Opportunistic Wireless Scheduling Using Motion-Based Fading Prediction
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Solution Overview
Problem
Current communication scheduling in wireless networks does not adequately incorporate motion information of mobile devices, leading to inefficiencies due to variable channel conditions caused by device movement and environmental factors.
Innovation Solution
A method and apparatus that utilize signals from motion sensors and location identification modules to predict fading events, allowing for scheduling of wireless communications to avoid time slots with predicted fading, thereby improving resource allocation and communication quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If opportunistic scheduling is used to improve spectrum utilization by monitoring channel qualities, then spectrum utilization is improved, but the system cannot adequately predict fading events caused by device motion, leading to communication quality degradation
Solution Approach 1:
The system performs preliminary action by obtaining motion information from sensors (accelerometers, GPS, etc.) and using it to predict fading events before they occur. This allows the scheduler to proactively avoid scheduling communications during predicted fading periods, rather than reactively responding to channel quality degradation after fading begins. The motion-based prediction enables advance preparation of scheduling decisions.
Solution Approach 2:
The system implements feedback by continuously monitoring motion sensor data from mobile devices and using this information to adjust scheduling decisions. The base station receives motion information from devices and feeds this back into the scheduling algorithm, creating a closed-loop system where scheduling is dynamically adapted based on real-time motion status and predicted fading conditions.
2Productivity
If channel quality monitoring is performed to enable opportunistic scheduling, then communication efficiency is improved, but the delay between obtaining channel quality estimates and making scheduling decisions reduces the effectiveness of fading avoidance
Solution Approach 1:
Motion information is obtained in advance and used to predict future fading events before channel quality degradation occurs. This preliminary prediction based on motion trends allows the system to make scheduling decisions proactively, eliminating the need to wait for channel quality estimates to show degradation. The prediction horizon extends the effective response time beyond what traditional channel monitoring can provide.
3Measurement precision
If motion sensors and location modules are integrated into mobile devices to provide motion information, then fading prediction accuracy is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent leverages motion sensors (accelerometers, gyroscopes) and location modules (GPS) that are already integrated into mobile devices for other purposes such as navigation, fitness tracking, and gesture control. By repurposing these existing multi-functional components for fading prediction, the system achieves improved measurement precision without significantly increasing device complexity, as the hardware is already present for other functions.
4Manufacturing precision
If motion information is obtained and processed to predict fading events, then scheduling accuracy is improved, but the complexity of the scheduling system increases
Solution Approach 1:
Motion information is obtained and processed in advance to predict fading events before scheduling decisions are made. This preliminary processing creates a prediction layer that operates independently from the real-time channel quality monitoring, allowing the scheduler to use pre-computed fading predictions rather than complex real-time analysis of multiple parameters during the scheduling decision moment.
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AI summary
A method, wireless communication device, and computer program product are provided for scheduling wireless communication between a base station and one or more mobile wireless communication devices. Signals indicative of motion are obtained and utilized to facilitate scheduling operations. In some embodiments, signals indicative of motion are used in estimation or prediction of variable conditions of the common radio medium, and scheduling, such as opportunistic scheduling, is performed based at least in part on the estimates or predictions. Signals indicative of motion may be obtained from GPS data, accelerometer data or other data generated at a mobile wireless communication device.