DeepSig Wins NTIA Grant for AI-Driven Spectrum Innovations

DeepSig Awarded NTIA Grant for Spectrum Sensing Advancement

DeepSig, a leading innovator in AI-driven wireless communications, has successfully secured a significant grant from the National Telecommunications and Information Administration’s (NTIA) Public Wireless Innovation Fund. This grant will enable DeepSig to collaborate with industry leaders Jabil and Airspan, integrating its advanced AI-powered solution known as OmniSIG® into Open Radio Access Network (Open RAN) Radio Units (O-RUs). This integration aims to enhance efficiency, security, and performance in 5G networks and beyond.

Enhancing Telecommunication Capabilities

The incorporation of OmniSIG® into edge-based RAN infrastructure represents a major leap forward for telecommunications. The technology focuses on critical areas, such as dynamic spectrum sharing and interference detection. By leveraging cutting-edge AI capabilities, DeepSig's initiative will contribute to a more robust and responsive telecommunication environment.

Dynamic Spectrum Sharing

This technology showcases how 4G and 5G can effectively share spectrum alongside naval radars. The integration with new bands for aircraft and vehicles illustrates the demand for real-time spectrum sensing and optimization.

Interference Detection and Security

DeepSig's grant-funded project aims to swiftly identify and mitigate jamming, interference, and equipment malfunctions. In a rapidly evolving telecommunications landscape, the ability to proactively detect threats adds a layer of security to various networks.

Empowering Automated Network Operations

The development of automated network operations through optimized spectrum allocation paves the way for streamlined network deployment and maintenance. This approach not only reduces operational costs but also enhances overall network performance.

Transforming Spectrum Sensing

DeepSig is committed to transforming spectrum sensing into a practical, deployable solution by embedding state-of-the-art AI within scalable and cost-efficient O-RU devices. This advancement is set to extend the proven capabilities of OmniSIG®, which has already established a strong presence in defense and cybersecurity.

Future Prospects for Telecommunications

This collaborative effort aspires to revolutionize RAN infrastructure by employing open interfaces, ultimately making it fully spectrum-aware. This approach is vital for supporting a diverse range of sectors including public safety and industrial applications. The initiative signifies a substantial progression towards modernizing telecommunications infrastructure for sensing-aware 5G and 6G networks.

About DeepSig, Inc.

DeepSig is known for being at the forefront of AI-native wireless communications. The company’s groundbreaking technology enhances spectrum sensing, wireless performance, and network capabilities. With expertise in deep learning, wireless systems, and signal processing, DeepSig’s AI and machine learning solutions strengthen security and efficiency across both tactical and commercial wireless communications.

Frequently Asked Questions

What is the purpose of the NTIA grant awarded to DeepSig?

The grant will help DeepSig integrate its OmniSIG® technology into Open RAN Radio Units to enhance telecommunication capabilities.

Who are the partners collaborating with DeepSig on this technology?

DeepSig is partnering with Jabil and Airspan to further advance its AI-powered spectrum sensing solutions.

How does OmniSIG® contribute to telecommunications?

OmniSIG® enhances spectrum awareness, security, and performance, facilitating robust communication in 5G and future networks.

What are some key benefits of this initiative?

Benefits include improved dynamic spectrum sharing, rapid interference detection, and enhanced wireless security across networks.

How does DeepSig’s technology aim to improve network operations?

DeepSig’s technology streamlines network deployment and maintenance through automated operations, optimizing spectrum allocation and real-time tuning.

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