DeepSig Blog

5G wireless technology promises to dramatically improve the information, computer and communications industries by enabling countless new services with diverse requirements. The complex technologies on the horizon manage massive amounts of data. 5G wireless networks need machine learning (ML) to manage the volume of data with near light speed. More specifically, deep learning in 5G must be applied to reduce power consumption and improve performance.

My first engineering interview was for a Summer internship at a small software company. The founder & president invited me to his home to interview one Saturday morning over Spring Break. Over a cup of coffee, we discussed my background, my interests, and what working at his company would be like while his children played around us. I had no way of knowing at the time, but it was one of the best job interviews I would have in my career.

It is clear that artificial intelligence will have a significant role to play in both improving the performance of existing wireless systems and in the fundamental capability of future systems, including 5G consumer wireless systems. DeepSig’s CTO and pioneer in the field, Tim O’Shea, is pleased to participate on a panel discussion on AI and 5G at IEEE Globecom 2018, from Dec 9-13 in Dubai. Dr. O’Shea will also give a podium talk on DeepSig's applied research and commercialization efforts, and is serving as the TPC for WS-18: Machine Learning for Communications.

DeepSig will once again be speaking at NVIDIA’s flagship conference, GTC Silicon Valley, between March 17th and 21st of 2019. The DeepSig team was previously invited to speak at GTC Silicon Valley 2018 and then at GTC DC 2018, and we are excited to once again be contributing to the conference program.

DeepSig gave the first public demonstration of a channel autoencoder running over-the-air at IEEE DySPAN 2018 in Seoul, South Korea. Co-founder & CTO Tim O’Shea presented DeepSig’s OmniPHY commercial software product for learned physical layers, showing it running live between two software-defined radios. This uses the same software product that’s being tested over NASA’s satellite system, TDRSS.