Intelligent Initial Provisioning for User Equipment
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Solution Overview
Problem
Current initial provisioning methods for User Equipment (UE) with Subscriber Identity Modules (SIMs) do not always provide the optimal network service based on signal strength, network congestion, and contractual criteria, leading to suboptimal user experience and service quality.
Innovation Solution
Implementing intelligent initial provisioning that analyzes criteria such as UE location, hardware and software capabilities, and network performance to determine the most suitable home network for UE, which can include direct provisioning or through a third party, using AI/ML models and multiple SIMs for different services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If MVNOs or MVNEs choose the network for initial provisioning, then provisioning process is simple, but the service quality and signal strength may not be optimal
Solution Approach 1:
The UE autonomously performs network selection by evaluating multiple MNO networks based on criteria including signal strength, network congestion, and service quality. The UE independently determines the optimal home network without requiring MVNO/MVNE intervention in the selection process, thereby achieving both simplicity and optimality.
Solution Approach 2:
The system dynamically adjusts provisioning parameters by considering real-time network conditions such as signal strength, congestion levels, and service quality metrics. The UE modifies its network selection based on changing parameters to ensure optimal service quality while maintaining procedural simplicity.
2Reliability
If manual network selection is used, then contractual criteria can be met, but the process is time-consuming and less efficient
Solution Approach 1:
The UE pre-evaluates and pre-selects the optimal network based on stored criteria including contractual requirements, signal strength, and network performance. This preliminary action eliminates the need for time-consuming manual selection processes while ensuring contractual criteria are met, achieving both reliability and efficiency.
Solution Approach 2:
The manual mechanical process of network selection is replaced with automated electronic evaluation and decision-making. The UE uses electronic criteria evaluation and algorithmic selection to determine the optimal network, significantly reducing provisioning time while maintaining compliance with contractual requirements.
3Device complexity
If single SIM is used, then device complexity is low, but service versatility and adaptability are limited
Solution Approach 1:
The UE is configured with multiple SIMs from different MNO networks, enabling it to universally access and evaluate multiple network options. This multi-SIM configuration allows the UE to provide diverse services and adapt to different network conditions, significantly enhancing service versatility while managing device complexity through intelligent selection algorithms.
Data Source
AI summary
Intelligent initial provisioning for UE with one or more than one subscriber identity modules (SIMs) is disclosed. Intelligent initial provisioning is the selection and provisioning of subscribers on a network from among multiple mobile network operator (MNO) networks using a respective SIM. In other words, intelligent initial provisioning pertains to selecting the home network of the UE. The intelligent initial provisioning may take into account criteria such as the home location of the UE, the capabilities of the UE, phone number eligibility, the average signal strength of the MNO networks in the area, the typical congestion on the MNO networks, the number or percentage of subscribers of the initial provisioning entity that are on the MNO networks, cost criteria, subscription criteria, MNO contract criteria, highest service quality, lowest voice and SMS service cost, etc. Forecasts of future traffic on the MNO networks may also factor into the intelligent initial provisioning.