Data Rate Throttling for Mobile Network Load Management
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Solution Overview
Problem
Large crowds at sporting events and dense gatherings stress mobile radio network infrastructure, leading to noticeable gaps in voice and data service due to high bandwidth usage from smartphone users, which existing temporary or portable antennas struggle to manage effectively.
Innovation Solution
A system that identifies and throttles the data rates of mobile devices at overloaded venues, selectively reducing data rates of devices causing excessive strain on the network, predicting peak usage times, and setting maximum upload and download speeds to prevent service disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If temporary or portable mobile radio antennas are deployed to maintain service, then service coverage is improved, but network infrastructure overload remains and service gaps persist
Solution Approach 1:
The system changes the operational parameters of mobile devices by dynamically adjusting data rates based on network conditions. When the network approaches capacity, the system reduces data rates for affected devices, transforming the network state from overloaded to manageable, thereby maintaining service continuity without adding physical infrastructure complexity
2Reliability
If data rates are throttled to manage network load, then network overload is reduced and service reliability improves, but user data throughput decreases
Solution Approach 1:
The system implements feedback by continuously monitoring network load conditions and device data rates. Based on this feedback, the system dynamically adjusts data rates to maintain optimal network performance. This closed-loop control ensures that data rate reductions are applied only when necessary to prevent overload, thereby maintaining service stability while minimizing impact on user throughput
3Productivity
If selective data rate reduction is applied to devices causing excessive strain, then network load management is improved, but device identification and selection complexity increases
Solution Approach 1:
The system enables devices to self-identify and self-regulate based on their impact on network load. By monitoring their own data consumption and network conditions, devices can determine when rate reduction is appropriate without requiring complex external management. This self-service approach simplifies the overall system architecture while maintaining effective network load management
Data Source
AI summary
The throttling of mobile device data rates is provided at events, e.g., sporting events, and other venues with large, dense crowds. The system can monitor the loading of the mobile radio antennas at the venue, and when the loading reaches a threshold loading point, the system can selectively throttle the data rates of mobile devices at the venue. In some embodiments, the system can throttle the data rates of certain applications on the mobile devices, or can select mobile devices that are placing a large strain on the network infrastructure to throttle. In other embodiments, the system can set maximum upload and download speeds for all the mobile devices at the venue.