Cellular Network Insights via SSID Tunneling
Solution Overview
Problem
Existing wireless communication networks face challenges in efficiently delivering data, particularly video data, due to network congestion and coverage issues, which can lead to interruptions or degradation in video quality, especially in areas with poor coverage or high loads.
Innovation Solution
A method and apparatus that detect network congestion on cellular networks and transmit non-cellular identifiers, such as basic service set identifier values, to facilitate knowledge sharing between user equipment and evolved Node Bs, enabling efficient data delivery by tunneling network assistance data through LTE system information blocks, thereby providing network insights to devices for optimized data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video data is delivered just in time for playback, then system capacity is optimized and resource waste is reduced, but video quality may be interrupted or degraded in areas with poor coverage or high network load
Solution Approach 1:
The system performs preliminary actions by delivering video data in advance of the actual playback time when network conditions are favorable. The media optimizer monitors network conditions and proactively transfers video segments to user equipment before the scheduled playback time, ensuring data availability even when coverage is poor or network load is high during playback.
2Reliability
If video data is pre-filled before needed, then video quality interruptions are avoided, but transmission capacity is consumed in advance
Solution Approach 1:
The system dynamically adjusts the timing and amount of video data delivery based on real-time network conditions. The media optimizer continuously monitors network load, coverage quality, and user behavior patterns to adaptively determine when and how much data to pre-deliver, balancing the trade-off between ensuring video quality and conserving transmission capacity.
Solution Approach 2:
The system implements feedback mechanisms where the media optimizer receives information about network conditions, user playback behavior, and data delivery status. This feedback loop enables the system to learn from past performance and continuously optimize pre-filling strategies, adjusting transmission capacity allocation based on actual network conditions and user needs.
3Productivity
If network insights are shared between user equipment and network infrastructure, then data transfer decisions are optimized, but device complexity increases
Solution Approach 1:
The system introduces a media optimizer as an intermediary component that manages the complexity of network insight processing. Rather than requiring user equipment to independently analyze and act on complex network conditions, the media optimizer serves as a mediator between the network infrastructure and user applications, translating network insights into actionable data transfer decisions and simplifying the overall system architecture.
Data Source
AI summary
Network insights may be useful in various communication networks. For example, certain cellular or similar networks may benefit from the delivery of cellular network insights to subscriber devices through service set identifier (SSID). A method can include detecting, by a device, at least one advertised value of non-cellular access, wherein the at least one advertised value is received by the device over a cellular system information block message. The method can also include extracting, from the at least one advertised value, at least one cellular network insight for a cellular network condition.