Optical Sensor Handover Prediction for Mobile Devices
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Solution Overview
Problem
In radio access networks, frequent handover events between base stations can disrupt continuous reception for mobile devices, especially when moving out of a base station's coverage area, due to the limited coverage of Micro and Pico base stations.
Innovation Solution
A system utilizing network-enabled optical sensors to track the movement of mobile devices and predict handover events by detecting visual cues, allowing for timely detachment from one base station and attachment to another, ensuring continuous communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If Micro and Pico base stations are used to provide coverage, then network capacity and coverage area are improved, but handover frequency increases and service continuity deteriorates
Solution Approach 1:
The system performs preliminary actions by using optical sensors to visually track the mobile device's movement and predict future handover events before they occur. The prediction mechanism calculates anticipated handover timing and location in advance, allowing the network to prepare and execute handovers smoothly, thus preventing service interruptions despite frequent base station transitions.
2Duration of action of moving object
If handover events are executed frequently to maintain coverage, then coverage continuity is improved, but handover execution reliability deteriorates due to make-before-break timing constraints
Solution Approach 1:
The system predicts handover events in advance using visual tracking data, calculating the optimal timing and target base station before the mobile device actually needs to hand over. This preliminary prediction allows the network to initiate make-before-break handover procedures with sufficient lead time, ensuring the new connection is established before disconnecting from the old base station, thus maintaining handover execution reliability even during frequent transitions.
Solution Approach 2:
The system continuously monitors the mobile device's position and movement through optical sensors, using this feedback to dynamically adjust handover predictions and timing. This real-time feedback mechanism ensures that handover decisions are based on current device state and trajectory, improving the accuracy of predictions and the reliability of handover execution in rapidly changing scenarios.
Data Source
AI summary
System and methods for visually tracking movement associated with a mobile device in order to determine optimal locations for handing over the device between different base stations arranged in a sequence. Initially, a current location of the mobile device is determined via a radio access network associated with the device. Then, a moving object is visually detected in an immediate proximity to the location determined, using a visual sensor array associated with the radio access network. The moving object detected is assumed to be associated with the mobile device due to said proximity, and is hence visually tracked along its path of progression, until arriving at a location that was previously determined to be optimal for performing a handover between two adjacent base stations. A handover is then executed, while continuing with said visual tracking until another handover is required.