ENDC Handover Mobility Control in Heterogeneous Networks
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Solution Overview
Problem
Current telecommunications networks face challenges in maintaining seamless handovers between different types of cells, particularly in heterogeneous networks, leading to potential disruptions and reduced connectivity during user mobility.
Innovation Solution
Implementing a machine learning algorithm in the telecommunications network to enhance evolved universal terrestrial radio access network dual connectivity (ENDC) by proactively determining the support for ENDC cells and adjusting handover thresholds to retain users on ENDC cells for longer, thereby improving coverage and reducing packet loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standard handover procedures are used in heterogeneous networks, then handover process is simple, but handover success rate decreases and packet loss increases during user mobility between ENDC and non-ENDC cells
Solution Approach 1:
The system performs preliminary determination of ENDC support capability at the target cell before executing handover. The network device proactively identifies whether the target cell supports ENDC functionality and pre-configures appropriate handover parameters, preventing handover failures before they occur. This advance preparation ensures reliable handovers while maintaining controlled complexity through automated detection.
Solution Approach 2:
The system dynamically adjusts handover parameters including thresholds and timing configurations based on the target cell's ENDC support status. When ENDC compatibility is detected, optimized parameters are applied to enhance handover success; when incompatible, standard parameters are used. This adaptive parameter adjustment resolves the contradiction by improving reliability through intelligent modification rather than complex procedural changes.
2Duration of action of moving object
If users are retained on ENDC cells for longer periods, then connectivity to ENDC services is improved, but handover delays may occur when moving between cells
Solution Approach 1:
The system proactively determines ENDC support status of target cells before handover execution. By performing this determination in advance, the system can prepare appropriate handover configurations and notify relevant network entities beforehand. This eliminates handover delays while allowing users to remain connected to ENDC cells longer, as the preliminary assessment ensures smooth transitions when moving away from ENDC coverage.
Solution Approach 2:
The network device acts as an intermediary that coordinates between user equipment and target cells during handover. It manages the timing and sequencing of handover messages, ensuring that ENDC capability determination and handover execution are properly synchronized. This intermediary control prevents delays by orchestrating the handover process efficiently while maintaining extended ENDC connectivity.
3Productivity
If machine learning algorithms are implemented to optimize handover, then handover success rate and throughput are improved, but network complexity increases
Solution Approach 1:
The network device autonomously determines ENDC support capability of target cells and automatically selects appropriate handover parameters without requiring complex external optimization systems. This self-service approach improves throughput through intelligent decision-making while avoiding the complexity of external machine learning infrastructure. The system serves itself by embedding determination logic directly in the handover control functionality.
Solution Approach 2:
The patent replaces complex procedural mechanisms with streamlined determination and configuration processes. Instead of implementing full machine learning systems, it substitutes a focused determination mechanism that directly identifies ENDC compatibility and applies appropriate parameters. This substitution achieves productivity improvements through intelligent automation while keeping complexity manageable by replacing elaborate mechanical-like procedures with simpler determination logic.
Data Source
AI summary
A method includes determining whether user equipment (UE) in a telecommunication network is configured to support evolved universal terrestrial radio access network dual connectivity (ENDC). Responsive to the UE being determined as configured to support the ENDC determining whether a source cell and a target cell are configured to support the ENDC. Performing on processing circuitry a first mobility modification in response to determining the source cell is an ENDC source cell and the target cell is a non-ENDC target cell. Performing on the processing circuitry a second mobility modification in response to determining the target cell is an ENDC target cell and the source cell is a non-ENDC source cell. The second mobility modification is different from the first mobility modification. Performing a handover from the source cell to the target cell in response to both the source cell and the target cell being configured for ENDC or non-ENDC.