AI-Based Target Cell Selection for Complex Wireless Handover
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Solution Overview
Problem
Current communication methods for determining cell handover in wireless systems are inadequate in complex scenarios, failing to meet the handover requirements of terminal devices.
Innovation Solution
Implementing an AI-based model to determine the target cell for handover, utilizing input information to make informed decisions beyond threshold-based determinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If threshold-based determination method is used for cell handover, then the method is simple to implement, but it cannot meet handover requirements in complex communication scenarios
Solution Approach 1:
The patent transforms the handover determination from simple threshold parameter comparison to multi-dimensional parameter analysis including signal strength, quality metrics, load conditions, and terminal device characteristics. This enables the system to adapt to complex scenarios by considering multiple parameters simultaneously rather than relying on single threshold values.
Solution Approach 2:
The patent introduces a determination module as an intermediary component that processes multiple input parameters and applies decision rules to generate handover recommendations. This mediator layer separates the complexity of multi-parameter analysis from the basic handover execution, allowing sophisticated decision-making while maintaining implementation simplicity.
2Reliability
If AI-based model is used to determine target cell, then handover performance in complex scenarios is improved, but computational complexity increases
Solution Approach 1:
The patent segments the handover determination process into distinct functional modules: parameter collection module, determination module with AI model, and handover execution module. This segmentation allows the computationally intensive AI model to be isolated and optimized separately, improving overall reliability while managing computational complexity through modular architecture.
Solution Approach 2:
The patent performs preliminary data collection and preprocessing of communication parameters before they are fed into the AI model. By preparing input data in advance and pre-training the AI model with historical handover data, the system reduces real-time computational burden while maintaining high handover performance in complex scenarios.
Data Source
AI summary
A communication method, a terminal device and a network device are provided. The communication method includes that: a terminal device hands over from a source cell to a target cell, where the target cell is determined based on a target Artificial Intelligence (AI) model and target input information for input into the target AI model.