Research

Current Project:

• IEEE 802.11be MAC standardization activities.

Legacy Projects:

• Machine Learning (ML)/Deep Learning for Wireless Communications:
  1. Deep Learning for Coding-Decoding Process
  2. Reservoir Computing/Echo State Network (ESN) for MIMO symbol detection.
  3. ML for Energy Efficient Communications

• Deep Reinforcement Learning (RL):
  1. Deep RL for Radio Frequency (RF) parameter optimization

• 3D Massive MIMO/Full Dimension (FD) MIMO
  1. Joint Channel Parameter Estimation
  2. Optimum Precoder Design and Power Allocation Strategy

• Millimeter Wave Massive MIMO for 5G and Beyond:
  1. Channel Estimation for 3D Massive MIMO– estimation of direction of arrival (DoA), path delay, and complex channel gains.
  2. Achievable Rate Analysis and Optimum Precoder Design
  3. Channel estimation and performance characterization of Multi-cell Multi-user Massive MIMO OFDM systems.
  4. Downlink Beamforming for Frequency Division Duplex (FDD) massive MIMO systems.

A talk on mmWave massive  MIMO given for Wireless@VT seminar series is available here.