Predictive Handover Service for MEC Resource Allocation
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Solution Overview
Problem
Conventional wireless network handover techniques often result in the wasteful reservation of radio resources in cells that an end device does not ultimately enter, leading to inefficient use of network resources and potential latency issues, especially in scenarios requiring low latency like C-V2X and autonomous vehicles.
Innovation Solution
A wireless resources handover service that synchronizes end devices with the network to predict their mobility profile, allowing the network to pre-allocate resources only where the device will roam, using scheduler logic to determine optimal handover routes and resource allocation across MEC sites to maintain service continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radio resources are reserved in all neighboring cells ahead of handover, then service continuity is maintained, but network resource waste increases
Solution Approach 1:
The system performs preliminary actions by predicting the end device's mobility profile and pre-reserving resources only in cells that will be entered, rather than reserving resources in all neighboring cells. This maintains service continuity while avoiding resource waste in cells that won't be accessed.
Solution Approach 2:
The patent applies local quality by making resource reservation cell-specific rather than universal. Resources are reserved locally only in the specific cells along the predicted mobility path, rather than uniformly across all neighboring cells, optimizing resource allocation based on actual need.
2Reliability
If resources are pre-allocated in all neighboring cells, then handover reliability is improved, but resource allocation efficiency deteriorates
Solution Approach 1:
The system calculates the end device's mobility profile in advance and performs preliminary resource allocation only in the specific cells that will be entered along the predicted path. This ensures handover reliability while improving resource allocation efficiency by avoiding allocation in cells that won't be accessed.
Solution Approach 2:
The patent changes the parameter of resource allocation from a static, uniform approach across all neighboring cells to a dynamic, selective approach based on predicted mobility parameters. This optimization improves resource allocation efficiency while maintaining handover reliability.
3Reliability
If conventional handover techniques are used, then service continuity is maintained, but latency increases
Solution Approach 1:
The system performs preliminary resource reservation based on predicted mobility profiles before handover is actually needed. This advance preparation reduces handover latency while maintaining service continuity, as resources are already in place when the end device arrives.
Data Source
AI summary
Systems, methods, and computer-readable media described herein provide for obtaining, mobility information associated with an end device, wherein the mobility information includes a starting location and a destination location; identifying multiple mobility routes from the starting location to the destination location; identifying a set of wireless resources accessible along each of the mobility routes; selecting, from the multiple mobility routes, a predetermined mobility route based on the sets of wireless resources; selecting, from the sets of wireless resources, wireless resources handover targets in the predetermined mobility route; generating mobility control information including the set of wireless station handover targets; and transmitting a mobility control message including the mobility control information to the end device and at least one of wireless resources handover targets.