Morphology Data Determination via Crowd-Sourced Signal Measurements
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Solution Overview
Problem
Current morphology data acquisition for small cell networks is costly and inefficient, with existing methods relying on expensive and static data sources like LiDAR imaging, which often become outdated, and lacks availability in all regions, necessitating a more effective and efficient method to generate current morphology data.
Innovation Solution
A method utilizing crowd-sourced data from user equipment to collect signal strength and geographic location measurements, which are then used to determine morphology parameters, with a system that optimizes these parameters based on statistical requirements to improve propagation modeling in small cell networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LiDAR imaging or satellite image processing is used to generate morphology data, then morphology data can be obtained, but the cost is expensive and the data becomes static and outdated over time
Solution Approach 1:
The patent transforms static morphology data into dynamic, continuously updating data by implementing a system that collects real-time measurements from mobile user equipment. The morphology database is continuously updated as users move through different locations, ensuring the data remains current without requiring periodic expensive satellite imaging campaigns.
Solution Approach 2:
The system utilizes the user equipment's own measurements and movements to automatically update morphology data. Users inadvertently contribute to data collection by using their devices for normal communication, and the system self-updates the morphology database without requiring external intervention or additional expensive imaging campaigns.
2Measurement precision
If LiDAR imaging or satellite image processing is used to generate morphology data, then morphology data can be obtained, but the acquisition cost is expensive
Solution Approach 1:
The patent replaces expensive, specialized LiDAR imaging equipment with ubiquitous, low-cost mobile user equipment (smartphones, tablets). These inexpensive devices continuously generate morphology data through their normal operation, eliminating the need for costly periodic satellite or aerial imaging campaigns.
Solution Approach 2:
The system repurposes user equipment primarily designed for communication to also serve as morphology data collection devices. The same devices users employ for calls and messaging automatically contribute to building and updating the morphology database, eliminating the need for specialized imaging equipment.
3Reliability
If morphology data is not readily available, then propagation modeling cannot be improved, but acquiring data through image processing is expensive and inefficient
Solution Approach 1:
The system implements continuous morphology data collection as user equipment moves through the environment. Rather than periodic snapshots, the database is continuously updated with new measurements, ensuring propagation models always have current morphology data to improve their accuracy without interruption or downtime.
Solution Approach 2:
The system incorporates feedback loops where measured path loss values are compared against predicted values, and morphology parameters are optimized based on statistical analysis of differences. This continuous feedback process automatically improves propagation modeling accuracy by refining the morphology database based on actual measurement performance.
Data Source
AI summary
Techniques for more effectively and efficiently obtaining current morphology data are described. Measurement data is transmitted by user equipment to a central location such as a communication network or another entity such as in remote servers, e.g. the cloud. The recipient of such data, or a third party that receives such data from the recipient, utilizes the data, e.g. signal strength measurements and related data, to determine morphology data for corresponding geographic locations, e.g. altitude, longitude, and latitude.