Radio Resource Control Point for QoE Optimization
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Solution Overview
Problem
Conventional wireless communication networks fail to optimize radio resource allocation effectively, as they do not consider user context or quality of experience (QoE), leading to inefficient bandwidth usage and suboptimal service provision.
Innovation Solution
Implementing a system that allocates and schedules radio resources based on user context (UCX) using a radio resource control point facility, which tracks user devices, mediates bidding processes, and generates heat maps to optimize resource allocation and scheduling, thereby maximizing aggregate user QoE while considering network constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional network criteria are used for radio resource allocation, then network management complexity is reduced, but user quality of experience (QoE) optimization is lost
Solution Approach 1:
The patent segments the radio resource management function by introducing a separate radio resource control point facility that operates independently from the base station scheduler. This control point receives QoE metrics from user devices and network state information, then generates optimized resource allocation decisions that are communicated back to the base station. This segmentation allows complex QoE-based optimization to be performed centrally without increasing the complexity of individual base station operations.
Solution Approach 2:
The radio resource control point facility acts as an intermediary between user devices and the base station scheduler. It collects QoE metrics from devices, processes this information along with network state data, and generates resource allocation recommendations. This intermediary layer enables QoE optimization without requiring the base station to directly handle complex QoE calculations, thus maintaining operational simplicity while improving user experience.
2Reliability
If real-time QoE-based optimization is implemented, then user experience is improved, but computational complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by having user devices continuously report QoE metrics to the radio resource control point facility before resource allocation decisions are needed. The control point maintains an updated view of user QoE states and network conditions, so when resource allocation is required, optimized decisions can be made quickly based on pre-collected information rather than calculating QoE metrics in real-time during the allocation process.
3Measurement precision
If detailed user context information is collected and processed, then resource allocation accuracy is improved, but information processing requirements and privacy concerns increase
Solution Approach 1:
The patent extracts only the essential QoE metrics and user context information needed for resource allocation optimization, rather than collecting and processing all possible user data. The radio resource control point facility receives specific QoE parameters from user devices and processes only this relevant information to make allocation decisions. This selective extraction approach improves allocation accuracy while minimizing information processing requirements and privacy concerns.
Data Source
AI summary
Disclosed embodiments include systems, methods, and a radio resource controller that may receive a request for radio resources from a user device. Disclosed embodiments may also determine a value ascribed to the requested radio resources. The ascribed value may reflect at least a qualitative or quantitative importance of the requested radio resources to a user of the user device. Additionally, disclosed embodiments may schedule radio resources based on the ascribed value.