Global demand for ubiquitous high-speed connectivity is driving massive investments in 5G, private networks, and IoT infrastructure. However, the complexity of urban environments and the sheer scale of deployments make traditional network planning inefficient and costly. This technology directly addresses the need for faster, more accurate, and cost-effective network design tools, enabling operators and integrators to meet aggressive deployment targets and deliver superior service quality in a competitive market.
Optimize Network Design with High-Precision Prediction: Integrates structural map data and distance attenuation using machine learning, enabling extrapolation of local radio wave propagation characteristics with approximately 20% higher accuracy than conventional methods.
Reduce On-Site Survey Costs by ~65%: Significantly reduces physical radio wave measurements, curbing annual field survey personnel and equipment transport costs by millions of dollars and maximizing ROI.
Secure Exclusive Market Advantage: Registered after comparison with four prior art documents, demonstrating clear technical superiority in radio wave propagation estimation and ensuring long-term market competitiveness.
This patent protects a radio wave propagation estimation system, method, and a method for manufacturing its generation unit, covering multiple facets of the technology across six claims. It was granted after a rigorous examination process that distinguished it from four prior art documents, confirming its novelty and inventiveness and providing a stable, defensible intellectual property foundation.
This patent focuses on estimation using structural and empirical data. White space exists in real-time dynamic network optimization based on live traffic data, or specific hardware implementations for active, drone-based measurement and data collection.
For telecom operators deploying 500 new 5G base stations annually, assuming conventional survey and simulation costs of $2,000/location (AI est.). This technology could reduce these costs by 50%, leading to a direct saving of 500 locations × $2,000/location × 50% = $500K/year (AI est.). Additionally, assuming an equivalent reduction in wasted infrastructure investment due to higher accuracy, the total economic impact could reach ~$1.0M/year (AI est.).
X: Prediction Efficiency
Y: Deployment Flexibility