MachineLearning

Virtual DPD Neural Network Predistortion for OFDM-based MU-massive MIMO
The nonlinearities of power amplifiers in massive MIMO arrays introduce unwanted spectral regrowth, which is typically avoided via …
Chance Tarver, Alexios Balalsoukas-Slimining, Christoph Studer, Joseph R Cavallaro
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Virtual DPD Neural Network Predistortion for OFDM-based MU-massive MIMO
New Preprint Available. Neural Networks are taking over DPD!
I have a new preprint available for my submission to the 2019 IEEE International Workshop on Signal Processing Systems in Nanjing, China. The paper is titled “Design and Implementation of a Neural Network Based Predistorter for Enhanced Mobile Broadband” and is available here.
Chance Tarver
Last updated on Apr 28, 2023 1 min read
New Preprint Available. Neural Networks are taking over DPD!
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, …
Chance Tarver, Matthew Tonnemacher, Vikram Chandrasekhar, Hao Chen, Boon Loong Ng, Jianzhong Zhang, Joseph R Cavallaro, Joseph Camp
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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 …
Matthew Tonnemacher, Chance Tarver, Joseph Cavallar, Joseph Camp
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Machine Learning Enhanced Channel Selection for Unlicensed LTE
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.
Chance Tarver
Last updated on Apr 28, 2023 1 min read
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 …
Matthew Tonnemacher, Chance Tarver, Vikram Chandrasekhar, Hao Chen, Pengda Huang, Boon Loong Ng, Jianzhong Charlie Zhang, Joseph R Cavallaro, Joseph Camp
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Opportunistic channel access using reinforcement learning in tiered CBRS networks