Challenges and Opportunities of Future Rural Wireless Communications

no code implementations • 11 Aug 2021 • Yaguang Zhang, David J. Love, James V. Krogmeier, Christopher R. Anderson, Robert W. Heath, Dennis R. Buckmaster

Broadband access is key to ensuring robust economic development and improving quality of life.

Optimizing Coverage and Capacity in Cellular Networks using Machine Learning

no code implementations • 22 Oct 2020 • Ryan M. Dreifuerst, Samuel Daulton, Yuchen Qian, Paul Varkey, Maximilian Balandat, Sanjay Kasturia, Anoop Tomar, Ali Yazdan, Vish Ponnampalam, Robert W. Heath

Wireless cellular networks have many parameters that are normally tuned upon deployment and re-tuned as the network changes.

Bayesian Optimization BIG-bench Machine Learning +1

DeepWiPHY: Deep Learning-based Receiver Design and Dataset for IEEE 802.11ax Systems

no code implementations • 19 Oct 2020 • Yi Zhang, Akash Doshi, Rob Liston, Wai-tian Tan, Xiaoqing Zhu, Jeffrey G. Andrews, Robert W. Heath

In this work, we develop DeepWiPHY, a deep learning-based architecture to replace the channel estimation, common phase error (CPE) correction, sampling rate offset (SRO) correction, and equalization modules of IEEE 802. 11ax based orthogonal frequency division multiplexing (OFDM) receivers.