UE Profile-Based Handover Parameter Optimization
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Solution Overview
Problem
Current mobile networks face challenges in maintaining seamless connectivity for subscribers moving between cells, particularly due to fluctuations in radio channel conditions and traffic load, leading to high probabilities of connection drops during handovers between different Radio Access Technologies (RATs).
Innovation Solution
The method involves classifying User Equipment (UE) into specific user profiles based on speed and location environments, allowing for individual parameter settings that optimize handover timing and execution, using techniques such as fading profile analysis, Doppler shift detection, and positioning data to dynamically adjust mobility thresholds and trigger times for each UE, thereby improving network performance and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cell re-selection and handover are triggered based on radio channel conditions or traffic load, then network resource allocation is optimized, but connection drops increase during handovers between different RATs
Solution Approach 1:
The patent applies preliminary action by detecting characteristic information (speed, location, behavior patterns) and classifying UEs into user profiles before handover events occur. This classification enables the network to pre-configure appropriate parameter settings for each UE type, ensuring that handover parameters are optimized in advance rather than reactively adjusted during handover, thus reducing connection drops while maintaining resource allocation efficiency
Solution Approach 2:
The patent implements local quality by assigning individual parameter settings to each UE based on its specific user profile, rather than applying uniform parameters to all UEs in a cell. This allows the network to tailor handover parameters (such as measurement thresholds, trigger conditions, and execution timing) to the specific characteristics of each UE type (e.g., fast-moving vs. stationary, voice vs. data services), optimizing both connection reliability and resource allocation for each local case
2Device complexity
If uniform parameter settings are applied to all UEs in a cell, then network configuration is simplified, but handover performance deteriorates for specific user types (e.g., fast-moving subscribers)
Solution Approach 1:
The patent applies segmentation by dividing the UE population into distinct user profiles based on characteristic information such as mobility speed, service type, and behavior patterns. This segmentation enables the network to apply different parameter settings to different UE groups (e.g., fast-moving subscribers, stationary users, voice service users, data service users), thereby improving handover performance for each specific user type while maintaining manageable configuration complexity through automated classification
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting handover parameters based on UE classification into different user profiles. The system modifies parameters such as measurement thresholds, handover trigger conditions, and execution timing according to the specific characteristics of each UE type, allowing optimized handover performance for fast-moving subscribers, stationary users, and different service types without requiring complete reconfiguration of the network
3Reliability
If handover is triggered earlier for fast-moving subscribers, then connection continuity is improved, but unnecessary handovers increase for stationary or slow-moving users
Solution Approach 1:
The patent applies dynamics by making handover parameters adaptive to each UE's mobility characteristics and behavior patterns. The system dynamically adjusts handover trigger conditions and timing based on the UE's classified user profile, allowing earlier handover triggering for fast-moving subscribers to maintain connection continuity, while simultaneously applying later or more conservative triggering for stationary or slow-moving users to avoid unnecessary handovers, thus optimizing the balance between connection reliability and handover efficiency for each UE type
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the reliability and performance of mobile networks by ensuring timely and efficient handovers, reducing connection drops, and maintaining service continuity, especially for fast-moving subscribers, while avoiding unnecessary changes for stationary users, thus improving overall network operability and user experience.
Implementation Method 1
detecting the Doppler shift occurring when sending signals between the BS and the UE or vice versa
Data Source
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AI summary
The present invention describes a method for defining and setting parameters in a cellular mobile communication network, in particular for setting parameters being used for performing and/or triggering a handover or cell re-selection routine, wherein the method comprises the following steps: detecting at least one characteristic information of a user equipment, i.e. UE, classifying the UE on basis of said at least one characteristic information into a specific one of a plurality of user profiles, and setting specific parameters in the cellular mobile communication network individually for said UE on basis of its user profile, preferably setting UE specific parameters which are used for performing and/or triggering a handover or cell re-selection routine and/or radio resource management on basis of the UE's user profile.