Remote Access Point Placement Evaluation via Signal Angle Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The placement of wireless access points relative to wireless devices significantly impacts network performance, and existing methods for evaluating optimal placement are often unreliable and require on-site surveys, which are costly and inconvenient, especially for critical systems like hospitals or home security.
Innovation Solution
A remote evaluation method that determines the optimal placement of access points by analyzing the distribution of signal directions and angles of arrival, using machine learning and edge computing to recommend adjustments and potentially deploy range extending devices like signal repeaters or amplifiers based on collected data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If on-site surveys are conducted to evaluate optimal access point placement, then placement accuracy is improved, but cost and convenience deteriorate
Solution Approach 1:
The patent replaces the mechanical/on-site survey system with a remote evaluation system using angle of arrival measurements and machine learning algorithms. The system uses wireless signal data collected by the access point itself to determine optimal placement, eliminating the need for physical site visits while maintaining evaluation accuracy through computational methods.
Solution Approach 2:
The access point performs self-evaluation by collecting angle of arrival data from wireless devices and using machine learning algorithms to determine optimal placement. The system serves itself by utilizing its own collected data and computational resources to evaluate and recommend placement improvements without external intervention.
2Ease of manufacture
If remote evaluation methods are used to assess access point placement, then cost and convenience are improved, but measurement precision deteriorates
Solution Approach 1:
The patent introduces angle of arrival measurements as an intermediary parameter to bridge remote evaluation and accurate placement determination. By measuring the angles at which wireless device signals arrive at the access point and analyzing their distribution, the system can infer optimal placement without physical site visits, maintaining precision through this intermediate measurement approach.
Solution Approach 2:
The system changes the evaluation parameter from direct physical measurement (on-site survey) to angular distribution analysis of received signals. By analyzing the distribution of angle of arrival measurements and using machine learning models trained on angular data, the system achieves accurate placement evaluation through parameter transformation rather than direct measurement.
3Reliability
If access point placement is optimized, then wireless network performance is improved, but device complexity increases
Solution Approach 1:
The patent extracts the evaluation functionality from the access point hardware itself and separates it into a independent machine learning model. The access point collects angle of arrival data and transmits it to a separate evaluation system that performs the optimization analysis, allowing the access point to remain relatively simple while achieving sophisticated evaluation through external computational resources.
Data Source
AI summary
Systems, apparatuses, and methods are described for providing remote evaluation of a placement of an access point relative to one or more wireless devices in communication with the access point in a wireless network. The access point may determine directions, relative to the access point, of signals associated with wireless communications received by the access point from the one or more wireless devices. An indication of whether to move access point may be provided. An indication of whether to install range extending computing devices may be determined based on evaluating a variety of wireless conditions associated with the wireless network.