Dynamic Location Reporting for Cellular Blind Handovers
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Solution Overview
Problem
In cellular telecommunications networks, blind handovers without preparation phase can be unsuccessful due to the requirement of UE radio and processing resources for location determination, especially in scenarios where traditional handovers are time-constrained, such as when a user enters a tunnel with sudden signal strength decrease.
Innovation Solution
A method where UEs report their locations at varying rates based on geographical region density thresholds, allowing for reduced resource usage during blind handovers by increasing reporting frequency only when approaching specific areas with high RLF event densities, such as near tunnel entrances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If UEs continuously report their location at high frequency to enable accurate blind handovers in areas with sudden signal deterioration, then handover reliability is improved, but UE radio and processing resource consumption increases
Solution Approach 1:
The system applies different location reporting strategies to different geographical regions. In regions with high RLF event density (such as near tunnel entrances), UEs are instructed to report location at higher frequencies, while in regions with low RLF density, reporting frequency is reduced. This local differentiation resolves the contradiction by concentrating resources where they are most needed for handover reliability while conserving UE resources in stable areas.
Solution Approach 2:
The location reporting frequency is made dynamic rather than static. The network determines RLF event density in different geographical regions and dynamically adjusts the reporting rate accordingly. This dynamic adaptation allows the system to optimize the balance between handover reliability and resource consumption based on actual environmental conditions, rather than applying a uniform reporting rate everywhere.
2Speed
If UEs perform continuous location measurements and reporting to ensure timely blind handovers in time-constrained scenarios, then handover speed is improved, but UE processing resources are depleted
Solution Approach 1:
The system implements location reporting at different rates in different geographical regions based on RLF event density. In regions with high RLF density where fast handover is critical, UEs report location more frequently, providing the network with timely information for blind handovers. In regions with low RLF density, reporting frequency is reduced, thereby conserving UE processing resources while still maintaining adequate handover capability when needed.
Solution Approach 2:
Instead of requiring all UEs to continuously report location at maximum frequency, the system applies partial action by instructing only those UEs in high RLF density regions to report at higher frequencies. This selective approach provides sufficient location information for timely blind handovers in critical areas without depleting UE processing resources in areas where such intensive reporting is not necessary.
3Measurement precision
If the network monitors all UEs at high reporting rates to identify RLF-prone areas for blind handover optimization, then measurement precision is improved, but network energy consumption increases
Solution Approach 1:
The network dynamically adjusts location reporting rates based on determined RLF event density in different geographical regions. Initially, the network may monitor UEs at higher rates to accurately map RLF-prone areas, then uses this information to optimize reporting rates in subsequent periods. This dynamic adjustment allows the network to achieve precise measurement of RLF event density while managing energy consumption by reducing monitoring intensity in stable regions.
Solution Approach 2:
The network performs periodic determination of RLF event density in geographical regions rather than continuous monitoring at maximum intensity. By periodically updating the RLF density map and adjusting reporting rates accordingly, the network achieves sufficient measurement precision to identify and respond to RLF-prone areas while avoiding sustained high energy consumption from continuous intensive monitoring of all UEs.
Data Source
AI summary
This disclosure relates to a method in a cellular telecommunications network, and a network node for implementing the method, the cellular telecommunications network including a base station having a coverage area, and a plurality of User Equipment (UE) located within the base station's coverage area, the method including instructing a first plurality of UEs to report their location; associating an occurrence of a connection performance indication for each UE of the first plurality of UEs with a reported location for that UE; defining a first geographical region in which the density of reported locations is above a first density threshold; defining a second geographical region in which the density of reported locations is above a second density threshold, wherein the area of the first geographical region is greater than the area of the second geographical region; instructing a second plurality of UEs within the first geographical region to report their location at a first reporting rate; and instructing a third plurality of UEs within the second geographical region to report their location at a second reporting rate.