RRC Idle QoE Reporting With Adaptive Buffer Prioritization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wireless communication networks face challenges in reporting Quality of Experience (QoE) measurements when a User Equipment (UE) is in RRC idle or inactive state, leading to delayed and outdated data due to buffering, which can exceed memory limits and waste network resources.
Innovation Solution
The UE is pre-configured to perform QoE measurements and manage a buffer while in RRC idle or inactive state through pre-configuration from the base station, including priority levels and expiry timers, allowing for adaptive reporting using small data transmission (SDT) or transitioning to RRC connected state based on buffer conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If QoE measurements are buffered while in RRC idle or inactive state, then measurements can be stored for later reporting, but the buffer may exceed memory limits and waste network resources
Solution Approach 1:
The UE is pre-configured with QoE measurement parameters and buffer management policies before entering RRC idle or inactive state. This preliminary configuration enables the UE to autonomously manage QoE measurements and reporting without continuous network control, preventing buffer overflow while ensuring reliable reporting.
Solution Approach 2:
The buffer management mechanism dynamically adjusts based on UE state transitions and network conditions. The UE can adaptively clear or retain QoE measurements in the buffer based on whether it transitions to connected state or remains idle/inactive, optimizing memory usage while maintaining reporting reliability.
2Reliability
If QoE measurements are buffered until UE returns to RRC connected state, then reporting can be performed, but reporting delays occur and data becomes outdated
Solution Approach 1:
The UE performs QoE measurements and prepares reporting actions before potentially transitioning to connected state. The pre-configuration includes reporting criteria and triggers that enable the UE to report QoE measurements promptly when conditions are met, reducing delays while ensuring complete reporting.
Solution Approach 2:
The network receives QoE measurement reports from the UE and can send additional configuration or triggers. This feedback mechanism allows the network to request specific QoE reports or adjust reporting parameters, ensuring timely and relevant QoE data delivery without excessive delays.
3Loss of information
If UE transitions to RRC connected state for QoE reporting, then complete measurements can be reported, but unnecessary RRC signaling and network resources are consumed
Solution Approach 1:
The QoE measurement reporting function is extracted from the mandatory RRC connected state transition. The UE can report QoE measurements using streamlined procedures or pre-configured uplink resources without fully establishing an RRC connected state, reducing signaling overhead while maintaining data completeness.
Solution Approach 2:
The QoE reporting mechanism is designed to work across multiple UE states (idle, inactive, and connected). The same QoE measurement and reporting framework adapts to different RRC states, eliminating the need for state transitions solely for reporting purposes and reducing unnecessary signaling.
Data Source
AI summary
Techniques, described herein, include solutions for managing a buffer in a radio resource control (RRC) idle or RRC inactive state. A user equipment (UE) may be pre-configured by a base station to manage the buffer via RRC signaling while in the RRC connected state. The pre-configuration may additionally configure the UE to perform quality of experience (QoE) measurements in the RRC idle/inactive state. The UE may transition to RRC idle or RRC inactive, perform the QoE measurements, and store results of the QoE measurements in the buffer. During operation, the buffer may become full. Based on the pre-configuration, the UE may be configured to manage the buffer by removing outdated or less prioritized data when necessary.