User Flow Pairing Scheduler for Cross-Slice QoS Synchronization
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Solution Overview
Problem
Existing multi-user MIMO pairing technologies face computational complexity, packet-oriented data flow changes due to jitter, and challenges in coordinating user data flows across distributed network slices in 5G networks, leading to inefficient use of air interface resources and suboptimal pairing decisions.
Innovation Solution
A pairing scheduler that determines suitable pairing conditions across multiple slices, synchronizes data flows based on QoS parameters, and manages pairing asynchronously to reduce computational load and improve resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pairing is decided per scheduled transmission slot (TTI) to adapt to changing data flows, then pairing suitability is improved, but computational complexity increases tremendously
Solution Approach 1:
The system performs preliminary pairing decisions at the MAC layer before data transmission, identifying suitable flow pairs in advance. This preliminary action allows the system to prepare pairing configurations without the computational overhead of evaluating all possible pairs at each TTI, thus maintaining adaptability while reducing complexity.
Solution Approach 2:
The pairing process is segmented into multiple stages: initial pairing candidate identification at MAC layer, followed by refined scheduling decisions at higher layers. This segmentation divides the computationally intensive task into manageable parts, reducing the complexity burden on any single processing stage while maintaining overall pairing suitability.
2Stability of the object's composition
If frequent pairing decisions are made per TTI to handle packet-oriented data flows with jitter, then data flow synchronization is improved, but processing overhead increases
Solution Approach 1:
Once pairing decisions are made at the MAC layer, the pairing configuration is maintained continuously across multiple TTIs rather than being re-evaluated each slot. This continuous application of pairing decisions reduces processing overhead while maintaining data flow synchronization through the use of buffering and timing adjustment mechanisms.
Solution Approach 2:
Pairing decisions are made periodically at MAC layer scheduling instances rather than continuously at every TTI. This periodic action reduces processing overhead by limiting the frequency of pairing evaluations, while buffering mechanisms ensure that data flows remain synchronized between periodic decision points.
3Reliability
If pairing is performed across distributed network slices with separate schedulers, then slice isolation and QoS guarantees are improved, but coordination difficulty increases
Solution Approach 1:
A coordination mechanism acts as an intermediary between distributed slice schedulers and the MAC layer pairing function. This intermediary collects pairing candidate information from various slices, applies cross-slice pairing decisions at the MAC layer, and coordinates the implementation across different schedulers. This intermediary structure enables slice isolation to be maintained while facilitating the coordination needed for cross-slice pairing.
Solution Approach 2:
The MAC layer pairing function serves as a universal coordination point that handles pairing decisions across multiple network slices simultaneously. This multi-functional approach allows a single pairing mechanism to serve multiple slices with different QoS requirements, reducing the coordination complexity that would arise from having separate pairing mechanisms for each slice.
4Productivity
If multiple flows are paired on the same air interface resources to increase bandwidth utilization, then spectral efficiency is improved, but interference management complexity increases
Solution Approach 1:
The system applies different pairing strategies and interference management techniques to different flow pairs based on their specific characteristics such as channel conditions, QoS requirements, and spatial separation. This localized approach to interference management allows multiple flows to share air interface resources efficiently while handling each pair's interference characteristics individually, reducing overall management complexity.
Data Source
AI summary
It is provided a method, including monitoring if an information on a first pairing condition is received, wherein the first pairing condition indicates that a first flow is suitable for pairing under the first pairing condition; checking, if the information on the first pairing condition is received, for at least one of one or more stored second pairing conditions, if the respective stored second pairing condition matches the first pairing condition, wherein each of the one or more second pairing conditions indicates that a respective second flow different from the first flow is suitable for the pairing under the respective second pairing condition; pairing the first flow and one of the second flows if the second pairing condition related to the one of the second flows matches the first pairing condition.