Adaptive Antenna Radiation Pattern Control for Wireless Networks
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Solution Overview
Problem
Existing wireless network infrastructure faces challenges in predicting and optimizing antenna coverage due to unpredictable radio wave propagation caused by environmental factors like buildings and foliage, leading to labor-intensive and costly site surveys and inefficient resource allocation.
Innovation Solution
The implementation of electronically configurable antennas and a system that uses mobile devices to continuously measure network performance, adjust radiation patterns, and store data for adaptive coverage, allowing for dynamic optimization of wireless network performance based on usage patterns and environmental changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If standard antennas with fixed radiation patterns are used, then manufacturing and deployment are simplified, but network performance cannot be optimized for specific geographic areas with unpredictable propagation conditions
Solution Approach 1:
The patent implements electronically configurable antennas that can dynamically change their radiation patterns through electronic control rather than physical reconfiguration. The base station includes multiple antenna elements that can be independently controlled to adapt the coverage area shape and direction based on real-time network performance data collected from mobile devices, allowing the system to transition from static to dynamic adaptation.
Solution Approach 2:
The system changes the radiation pattern parameters (beam direction, coverage shape, gain distribution) of the antennas based on analyzed network performance data. By adjusting electrical parameters such as phase and amplitude of signals fed to different antenna elements, the system optimizes coverage for specific geographic areas without requiring physical antenna replacement or repositioning.
2Reliability
If manual site surveys are conducted to optimize antenna coverage, then network performance can be improved, but the process becomes labor intensive and expensive
Solution Approach 1:
The system performs self-optimization by automatically collecting network performance measurements from mobile devices in the coverage area, analyzing this data to determine optimal radiation patterns, and reconfiguring the antennas accordingly. This eliminates the need for manual site surveys by engineering teams, as the system autonomously monitors and adjusts its own performance using data from ordinary mobile device traffic.
Solution Approach 2:
The system implements a continuous feedback loop where network performance measurements collected from mobile devices are fed back to the base station controller, which then adjusts the antenna radiation patterns to improve performance. This automated feedback mechanism replaces manual measurement and adjustment processes, enabling continuous optimization without repeated site surveys.
3Reliability
If repeated site surveys are performed to account for environmental changes, then coverage can be maintained, but infrastructure costs and labor requirements increase
Solution Approach 1:
The system performs continuous monitoring and optimization of network coverage by constantly collecting performance measurements from mobile devices and automatically adjusting antenna patterns in response to environmental changes. This continuous adaptive process replaces periodic manual site surveys, maintaining coverage consistency through ongoing automated adjustments rather than intermittent manual interventions.
Data Source
AI summary
A system and method is provided for performing an automated a site survey process for adjusting radiation patterns of access point antennas in a wireless network. The system and method utilize wireless mobile devices in their normal process of carrying about ordinary traffic to measure network performance. Further, such information is utilizes to configure the radiation patterns of the access point antennas to tailor coverage areas of the antennas to current network conditions.