Dynamic TDD Configuration for Wireless Network QoS
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wireless networks face inefficiencies in resource allocation for time division duplex (TDD) communications, leading to suboptimal utilization of RF resources and increased queueing delays, which affect user experience.
Innovation Solution
Dynamic adjustment of TDD parameters based on varying criteria such as network slices, UE attributes, and QoS thresholds, using AI/ML techniques to optimize uplink and downlink resource allocation on a per-UE basis, allowing for granular control of resource allocation without affecting other UEs connected to the same RAN.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dynamic TDD parameter adjustment is implemented per-UE, then RF resource utilization is enhanced and queueing delays are reduced, but device complexity and network control complexity increase
Solution Approach 1:
The patent segments the TDD resource allocation into per-UE configurations, allowing each UE to have customized uplink-downlink time slot ratios based on their specific traffic patterns and QoS requirements. This segmentation enables granular control of RF resources while maintaining overall network coordination through the gNB.
Solution Approach 2:
The patent implements dynamic adjustment of TDD parameters where the gNB can modify uplink-downlink time slot ratios in real-time based on varying traffic conditions, UE buffer states, and QoS requirements. This dynamic approach allows the system to adapt to changing network conditions and optimize resource utilization continuously.
2Reliability
If per-UE TDD optimization is implemented, then user experience is improved, but processing overhead and signaling overhead increase
Solution Approach 1:
The patent performs preliminary assessment of UE traffic patterns, buffer states, and QoS requirements to pre-determine optimal TDD configurations. By anticipating future traffic conditions and proactively adjusting parameters before congestion occurs, the system reduces reactive processing overhead and signaling requirements.
Solution Approach 2:
The patent implements feedback mechanisms where the gNB monitors UE buffer states, traffic patterns, and QoS compliance, then uses this feedback to continuously optimize TDD parameter assignments. This closed-loop approach ensures user experience improvements while minimizing unnecessary signaling by only adjusting parameters when actual performance degradation is detected.
Data Source
AI summary
A system described herein may identify Quality of Service (“QoS”) information associated with a User Equipment (“UE”) that is connected to a radio access network (“RAN”) of a wireless network. The QoS information may include or may be based on a network slice identifier, a QoS value, a Service Level Agreement (“SLA”), a model associated with UE attributes, or other suitable information. The system may determine a time division duplex (“TDD”) configuration for the UE based on the identified QoS information and/or models that associate UE attributes to TDD configurations. The system may implement the determined TDD configuration at the RAN. The UE and the RAN may communicate with each other according to the implemented TDD configuration, which may include particular timing information for uplink and downlink communications between the UE and the RAN.