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.
Edge deployments and low-SWAP operating environments have been an important usage model for DeepSig’s commercial software products since the beginning, and we are excited to share some of our work and lessons learned in this area. Embedded applications have always been challenging for RF sensing due to the data and processing rates traditionally required, but DeepSig’s approach using deep learning is able to both improve performance and reduce power consumption.
Our presentation is titled, “Machine Learning for Wireless Communications using TensorRT and NVIDIA Xavier”, with talk ID S9693. Once the conference agenda is finalized, we will post more information here about the date and time of the talk!
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.
We will be presenting at NVIDIA's GPU Technology Conference (GTC) DC 2018, which is taking place October 22nd - 24th in Washington D.C. Building on the work presented in our GTC Silicon Valley 2018 Talk, and expanded upon in an article featured by NVIDIA, we will be presenting "Deep Learning for RF Sensing and Communications". Information about the talk can be found on the NVIDIA GTC DC website.
The abstract for the talk is below:
Machine learning is rapidly advancing the state-of-the-art in algorithm performance for wireless telecommunications systems. Building on our work presented at GTC Silicon Valley, recasting fundamental wireless signal processing problems as data-centric deep learning problems, we present further evidence that learned signal processing algorithms can empower the next generation of wireless systems with significant reductions in power consumption and improvements in density, throughput, and accuracy when compared to the brittle and manually designed systems of today. This talk will introduce the core enabling technologies and fundamental approaches, share our latest work and results in deep learning-based sensing and learned communications, and discuss applications such as 5G and IoT, commercial cyber-threat sensing, and defense RF sensing to illustrate the wide range of fields these technologies will impact over the next several years.
If you'll be at GTC DC and are interested in chatting, please send us a note at email@example.com! We would love to meet up at the conference or host you in our offices just outside of D.C. while you're in town.
DeepSig presented its groundbreaking work in learned adaptive communications systems at the NASA Glenn Research Center on Jun 28th as part of the keynote for the IEEE Cognitive Communications for Aerospace Applications Workshop. We are looking to further developing our technology for the future of highly efficient adaptive space communications systems!