Machine learning (ML) uses a data-driven approach to ensure real-world performance where rigid model-driven approaches can’t.
ML-driven spectrum sensing enables rapid intelligent awareness and identification of RF devices & activity not previously feasible.
ML enables end-to-end optimization of core radio functions, benefitting L1 & system performance beyond traditional approaches.
DeepSig is pioneering the use of deep learning to realize state of the art signal processing and radio systems by developing fundamentally new methodologies and software systems for the design and optimization of wireless communications. By creating new tools, algorithms, and approaches for signal processing systems, DeepSig is able to achieve unparalleled results in system performance.
The performance goals for 5G are ambitious, impressive, and will be world-changing. Achieving them is also a significant challenge, and as the world races to develop, test, and deploy 5G technology, existing approaches using traditional design methodologies are starting to show some of their limits.
Our process for creating learned signal processing systems enables us to use a common core software architecture for a range of different applications while still customizing and optimizing model performance for specific application and deployment requirements.
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A new class of RF sensing and awareness using DeepSig’s pioneering application of AI to radio systems.
An easy-to-use method for visualizing your signal captures and labeling them and training new models for use in AI systems.
OmniPHY enables a new, radically different approach to communications by leveraging Machine Learning.
DeepSig is rapidly building out capabilities within partial reference 5G-NR RAN L1 implementation.
1201 Wilson Blvd, Floor 27
Arlington, VA, 22209
info@deepsig.io
703.340.1451