Students: Mihir Laghate

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Mihir Laghate was a PhD student in Electrical Engineering at the University of California, Los Angeles (UCLA) from September 2012 to June 2017. He is currently working at Qualcomm Technology Inc. While at UCLA, he worked with Prof. Danijela Čabrić on extending radio scene analysis methods to learn higher-layer information about the primary network such as the channel access schemes employed and the network topology. He also worked on countering statistical attacks in cooperative spectrum sensing as well as implementing receivers and blind modulation classifiers on Universal Software Defined Radios (USRPs).

His latest CV can be downloaded here: CV

Education

Awards

  • Received Best-in-Session-Presentation award at IEEE Infocom 2017
  • Received NSF student travel grant to attend IEEE DySPAN 2017
  • Ranked first in the Signals and Systems stream of the UCLA EE Ph.D. examination in 2014
  • Recipient of Guru Krupa Fellowship from the Guru Krupa Foundation
  • Recipient of Department Fellowship from the Electrical Engineering Department, UCLA

Projects

Dynamic spectrum access by learning primary network topology

The goal is to learn and utilize higher-layer information about the primary network using cooperation in the cognitive radio network. This includes primary network topology, channel access schemes, and traffic statistics.

DARPA-CLASIC: Cognitive radio Low-energy signal Analysis Sensor ICs

  • Developed methods to classify the primary network's channel access scheme as TDMA, CDMA, OFDMA, or contention-based by observing the signals received at a single wideband cognitive radio. Currently extending work to classify FHSS and FDMA.
  • Implementing modulation type and level classification methods on NI Ettus USRPs using GNURadio, C++, and Python

IARPA-RiM4S: Reliable Inference with Missing, Masked, Malfunctioning or Malicious Sensors

  • Developed methods to identify and counteract the effect of malicious cognitive radios participating in cooperative spectrum sensing
  • Identification was proposed by learning the structure of a Bayesian network representation of the sensor reports while spectrum sensing was proposed using a loopy belief propagation algorithm.

Publications

Journal

Conferences and Workshops

Master's Thesis

  • M. Laghate, "Downlink Stochastic Power Control for Cellular Networks with Femto Base Stations", M.Tech. Thesis, Indian Institute of Technology Bombay, 2012
  • Adviser: Prof. Dr. Abhay Karandikar

Contact Information

  • Email:smvlaghate-at-ucla.eduuu
  • Phone: (Lab) +1 310 206 9252
  • Profiles: