SCOPE
Welcome to ANSpect 5G PHY-Layer Capacity Testing & Validation
What is this project?
This project is a collaboration between ANSpect Technologies Inc. and Virginia Tech aimed at experimentally validating ANSpect's patented PHY-layer capacity-boosting technology using Virginia Tech's 5G testbed infrastructure at its Arlington and Blacksburg campuses. ANSpect's approach piggybacks additional bits from high-quality channels during low-MCS transmissions to increase aggregate cell throughput without additional spectrum. The project deploys this technology on srsRAN with Open5GS across indoor and outdoor environments to generate rigorous empirical evidence supporting a pathway toward commercial deployment.
Project Objectives
The primary mission is to produce validated throughput measurements demonstrating ANSpect's capacity gains across multiple user pairing and channel quality scenarios. Key objectives include:
- Indoor Validation: Deploy ANSpect's modified srsRAN stack at VT Arlington's Indoor 5G Lab to establish baseline performance and measure gains across four test cases.
- Outdoor Replication: Extend all four test cases to VT Blacksburg's Outdoor Test Field to assess performance under real-world propagation, mobility, and interference conditions.
- Multi-User Characterization: Test PHY enhancements across user pairings ranging from weak/strong single-user pairs to four-UE environments, spanning QPSK through 256QAM.
- Milestone Deliverables: Produce six formal deliverables across 16 weeks, including setup reports, throughput analyses, and a final comparative report.
Project Impact
This project bridges PHY-layer innovation and commercial 5G deployment by providing independently conducted, real-world validation data. Successful results across both phases will demonstrate meaningful throughput improvements in realistic 5G NR deployments, strengthening ANSpect's case for broader commercial adoption.
Project Team
- Aloizio Da Silva
- Director of CCI XG Testbed
- Asheesh Tripathi
- Research interests include O-RAN-based NextG wireless networks, software-defined radio-based citizens broadband radio service networks, and machine learning.
- Fahim Bashar
- Focuses on NextG Testbed deployment and development