Automated Wireless Access Point Configuration via Spatial Data
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Solution Overview
Problem
Conventional wireless communication networks require manual configuration and reconfiguration of access points, which is inefficient and time-consuming, especially when changes in communication parameters occur, such as frequency swaps or changes in access point capacity.
Innovation Solution
The implementation of an automated system that uses location-specific settings to automatically configure wireless access points, utilizing an external data store to select appropriate parameters and an access point provisioning gateway to remotely initiate configuration changes based on spatial data and other factors like time zones or utilization rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual configuration and reconfiguration of access points is used, then configuration accuracy can be ensured, but time consumption and operational efficiency deteriorate
Solution Approach 1:
The access point automatically configures itself by receiving spatial data, determining its geographical location, and selecting appropriate communication parameters without human intervention. The system performs self-provisioning through automated firmware installation and parameter configuration based on its detected location.
Solution Approach 2:
Configuration parameters and firmware are pre-prepared and stored in association with different geographical locations. When an access point is deployed, the system retrieves the pre-configured parameters appropriate for that location, eliminating the need for manual configuration during deployment.
2Productivity
If automated configuration is implemented, then operational efficiency and responsiveness improve, but system complexity increases
Solution Approach 1:
A centralized server acts as an intermediary between access points and the configuration management system. The server receives spatial data from access points, determines appropriate parameters based on geographical location, and automatically provisions the access points, thereby managing complexity centrally rather than at each device.
Solution Approach 2:
The system continuously monitors access point performance and utilization metrics, using this feedback to dynamically adjust and reconfigure parameters. The system receives feedback from access points about their operational status and automatically responds by optimizing configurations based on current conditions.
3Adaptability or versatility
If location-specific automated configuration is used, then adaptability to different geographical conditions improves, but the complexity of parameter selection and management increases
Solution Approach 1:
The system implements location-specific configuration by associating different communication parameters with different geographical locations. Each access point receives parameters tailored to its specific geographical context, such as frequency assignments and capacity settings appropriate for that region's conditions and regulations.
Data Source
AI summary
Automated wireless access point resource allocation and optimization are facilitated. An external data store (EDS) component can automatically select, based on spatial data of at least one polygon including at least one wireless access point, one or more parameters associated with wireless communications of the at least one wireless access point. Further, an access point provisioning gateway (APPG) can remotely initiate the at least one wireless access point to automatically configure equipment of the at least one wireless access point to service the wireless communications using at least one of the one or more parameters. Furthermore, a boundary generation component can automatically generate the spatial data by at least one of: combining spatial data of two or more polygons; splitting a polygon into at least two polygons; or expanding a boundary of the polygon.