Base Station Scheduling for Mobile Battery Conservation
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Solution Overview
Problem
The battery life of portable computing devices is a significant challenge due to increased computing power demands, with existing solutions like adding larger batteries being inefficient and costly, and previous attempts to reduce processor cycles having limited success.
Innovation Solution
The system analyzes communication types and patterns to limit communications to times and situations where battery preservation will have a significant impact, using a central server to control the timing of voice, data, and control signals, employing machine learning to determine optimal communication times based on user behavior and patterns, and utilizing the cellular carrier's network to extend battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If larger batteries are added to extend battery life, then battery life is improved, but weight and cost increase
Solution Approach 1:
The base station performs preliminary analysis of communication patterns and user behavior to predict when communications are likely to occur. By proactively determining optimal communication times before actual communications happen, the system can schedule communications during periods when the device is less likely to be used, thereby extending battery life without requiring larger batteries.
Solution Approach 2:
The system uses the device's own communication patterns and usage behavior to automatically determine when communications should be limited. The base station monitors and analyzes the device's self-generated data about its usage patterns, eliminating the need for manual user configuration or external intervention to optimize battery life.
2Reliability
If communication frequency is increased to maintain network connectivity, then network connectivity is improved, but battery power consumption increases
Solution Approach 1:
Instead of continuous or frequent communications, the system implements periodic communications scheduled at optimized intervals. The base station determines specific time periods when communications should occur based on analyzed patterns, allowing the device to enter low-power states between scheduled communications while maintaining adequate network connectivity.
Solution Approach 2:
The system applies partial action by selectively limiting communications only during periods when they are least likely to impact user experience, rather than reducing all communications uniformly. Communications are maintained at full frequency during high-need periods while being reduced during low-need periods, achieving energy savings without compromising reliability where it matters.
3Duration of action of moving object
If processor cycles are reduced to conserve battery power, then battery life is improved, but communication effectiveness deteriorates
Solution Approach 1:
The base station performs preliminary analysis of communication patterns, user behavior, and network conditions before actual communications occur. This advance analysis allows the system to pre-determine optimal communication schedules and strategies, ensuring that when communications do occur, they are highly effective and require minimal processor cycles for decision-making during the actual communication events.
Solution Approach 2:
The base station acts as an intermediary that handles the complex analysis and decision-making processes, freeing the mobile device's processor from performing these computationally intensive tasks. The base station analyzes patterns and generates communication schedules, then transmits these schedules to the device, which simply follows the predetermined schedule with minimal local processing required.
Data Source
AI summary
The handset and base station disclosed save battery life and processor cycles by further analyzing communication types and patterns to limit communications to times and situations where communications are more likely and where battery preservation will have a significant impact. In one embodiment, the server side controls the timing of communicating voice signals, data signals and control signals to save battery life in a portable computing device.