SharedSpectrum

Machine Learning Enhanced Channel Selection for Unlicensed LTE

We propose a mechanism for unlicensed LTE channel selection that not only takes into account interference to and from Wi-Fi access points but also considers other LTE operators in the unlicensed band. By collecting channel utilization statistics and …

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. …

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 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.