Dynamic Power Adjustment of Network Towers Using Vehicle Sensors
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Solution Overview
Problem
Wireless carrier network components face communication disruptions due to inclement weather, which affects signal strength and reliability, especially when traditional methods like RSSI measurements are inaccurate due to signal reflections and degradations.
Innovation Solution
Implementing a C-V2X application that utilizes vehicle-mounted weather sensors to collect data on moisture, temperature, humidity, and other conditions, which is then used by a central network to dynamically adjust network tower settings, such as transmission power, through machine learning models to improve network performance and reliability during adverse weather.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional RSSI measurements are used for power adjustment, then the system is simple to implement, but the measurement precision deteriorates due to signal reflections and degradations from inclement weather
Solution Approach 1:
The patent introduces vehicle-mounted weather sensors as intermediary devices to measure actual weather conditions (moisture, temperature, humidity) that affect wireless signals. These sensors act as mediators between the environment and the network tower, providing direct weather data without relying on indirect RSSI measurements that are corrupted by signal reflections and degradations.
Solution Approach 2:
The patent replaces the traditional electromagnetic signal-based measurement system (RSSI) with a mechanical/sensor-based measurement system (vehicle-mounted environmental sensors). This substitution eliminates the problem of signal reflections and degradations by using physical sensors that directly measure weather conditions rather than inferring them from corrupted wireless signals.
2Reliability
If dynamic power adjustment based on accurate weather data is implemented, then communication reliability improves during inclement weather, but energy consumption increases
Solution Approach 1:
The patent implements dynamic power adjustment where the network tower's transmission power is continuously adapted based on real-time weather conditions detected by vehicle sensors. The system transitions from static power levels to dynamic adjustment, increasing power only when weather conditions deteriorate and decreasing it when conditions improve, thereby maintaining reliability while optimizing energy consumption.
Solution Approach 2:
The patent changes the operational parameter (transmission power) of the network tower based on measured weather parameters (moisture, temperature, humidity). By adjusting the power parameter in response to weather parameter changes, the system maintains communication reliability during inclement weather while avoiding unnecessary energy consumption during favorable conditions.
3Adaptability or versatility
If vehicle sensor data is collected and processed through machine learning models, then the adaptability to weather conditions improves, but the device complexity increases
Solution Approach 1:
The patent employs machine learning models that are pre-trained on historical weather and signal data to predict the impact of weather conditions on network performance. This preliminary action allows the system to quickly adapt to new weather conditions without requiring complex real-time analysis, as the ML models have already learned the relationships between weather parameters and signal degradation patterns.
Solution Approach 2:
The patent uses vehicle-mounted sensors to create a distributed network of weather measurement points across the service area. Each vehicle acts as a mobile measurement node, copying the functionality of fixed weather stations. This approach improves weather data coverage and adaptability without requiring a complex fixed infrastructure, as the system leverages existing mobile vehicles as sensing platforms.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for dynamically adjusting the power of network towers are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, data that reflects characteristics of a vehicle. The actions further include, based on the data that reflects the characteristics of the vehicle, determining, by the computing device, whether to adjust a setting of a base station of a wireless network. The actions further include, based on determining whether to adjust the setting of the base station of the wireless network, determining, by the computing device, whether to provide, for output to the base station of the wireless network, an instruction to adjust the setting of the base station.