Forecasting Wireless Rate Discounts for Network Load Management
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Solution Overview
Problem
Wireless communication networks face challenges in efficiently managing radio resources and subscriber behavior due to the lack of effective forecasting and notification of future rate discounts, especially in 3G networks without cell broadcast support.
Innovation Solution
A system that provides wireless user terminals with forecasted rate discount information, using nodes and core networks to determine and transmit future rate discounts based on location, time, and user movement, displayed through various graphical and textual interfaces, including maps and animations, enabling users to adjust their communication behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dynamic pricing/discounts are implemented to manage network resources, then network utilization efficiency is improved, but the complexity of rate management and user information provision increases
Solution Approach 1:
The system provides forecasted rate discount information to users in advance before the actual discount period begins. This preliminary information provision allows users to plan their communication behavior ahead of time, knowing when discounted rates will be available, thereby facilitating load management without requiring complex real-time decision-making by users or the network
2Ease of operation
If forecasted rate discount information is provided to users in advance, then user ability to manage communication costs is improved, but the complexity of information provision and network signaling increases
Solution Approach 1:
The network node acts as an intermediary that automatically generates, processes, and transmits forecasted rate discount information to users. This intermediary function simplifies the user interface by presenting ready-to-use forecast information without requiring users to manually query or interpret complex network pricing structures, while the network node handles the computational complexity of generating these forecasts
3Productivity
If rate discounts are offered based on location and time to change subscriber call patterns, then network traffic distribution is improved, but the complexity of dynamic pricing implementation increases
Solution Approach 1:
The system pre-calculates and provides forecasted rate discount information based on anticipated location and time conditions. Users receive advance notice of when and where discounted rates will be available, allowing them to proactively adjust their communication patterns to match favorable conditions without requiring complex real-time analysis by the user device
Solution Approach 2:
The system implements feedback mechanisms where user responses to forecasted discount information are monitored and used to refine future forecasts. The network node receives information about user behavior changes in response to discount forecasts and adjusts subsequent forecast information to optimize traffic distribution patterns while learning from actual user responses
Data Source
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AI summary
A user interface of a wireless user terminal provides a forecast of a future rate discount that may apply at a future time and/or at a possible future location of the wireless user terminal. The forecast may be displayed as a map and/or as textual or graphical information, and may be provided in response to a user request, in response to receipt of a message from the wireless network and/or automatically at a given time. Related systems, methods and devices are described.