CBRS

Enabling a “Use-or-Share” Framework for PAL–GAA Sharing in CBRS Networks via Reinforcement Learning

By implementing reinforcement learning-aided listen-before-talk (LBT) schemes over a citizens broadband radio service (CBRS) network, we increase the spatial reuse at secondary nodes while minimizing the interference footprint on higher-tier nodes. …

2019 ECE Affiliates Day

The ECE Corporate Affiliates Day was recently on March 29th. I was involved in two research posters. 1st was the neural network based DPD that I am working on with our VIP team.

Method and apparatus for improving coexistence performance by measurements in wireless communication systems

A method of operating a base station (BS) for a coexistence operation in a wireless communication system is provided. The method comprises performing a first measurement of first signals received from neighbor BSs over channels that are shared with …

DySPAN Paper Invited for Submisssion to TCCN

The 2018 DySPAN paper was invited for submission to IEEE Transactions on Cognitive Communications and Networking (TCCN) for a special issue featuring the top papers from this year’s conference. We accepted the invitation and have made improvements to the paper including additional simulations focusing on new topologies.

Opportunistic channel access using reinforcement learning in tiered CBRS networks

The upcoming deployments of devices on the new 3.5 GHz, Citizens Broadband Radio Service (CBRS) is expected to enable innovation by lowering the barrier to entry into LTE and other technologies. With a three-tiered spectrum-sharing solution, the CBRS …

DySPAN 2018 Paper Accepted

I just got notified that our submission to DySPAN 2018, Opportunistic Channel Access Using Reinforcement Learning in Tiered CBRS Networks, was accepted. Matthew Tonnemacher from SMU and Samsung Research America led this paper which focuses on using machine learning to help overcome the hidden terminal problem in the emerging CBRS band.