Wireless Power Save Control Using RL-Based Inactivity Timeouts
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Solution Overview
Problem
Wireless devices consume excessive power and negatively impact performance by remaining in active mode longer than necessary due to the use of inactivity timeouts (ITO) that are not adjusted based on traffic type, leading to inefficient power management.
Innovation Solution
Implement adaptive power save techniques using reinforcement learning to adjust ITOs based on traffic indicator metrics and perform speculative wakeups, updating ITO look-up tables (LUTs) with closed-loop feedback to optimize power mode transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a fixed inactivity timeout (ITO) is used regardless of traffic type, then the STA can maintain simple power management, but the STA consumes excessive power by remaining in active mode longer than necessary
Solution Approach 1:
The patent implements dynamic adjustment of inactivity timeout (ITO) values based on traffic characteristics. The system transitions from a fixed ITO to a variable ITO that adapts to different traffic types (e.g., voice, video, data), allowing the STA to optimize power consumption by selecting appropriate timeout values rather than using a single fixed value for all traffic scenarios.
Solution Approach 2:
The system changes the ITO parameter based on traffic type detection. When different traffic types are identified, the corresponding ITO value is adjusted to match the traffic pattern requirements, enabling the STA to exit active mode at optimal times for each traffic type and reduce unnecessary power consumption.
2Reliability
If the STA waits for ITO to expire before entering sleep mode, then the STA ensures it is ready for the next packet, but this delays power saving and reduces battery life
Solution Approach 1:
The system performs preliminary detection of traffic type and characteristics before the ITO period expires. By identifying the traffic pattern in advance, the STA can determine whether entering sleep mode early would miss important packets, allowing it to make informed decisions about when to transition to power-saving mode while maintaining reliable packet reception.
Solution Approach 2:
The system uses feedback from traffic monitoring to adjust power mode transitions. By continuously monitoring traffic patterns and using this feedback to determine optimal sleep entry timing, the system balances reliable packet reception with power conservation, avoiding both premature sleep transitions and unnecessary active mode extensions.
3Productivity
If the STA remains in active mode to handle periodically-scheduled packets, then the STA ensures continuous communication availability, but this unnecessarily consumes power during periods when packets are not sent
Solution Approach 1:
The system leverages the periodic nature of certain traffic types (e.g., voice calls with regular packet intervals) to optimize power management. By detecting the periodic pattern, the STA can enter sleep mode during intervals when no packets are expected and wake up precisely when packets are scheduled to arrive, maintaining communication availability while minimizing power consumption during idle periods.
Data Source
AI summary
Methods, systems, and devices for wireless communication are described. A station may be communicating with an access point during a first active communication period. The communication may be performed in a first power mode. The station may switch to a second power mode to transition to a sleep period. The station may determine, based on traffic indicator metric(s), whether to perform a speculative wakeup and switch to the first power mode at the end of the sleep period.