“Thank you for your support and service throughout my petition process. I truly appreciate the effort your team put into securing the approval.”

Case Summary:      

North America Immigration Law Group (NAILG) presented a proposed endeavor to analyze, allocate, and share limited radio spectrum more efficiently so that critical services and consumer networks can operate with fewer conflicts. The record links this work to U.S. priorities in 5G and future 6G, spectrum security, public-safety communications, and AI-enabled spectrum tools.

Research Focus and Contributions

• Interference analysis and mitigation: Built software-defined radio testbeds to characterize LTE–telemetry interactions and produced data-driven rules that prevent conflicts between adjacent bands used by commercial and mission-critical systems.
• Shared-spectrum strategies: Advanced LTE-U and Wi-Fi coexistence using deep-learning classification of RF signals on an SDR platform to coordinate channel access and reduce collisions.
• Guidelines and tools: Developed spectrum-usage ontologies and acceptance-test plans that translate lab findings into operational practices for cleaner, more reliable networks.

Research Impact and Metrics

• Peer-Reviewed Publications: 1 journal article and 4 peer-reviewed conference papers, plus 1 technical report.
• Citations: 11 independent citations, including uptake in aeronautical telemetry studies.
• Recognition & Support: supported spectrum work referenced in the record, evidencing national relevance and real-world utility. His research has been supported with funding from the S. Department of Defense (DOD). This funding is reserved solely for research directed at advancing the national interest, including studies that “ensure our nation’s security”.

Here is an anonymized excerpt from a recommendation letter that underscores the practical impact of his work:

“[Client] tackles a core challenge in wireless communications: precise radio-signal classification to enable efficient spectrum allocation and reduce interference. In a notable study on LTE-U and Wi-Fi coexistence in the crowded 6 GHz subcarrier bands, [client] built a software-defined-radio testbed and applied deep-learning (convolutional-neural-network) techniques with transfer learning, accounting for varying SNR and noise uncertainty during real-world testing. This work produced an effective system to differentiate LTE-U and Wi-Fi signals, supporting harmonious operation and better utilization of limited spectrum resources. The outcomes, reflected in publications and independent citations, benefit service providers and end users by making wireless networks more efficient and reliable.”

Demonstrating Substantial Merit and National Importance

We showed substantial merit by tying the research to reduced interference, higher network reliability, and safer operations across telemetry, LTE/5G, and Wi-Fi. National importance was established through independent adoption of the client’s findings, alignment with federally recognized critical and emerging technologies, and references in the record to defense-related support for spectrum work.

Well Positioned to Advance the Proposed Endeavor

With a Ph.D. in a directly related STEM field, hands-on SDR engineering experience, and a continuing U.S. research role, the client is well-positioned to expand AI-assisted spectrum sensing, coexistence protocols, and compliance tools that benefit public-safety and commercial networks. Expert letters in the record attest to recognized expertise and practical impact.

NIW Approval and Outlook

Approved in 1 year, 5 months, and 5 days, this NIW recognizes a research agenda that strengthens U.S. connectivity by improving spectrum sharing and interference mitigation. NAILG is proud to have guided this case and looks forward to the client’s continued contributions to safer, faster, and more reliable American wireless networks.