Wireless Network Pre-Authentication Using Cell Residence Time Prediction
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Solution Overview
Problem
Current methods for pre-registration and pre-authentication in wireless networks, such as E-UTRAN and eHRPD, face challenges in determining when and with which neighboring cells to perform these operations, leading to potential handoff delays and inefficient resource management, especially in heterogeneous networks.
Innovation Solution
A method using stochastic processes, like the Wiener process, and time series analysis to estimate cell residence time and predict network resource requirements, allowing for optimized pre-authentication and pre-registration with neighboring cells based on signal-to-noise ratios and historical data, while managing resource reservation and release effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-registration and pre-authentication are performed with multiple neighboring cells, then handoff reliability is improved, but network signaling overhead and resource consumption increase
Solution Approach 1:
The patent performs pre-registration and pre-authentication actions in advance before handoff is actually needed. By predicting future handoff targets based on historical movement data and performing authentication beforehand, the system ensures reliable handoff while reducing the urgency and volume of signaling during actual handoff events.
Solution Approach 2:
The patent selectively performs pre-registration with only the most likely handoff target cells rather than all neighboring cells. By ranking candidate cells based on prediction algorithms and selecting only top candidates, the system achieves sufficient handoff reliability without overwhelming network signaling overhead.
2Loss of time
If pre-authentication is performed early, then handoff delay is reduced, but network resources are reserved for longer periods increasing resource consumption
Solution Approach 1:
The patent dynamically adjusts the resource reservation period based on predicted handoff timing and user movement patterns. Rather than using fixed reservation periods, the system adapts resource allocation to actual handoff needs, releasing resources sooner when handoff is delayed or canceled, thus reducing unnecessary resource consumption while maintaining early pre-authentication benefits.
3Measurement precision
If centralized database is used to collect user equipment movement histories, then prediction accuracy is improved, but system complexity and performance bottleneck increase
Solution Approach 1:
The patent segments the centralized prediction function into distributed components at different network elements (e.g., at the access network and core network levels). Each segment handles local prediction tasks using locally available data, reducing the burden on any single centralized database while maintaining overall prediction accuracy through coordinated operation of multiple segments.
Data Source
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AI summary
A system and method is provided to manage wireless network mobility and wireless network resources. In one aspect of the invention, network equipment acquires samples associated with time that past user devices stayed in the coverage range of the network equipment and estimates a time that a user device currently stays in the cell based on the acquired samples. In another aspect, pre-authentication and pre-registration of the user device in another network are performed based on the estimated time. In yet another aspect, network resources reserved for the user device are released based on the estimated time.