UE Sensor-Based Service Optimization for Mobile Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing service optimization methods in mobile communications focus on network resource allocation without considering specific application optimizations for user equipment (UE), affecting user experience and efficiency.
Innovation Solution
A method where UE reports sensor information to a network device, enabling the device to perform service optimization processing, such as adjusting bit rates and scheduling, based on the reported data to optimize power consumption and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If service optimization is performed from a network perspective only, then network resource utilization is improved, but user experience is affected
Solution Approach 1:
The service optimization function is segmented into two parts: network-side optimization (resource allocation, signaling control) and UE-side optimization (application-specific parameters, sensor information). This segmentation allows each side to focus on its strengths while collaborating for overall system optimization, resolving the contradiction between network efficiency and user experience.
Solution Approach 2:
The UE acts as an intermediary that provides sensor information and application-specific parameters to the network, enabling the network to make more informed optimization decisions. This intermediary role bridges the gap between network resources and user experience by providing the network with insights into actual UE conditions and application requirements.
2Reliability
If application optimization specific to UE is added, then user experience is improved, but device complexity increases
Solution Approach 1:
The UE is empowered to self-report sensor information and application-specific parameters to the network, enabling it to participate actively in its own optimization. This self-service approach reduces the need for complex network-controlled optimization mechanisms, as the UE autonomously provides the necessary information for optimization decisions.
Solution Approach 2:
The optimization approach changes from controlling network parameters only to including UE-side parameters such as sensor information, application requirements, and terminal capabilities. This parameter expansion enables more precise optimization without requiring complex control mechanisms, as the additional parameters are naturally provided by the UE.
3Measurement precision
If sensor information is collected and reported, then service optimization accuracy is improved, but signaling overhead increases
Solution Approach 1:
Instead of continuously reporting all sensor information, the UE reports only the necessary sensor parameters that are relevant for service optimization at specific moments. This partial reporting approach provides sufficient information for accurate optimization while minimizing signaling overhead by avoiding redundant or excessive data transmission.
4Productivity
If cooperative optimization between network and terminal is implemented, then overall system efficiency is improved, but coordination complexity increases
Solution Approach 1:
The network-side optimization functions and UE-side optimization functions are merged into a unified service optimization framework. The network handles resource allocation and high-level optimization, while the UE handles application-specific optimization and sensor reporting. This merging allows both sides to work together efficiently without requiring complex coordination mechanisms, as each side operates within its designated scope.
Data Source
Figure 1
Figure 2
Figure 3~5
AI summary
Embodiments of the present invention provide a service optimization processing method, a device, and a system. Sensor information of UE is reported to a network side, the network side predicts a status of the UE based on the sensor information of the UE, and optimizes a service of the UE based on the status, or the network side performs service adjustment based on the sensor information of the UE. In this way, power consumption of the UE can be effectively reduced, and user experience is improved. In addition, network signaling and resource usage can be optimized, and channel resource utilization is improved.