RL Microwave Antenna Alignment for Weather-Driven Path Loss
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Solution Overview
Problem
Microwave transmissions are vulnerable to environmental changes such as weather conditions and temporary objects, leading to misalignment and reduced signal quality, especially in dynamic conditions like rain or snow, which existing technologies struggle to address effectively.
Innovation Solution
A reinforcement learning (RL) model-based method for dynamically adjusting the alignment of microwave transmissions, using external state space parameters like weather conditions and internal state space parameters like antenna angles, to minimize path loss by adjusting the alignment of microwave transmitters and receivers, potentially involving unmanned aerial vehicles for data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If microwave transmissions are used for backbone carriers in telecom networks, then network connectivity and traffic capacity are improved, but vulnerability to weather conditions and environmental changes increases causing misalignment and signal loss
Solution Approach 1:
The patent implements dynamic alignment adjustment by continuously monitoring environmental conditions (temperature, humidity, precipitation) and automatically adjusting microwave antenna orientation in real-time. This transforms the static antenna positioning into a dynamic system that adapts to changing weather conditions, resolving the contradiction between maintaining high transmission capacity and ensuring reliability under varying environmental conditions
Solution Approach 2:
The system employs feedback mechanisms by monitoring transmission quality metrics and environmental parameters, then using this information to adjust antenna alignment. The feedback loop continuously optimizes the microwave link performance by detecting degradation caused by weather conditions and automatically compensating through alignment adjustments, thereby maintaining reliability while preserving network capacity
2Ease of manufacture
If manual alignment adjustment methods are used during installation, then initial setup is achieved, but the system cannot adapt to dynamically changing conditions such as weather changes or moving objects
Solution Approach 1:
The patent implements self-service by enabling the microwave system to automatically monitor its own performance and environmental conditions, then autonomously adjust its alignment without human intervention. The system serves itself by detecting misalignment caused by weather changes or moving objects and automatically compensating, thereby achieving both ease of operation and high adaptability to dynamic conditions
Solution Approach 2:
The patent replaces manual mechanical alignment adjustment with an automated electronic control system that uses sensors, processors, and actuators. This substitution transforms the purely mechanical manual adjustment process into an intelligent automated system that can rapidly respond to changing conditions, maintaining simplicity of operation while dramatically improving adaptability
3Productivity
If higher frequencies above 10 GHz are used for microwave transmissions, then data transmission capacity is improved, but vulnerability to precipitation and weather conditions increases causing refraction and misalignment
Solution Approach 1:
The patent applies preliminary anti-action by proactively detecting environmental conditions that may cause signal degradation and adjusting antenna alignment before significant misalignment occurs. The system monitors precipitation rates and atmospheric conditions, then preemptively adjusts the microwave beam orientation to compensate for expected refraction effects, thereby maintaining high-frequency transmission capacity while mitigating vulnerability to weather conditions
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for automatic and dynamic adaptation to changing environmental conditions, improving microwave transmission quality without manual intervention, reducing path loss and maintaining network performance even in adverse weather or interference scenarios.
Implementation Method 1
Precipitation causes microwaves to refract and hence the communication gets misaligned between the microwave transmitter and the microwave receiver
Data Source
AI summary
It is provided a method for adjusting alignment for microwave transmissions from a microwave transmitter to a microwave receiver based on a reinforcement learning, RL, model. The method comprises the steps of: obtaining state space comprising external state space and internal state space, the external state space comprising at least one value of a parameter related to environmental conditions, and the internal state space relates to alignment of the microwave transmitter; determining an action in an action space, the action space comprising actions to adjust alignment of the microwave transmitter; obtaining a measurement of path loss for a transmission from the microwave transmitter to the microwave receiver; determining a reward value based on the path loss, wherein an increase in path loss results in a reduced reward value; and adjusting the RL model based on the obtained state space, the determined action and the determined reward value.