SAR Averaging Algorithm for Wireless Power Management
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Solution Overview
Problem
Conventional methods for human exposure compliance in wireless communication devices, such as arithmetic mean averaging for SAR calculations, require significant memory and are prone to overshoot issues, leading to unnecessary power reductions and inefficiencies.
Innovation Solution
Implementing a central tendency calculation, such as a weighted or harmonic mean, for power management within a sliding window, reducing memory requirements and eliminating overshoot by dynamically adjusting power levels based on recent transmission powers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If arithmetic mean averaging is used for SAR calculations, then compliance measurement is achieved, but memory requirements increase significantly and overshoot occurs
Solution Approach 1:
The patent segments the averaging process into manageable components by using a sliding window approach that divides the measurement period into discrete time slots. Instead of storing all samples in memory, the system processes them in segments, calculating the arithmetic mean over a defined window period while discarding older samples. This segmentation allows compliance measurement without requiring large memory capacity.
Solution Approach 2:
The patent extracts only the essential elements needed for SAR calculation from the complete set of power samples. By using the formula SAR_avg = (1/N) * Σ(P_i * T_i) where N is the number of samples in the averaging window, the system extracts the necessary power and time data points without storing the entire history of transmissions. This extraction approach maintains measurement precision while minimizing memory usage.
2Measurement precision
If arithmetic mean averaging is used for SAR calculations, then compliance measurement is achieved, but overshoot occurs during first cycle
Solution Approach 1:
The patent applies preliminary action by initializing the SAR average calculation with appropriate starting values and applying the averaging formula from the beginning of operation. The system uses SAR_avg = (1/N) * Σ(P_i * T_i) with proper initialization of the summation term, ensuring that the first cycle calculation is accurate and does not produce overshoot. This preliminary setup of the calculation framework ensures reliable compliance measurement from the start.
Solution Approach 2:
The patent implements feedback by continuously monitoring the calculated SAR average and comparing it against compliance thresholds. The system adjusts power transmission based on the feedback from SAR_avg calculations, ensuring that the average power remains within regulatory limits. This closed-loop feedback mechanism prevents overshoot by dynamically adjusting transmission power based on real-time SAR measurements.
3Object-affected harmful factors
If static power reduction is used based on proximity sensors, then human exposure compliance is achieved, but data throughput performance decreases
Solution Approach 1:
The patent applies dynamics by transitioning from static power reduction to dynamic power adjustment based on real-time SAR measurements. Instead of using fixed proximity sensor thresholds that continuously reduce power, the system dynamically adjusts transmission power based on the calculated SAR_avg value. This dynamic approach allows the system to maintain maximum power when SAR compliance is satisfied, thereby preserving data throughput while still ensuring human exposure compliance.
Solution Approach 2:
The patent changes the control parameter from proximity-based static power levels to SAR-average-based dynamic power levels. By using SAR_avg = (1/N) * Σ(P_i * T_i) as the control metric, the system adjusts transmission parameters based on actual electromagnetic exposure measurements rather than assumed proximity conditions. This parameter change enables more efficient power management that maintains compliance without unnecessary throughput reduction.
Data Source
AI summary
A wireless communication device includes one or more processors, configured to determine one or more first transmission power measurements within a first transmission power measurement sampling period; calculate a first transmission power factor, the first transmission power factor representing a central tendency of the one or more first transmission power measurements from the first power measurement sampling period; determine a second power measurement during a second transmission power measurement sampling period; and calculate a second transmission power factor, wherein the second transmission power factor is a central tendency of at least one of the one or more first power measurements and the second power measurement.