Protocol Stack Power Optimization for Wireless Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
User Equipment (UE) devices face a challenge in optimizing power consumption while maintaining a good user experience, as they have limited battery life and increasing power demands due to advanced communication and computation capabilities, leading to thermal issues and reduced battery life.
Innovation Solution
A protocol stack power optimization algorithm that collects measurements across various layers of the protocol stack to selectively control power usage by switching off unnecessary hardware, reducing peak power amplifier levels, and adjusting processor voltage and frequency, thereby optimizing energy resources for improved battery life and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If UE devices use advanced communication and computation capabilities to improve user experience, then performance and data rate are improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts power consumption parameters (processor voltage, frequency, RF power amplifier levels) based on real-time measurements of data rate, block error rate, and buffer status. This allows the UE to optimize the trade-off between productivity and energy usage by adapting to changing communication conditions rather than operating at fixed high-performance settings.
Solution Approach 2:
The invention changes operational parameters (processor voltage, clock frequency, RF power levels) to achieve optimal performance. By adjusting these parameters based on measured communication quality and data rate requirements, the system can maintain acceptable user experience while reducing power consumption during periods of lower demand.
2Productivity
If UE devices increase processing power and communication capabilities, then user experience is improved, but battery life is reduced
Solution Approach 1:
The system implements a feedback mechanism that continuously measures communication performance metrics (data rate, block error rate, buffer status) and uses this information to adjust power consumption parameters. This closed-loop control ensures that battery life is extended by reducing power usage when high performance is not needed, while maintaining acceptable user experience through dynamic adaptation.
Solution Approach 2:
The invention applies partial action by using only the necessary processing power and communication capabilities required for acceptable user experience rather than always operating at maximum capacity. This allows the system to extend battery life by avoiding excessive power consumption while still delivering satisfactory performance.
3Productivity
If UE devices operate at high power levels to maintain performance, then data rate is maintained, but thermal issues increase
Solution Approach 1:
The system uses periodic measurements of communication performance and adjusts power levels accordingly, rather than maintaining continuously high power output. This periodic adjustment allows the UE to reduce thermal generation during periods when high data rates are not required, while still maintaining acceptable performance through timely power adjustments.
Data Source
AI summary
User experiences on wireless devices are affected by communication, computation, and user interface capabilities. Another key performance indicator of a wireless device is its battery life. A method, algorithm and apparatus for improving the communication, computation and user interface capabilities of a mobile device is disclosed, which requires the expenditure of less energy and increases battery life. The trade-off between battery life and user experience related to the communication capability is managed by a protocol stack power optimization algorithm that optimally allocates energy resources. The power management algorithm inputs and combines measurements made at various layers of the protocol stack to selectively control a set of actions impacting energy usage. The algorithm maps from a set of measurements to a set of actions that provides the best trade-off between user experience and energy consumption.