Mobile Station Mobility Prediction for Dense Small Cell Resource Allocation
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Solution Overview
Problem
In mobile communication systems, existing methods fail to effectively manage resources between macro Base Stations (BS) and small cell BSs, particularly when small cell BSs are densely located within the service coverage of a macro BS, leading to inefficiencies in handover processes and resource allocation due to the inability to accurately predict mobility of Mobile Stations (MS) in non-terrestrial environments and dense small cell deployments.
Innovation Solution
The proposed solution involves a method where Mobile Stations (MS) perform measurement operations and report signal strength to determine neighbor small cell BS change probabilities, allowing macro BSs and small cell BSs to allocate resources based on these probabilities and suitable service conditions, thereby minimizing handover times and optimizing resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a small cell BS is deployed to increase total capacity, then system capacity increases, but handover management complexity increases due to dense small cell locations within macro BS coverage
Solution Approach 1:
The patent segments the network into macro BS and small cell BS layers, with each layer having independent resource pools. The mobility prediction mechanism is also segmented to operate independently at each BS level, allowing separate optimization of handover management for each cell type without interfering with the other layer's operations.
Solution Approach 2:
The patent implements preliminary action by predicting MS mobility patterns before handover decisions are made. The system calculates mobility prediction values based on historical handover data and uses these predictions in advance to pre-determine resource allocation strategies and handover timing, preventing handover failures before they occur.
2Measurement precision
If GPS-based mobility detection is used, then mobility measurement accuracy improves, but applicability deteriorates in non-terrestrial environments such as subway and tunnel
Solution Approach 1:
The patent introduces an intermediary approach by using network-based mobility prediction mechanisms that operate through signaling between MS and BSs, rather than relying on external GPS infrastructure. This intermediary signaling system allows mobility detection to function in both terrestrial and non-terrestrial environments by using available network measurements and historical data.
3Productivity
If handover to small cell BS is allowed for high mobility MS, then resource utilization improves, but service continuity deteriorates due to frequent handovers
Solution Approach 1:
The patent implements dynamics by making handover decisions adaptive to real-time mobility conditions. The system continuously updates mobility prediction values based on recent handover patterns and uses these dynamic predictions to adjust handover thresholds and resource allocation in real-time, allowing the system to respond flexibly to changing mobility conditions rather than using fixed rules.
4Ease of manufacture
If mobility prediction based on macro BS handover counting is used, then implementation simplicity improves, but prediction accuracy deteriorates in dense small cell environments
Solution Approach 1:
The patent applies local quality by implementing separate mobility prediction mechanisms for macro BS and small cell BS. Instead of using a single unified prediction method, the system maintains distinct prediction values and calculation methods tailored to each BS type's characteristics, allowing each layer to be optimized for its specific environment while maintaining overall system simplicity.
Data Source
AI summary
A method for allocating a resource by a Mobile Station (MS) in a mobile communication system includes performing a measurement operation and a measurement report operation; and being allocated a resource from a small cell Base Station (BS) or a macro BS based on a neighbor small cell BS change probability and a neighbor small cell BS list, wherein the neighbor small cell BS list includes information on neighbor small cell BSs, and the neighbor small cell BSs are neighbor small cell BSs of which received signal strengths for reference signals measured by the MS are equal to or greater than a threshold received signal strength, and wherein the neighbor small cell BS change probability is determined using a neighbor small cell BS list which is generated at a current timing point and a neighbor small cell BS list which is generated at a previous timing point.