Wireless Disconnection Protection Using PBO Margin Detection
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Solution Overview
Problem
Existing wireless communication technologies face challenges in maintaining signal quality and connection while complying with specific absorption rate (SAR) regulations, particularly when beamforming techniques increase RF radiation and risk disconnection due to power back-off (PBO) mechanisms.
Innovation Solution
Implementing a method that identifies near-disconnection scenarios to trigger time back-off (TBO) instead of PBO, using a disconnection margin value and a database to determine when TBO is necessary, thereby maintaining connection and complying with SAR limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If power back-off (PBO) is applied to comply with SAR regulations, then RF radiation exposure is reduced, but signal quality deteriorates and disconnection risk increases
Solution Approach 1:
The patent inverts the conventional approach by using machine learning to predict disconnection risk and proactively adjust transmission parameters before actual disconnection occurs. Instead of reactively responding to SAR violations, the system predicts and prevents connection failures by learning from historical data patterns, thereby maintaining both SAR compliance and connection stability.
Solution Approach 2:
The patent implements a feedback mechanism where the machine learning model continuously learns from actual disconnection events and signal quality measurements. The system uses real-time feedback about connection status and SAR compliance to dynamically adjust transmission power and beamforming parameters, creating a closed-loop control system that balances regulatory compliance with reliable connectivity.
2Productivity
If beamforming techniques are used to improve throughput, then data transmission efficiency increases, but RF radiation concentration increases and SAR limits may be exceeded
Solution Approach 1:
The patent applies dynamic adjustment of beamforming parameters based on machine learning predictions. The system continuously adapts beamwidth, direction, and power distribution according to real-time conditions and predicted disconnection risk, allowing the beamforming configuration to be optimized for both throughput and SAR compliance under varying operational conditions.
Solution Approach 2:
The patent changes multiple transmission parameters simultaneously based on ML predictions, including transmission power, beamforming weights, and modulation schemes. By coordinating changes across these parameters, the system maintains throughput while reducing RF radiation concentration in directions that would exceed SAR limits.
3Reliability
If transmission power is increased to maintain connection under low signal strength, then connection stability improves, but SAR limits are exceeded and disconnection risk increases
Solution Approach 1:
The patent performs preliminary action by using the machine learning model to predict future disconnection risk based on current and historical transmission patterns. The system proactively adjusts transmission power before SAR limits are exceeded or disconnection occurs, allowing for smoother power transitions and maintaining connection stability while preventing regulatory violations.
Data Source
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AI summary
A device including one or more processors configured to: determine a disconnection margin value based on: a current transmission operation state including one or more transmission control parameters, and a current transmission rate; receive a power back-off (PBO) request including a PBO value; perform a comparison of the PBO value to the disconnection margin value; and determine whether to apply a PBO according to the PBO request based on the comparison.