User Device Mobility State Determination Using Sensor Data
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Solution Overview
Problem
Existing wireless communication systems face inaccuracies and delays in determining the mobility state of user devices due to reliance on reselection counts rather than actual movement, leading to inefficient handover and reselection processes, especially in areas with overlapping base station coverage.
Innovation Solution
User devices employ sensors like GPS, accelerometers, and compasses to determine their actual movement, transitioning between mobility states based on speed and direction, rather than solely on reselection counts, thereby adjusting measurement parameters and timing for more accurate and timely handovers and reselections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mobility state is determined based on reselection counts, then handover control can be implemented, but accuracy and timeliness of mobility state determination deteriorates
Solution Approach 1:
The system performs preliminary actions by determining mobility state based on actual movement data (GPS, accelerometer) before handover decisions are made. This allows the system to proactively identify high-mobility users and prepare appropriate measurement parameters and handover thresholds, avoiding delays associated with reactive reselection-count-based detection.
Solution Approach 2:
The patent introduces movement data from sensor devices (GPS, accelerometer, compass) as an intermediary to bridge the gap between actual user mobility and network-perceived mobility. These sensors provide direct measurement of movement characteristics, which then inform the selection of measurement parameters and handover control strategies, improving both accuracy and timeliness.
2Speed
If measurement parameters are adjusted frequently to track mobility changes, then handover responsiveness improves, but device energy consumption increases
Solution Approach 1:
The system dynamically adjusts measurement parameters based on the determined mobility state. For high-mobility users, the system selects measurement parameters with shorter averaging periods and lower thresholds to enable faster handover detection. For low-mobility users, longer averaging periods and higher thresholds are used to reduce unnecessary measurements and conserve energy. This dynamic adaptation optimizes the balance between responsiveness and energy consumption.
Solution Approach 2:
The patent changes measurement parameters (averaging period, handover threshold, measurement frequency) based on mobility state classification. By categorizing users into different mobility states and applying appropriate parameter sets, the system avoids continuous frequent adjustments while maintaining appropriate responsiveness for each user type, thereby reducing overall energy consumption.
3Speed
If handover thresholds are lowered to detect mobility faster, then handover speed increases, but false handovers in overlapping coverage areas increase
Solution Approach 1:
The system applies different handover thresholds and measurement parameters tailored to local conditions and user-specific mobility states. Instead of using uniform thresholds, the patent adjusts parameters locally based on individual user movement patterns and network conditions. This allows lower thresholds for genuinely mobile users while maintaining higher thresholds or different parameter configurations for users in overlapping coverage areas, reducing false handovers.
Solution Approach 2:
The system performs preliminary classification of user mobility states using sensor data before applying handover threshold decisions. This preliminary assessment allows the system to set appropriate thresholds in advance - lower thresholds for confirmed high-mobility users and more conservative thresholds for users whose movement patterns suggest they may be in overlapping coverage areas, thereby preventing false handovers.
Data Source
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AI summary
A mobility module receives sensor data from one or more sensors and determines the movement of type of movement of a user device, based on the sensor data. Based on the movement or rate of movement, the mobility module transitions the user device to a mobility state. The user device evaluates the power levels of radio signals from neighbor base stations using one or more measurement parameters that are scaled of offset based on the mobility state.