CBRS CPE Installation via Predictive Link Assessment
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Solution Overview
Problem
The installation of outdoor CBRS CPEs faces challenges due to stringent performance requirements, complex antenna configurations, and the need for precise signal assessment, especially in rural areas where updated digital maps and 3D foliage profiles are lacking, leading to difficulties in data throughput reliability.
Innovation Solution
A system comprising a database server, a mobile communications device with a CBRS CPE Installation Application, and a sensor unit with position/orientation sensors, enabling fast and reliable installation by establishing communication links for network configuration, performance estimation using machine learning algorithms, and precise antenna pointing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional RF planning and digital maps are used for site survey, then installation can proceed with basic information, but the accuracy of serviceability assessment is insufficient due to lack of updated 3D foliage profiles and seasonal variations
Solution Approach 1:
The system performs preliminary mathematical modeling and prediction of signal propagation conditions before physical installation. By using advanced channel models that incorporate 3D foliage profiles, terrain data, and seasonal variations, the system assesses serviceability in advance with high accuracy, avoiding the need for complex post-installation adjustments and reducing on-site trial-and-error time.
Solution Approach 2:
The patent introduces an intermediary computational layer between the physical environment and the installation decision-making process. This layer uses sophisticated mathematical models to translate raw environmental data (terrain, foliage, weather patterns) into predictive performance metrics, enabling accurate serviceability assessment without requiring direct physical measurement of all environmental factors during installation.
2Reliability
If CPE attempts to connect multiple times to assess performance, then connectivity reliability can be evaluated, but the total installation time exceeds the FCC limit of 90 minutes
Solution Approach 1:
The system performs preliminary connectivity assessments using mathematical models that predict link reliability based on environmental factors, equipment characteristics, and propagation conditions. This preliminary evaluation identifies the most promising connection targets before actual connection attempts, reducing the number of trial connections needed and ensuring that installation completes within the 90-minute FCC limit while still achieving reliable connectivity assessment.
Solution Approach 2:
The system implements a feedback mechanism where each connection attempt provides data that refines the mathematical models. The models learn from successful and unsuccessful connection attempts, adjusting predictions of connectivity reliability. This feedback loop enables the system to minimize the number of connection attempts needed while maintaining high accuracy in reliability assessment, thereby reducing installation time.
3Manufacturing precision
If basic KPI evaluation is used for signal assessment, then the process is simple and fast, but it is insufficient to indicate best performance for complex multiple antennas with different characteristics
Solution Approach 1:
The system applies local quality by tailoring the evaluation process to each antenna's specific characteristics. Instead of using a single generic KPI threshold for all antennas, the mathematical models incorporate antenna-specific parameters such as beamforming capabilities, directional patterns, and frequency responses. This enables precise performance optimization for each antenna element while maintaining a systematic evaluation framework that manages complexity through modular modeling approaches.
Data Source
AI summary
A system, apparatus and method for installation of outdoor CPE (Customer Premise Equipment) for CBRS (Citizen Broadband Radio Service) for fixed wireless access is disclosed. The system comprises a database server which stores data comprising eNodeB locations and details, pathloss models and throughput prediction data. A position/orientation sensor and WiFi access point are attached to the CPE during installation. For a specified CPE height and a range of pointing angles, a smartphone app is used in scan mode to obtain KPI and evaluate nearby eNodeBs for performance based on stored parameters and link type, to provide estimated UL/DL throughput data for each eNodeB. After selecting an eNodeB, in network entry mode, a RF link between the CPE and eNodeB is established to request SAS grant. If successful in entering operational mode, actual throughput is measured to ensure the desired performance is attained, and data are reported back to the database.