Wireless Device Power Saving Mode Selection Based on Traffic Monitoring
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Solution Overview
Problem
Current wireless communication systems face inefficiencies in power management, particularly in LTE technology, as the increasing demand for mobile broadband access necessitates improved power saving modes to reduce energy consumption without compromising performance.
Innovation Solution
A method and apparatus for selecting a power saving mode in wireless networks by monitoring data traffic, determining the presence of real data traffic during predefined periods, and deciding to enter either a first low power state (sleep mode) or a second low power state (idle mode) based on observed traffic, utilizing a processor and memory to execute this determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the wireless device continuously monitors data traffic to accurately determine power saving mode, then power saving efficiency is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary monitoring of data traffic during active periods to predict future traffic patterns. By analyzing traffic characteristics in advance and determining whether traffic is likely to continue, the device can proactively transition to appropriate power saving modes before actual idle periods begin, reducing the need for continuous monitoring while maintaining accurate power mode selection.
Solution Approach 2:
The wireless device autonomously analyzes its own traffic patterns and self-determines the appropriate power saving mode without requiring continuous network control signals. The device uses its own observed traffic data to make intelligent decisions about when to enter sleep mode or idle mode, reducing overall system complexity and energy consumption.
2Loss of energy
If the wireless device enters deep sleep mode to maximize battery life, then energy consumption is reduced, but data transmission responsiveness deteriorates
Solution Approach 1:
The system dynamically adjusts the power saving mode based on real-time traffic conditions and predictions. Rather than using a fixed deep sleep mode, the device flexibly transitions between different power states (active, sleep, idle) depending on whether traffic is detected or predicted. This dynamic adaptation allows the device to achieve deep power savings during truly idle periods while maintaining quick responsiveness when traffic arrives.
Solution Approach 2:
The system continuously monitors actual traffic patterns and uses this feedback to refine its power mode decisions. By observing whether traffic predictions were accurate and adjusting future decisions accordingly, the device learns to enter deep sleep modes only when appropriate, ensuring both energy efficiency and responsive data transmission when needed.
3Reliability
If the wireless device frequently checks for data traffic to avoid missing transmissions, then data transmission reliability is improved, but power saving effectiveness deteriorates
Solution Approach 1:
The device performs preliminary traffic analysis during active periods to predict whether data traffic will continue or stop. Based on these predictions, the device can confidently transition to power saving modes without needing frequent checks, knowing that traffic is unlikely to arrive. This preliminary assessment maintains reliability by avoiding premature transitions while reducing the need for frequent monitoring.
Solution Approach 2:
Instead of continuously monitoring traffic, the device performs partial monitoring at strategically determined intervals based on traffic patterns. When traffic is detected, monitoring is more frequent; when no traffic is detected and predictions indicate continued absence, monitoring frequency is reduced. This partial action approach maintains sufficient reliability while significantly reducing power consumption compared to continuous monitoring.
Data Source
AI summary
Certain aspects of the present disclosure present methods and apparatus for selecting a power saving mode for a mobile station (MS) in a wireless network. The power saving mode may be selected based on the traffic that is observed at the MS in a predefined duration. Once low overall data traffic is observed, the device may enter a first low power state. If data traffic of a particular type (e.g., not for management or maintenance purposes) is not observed for a predetermined duration, the device may enter a second low power state (deeper than the first low power state).