: Reviewer for IEEE Transactions on Information Theory, IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, and several conference papers. My doctoral work was primarily on the construction of low complexity space-time block codes (STBCs) for multiple-input, multiple-output (MIMO) systems to combat multi-path fading in a wireless environment. In particular, my research resulted in the construction of STBCs with lower ML-decoding complexity than that of existing codes without sacrificing diversity gain, coding gain, or symbol rate. For certain MIMO systems, we were able to construct STBCs with higher coding gain than that of the… Show more My doctoral work was primarily on the construction of low complexity space-time block codes (STBCs) for multiple-input, multiple-output (MIMO) systems to combat multi-path fading in a wireless environment. In particular, my research resulted in the construction of STBCs with lower ML-decoding complexity than that of existing codes without sacrificing diversity gain, coding gain, or symbol rate. For certain MIMO systems, we were able to construct STBCs with higher coding gain than that of the best known STBCs using tools from division algebra and Galois theory. Show less

  • Experience

    • Robert Bosch Engineering and Business Solutions Ltd.

      Sept 2005 - Jul 2006
      Software Engineer

      I was a developer for the Human-Machine interface (HMI) of Ford High-series Radio navigation systems (Ford-HSRNS).

    • Broadcom

      Jan 2013 - Nov 2013
      Scientist, Staff II

      As a member of the physical layer algorithms team for Long term evolution-Advanced (LTE-A) user equipment (UE) receiver design, I worked on the following:1) Studied and evaluated various techniques for rejecting/combining interference in the downlink control channel detection. The goal was to identify the best technique for each scenario.2) Fine tuning of the downlink hybrid-automatic repeat request (HARQ) performance. The goal was to get the best performance for the given memory constraints. Show less

    • University of Cambridge

      Nov 2014 - Jun 2018
      Research Associate in Signal Processing and Communications

      I worked on computationally feasible methods with provable theoretical guarantees for high-dimensional statistical inference. In particular, my research was on the following:1) Low-complexity algorithms for high-dimensional sparse linear inverse problems with applications to compressed sensing, channel-coding for communication systems, and machine learning.2) Non-parametric shrinkage estimation of high-dimensional (sparse) sequences.My other responsibilities included the following: 1) Small group teaching for several M.Eng. modules at the University of Cambridge.2) Project Assessor for the following M.Eng. projects: Reed Solomon Coding for DNA Storage, DNA storage systems. Show less

    • Nokia Bell Labs

      Mar 2019 - now
      Research Engineer

      System-level analysis of 6G massive multi-user MIMO uplink gNB reception and downlink gNB transmission (L1 and L2 aspects). This project includes the following:1) Co-implementation of a system-level simulator in TensorFlow and NumPy with explicit channel generation and interference modelling, 5G LDPC code generation with rate-matching capabilities, link-adaptation and HARQ, multiple UE scheduling, dynamic UE rank selection.2) A detailed study of algorithms for linear and non-linear uplink MU-MIMO reception and linear transmit-precoding with hybrid beamforming for downlink MU-MIMO transmission. These algorithms are intended to enhance the network throughput and involve, for example, the design of power control parameters and resource allocation (L2 features) and SINR maximization (L1 feature).3) Computational complexity and energy-efficiency analysis of various algorithms and MIMO architectures.4) Application of machine-learning techniques wherever relevant and appropriate.Other activities:1) Supervised and semi-supervised learning for UE localization.2) Supervision of Master’s Thesis and PhD internships. Show less

  • Licenses & Certifications