Client Device Traffic Scheduling via Moving Average Estimation
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Solution Overview
Problem
Conventional communication networks face challenges in efficiently scheduling data traffic due to the lack of advanced resource allocation and signaling mechanisms, particularly with the anticipated increase in user equipment and IoT devices, leading to high computational costs and signaling overhead, especially for varying traffic types like VoIP and DASH traffic.
Innovation Solution
A client device and network access node system that uses moving averages and scalar factors to characterize and estimate traffic behavior, reducing resource allocation signaling by transmitting control messages to determine scheduling modes and adjust resource allocations proactively, enabling flexible and accurate planning of radio resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional scheduling algorithms are used to handle increasing user equipment and IoT devices, then resource allocation can be performed, but computational cost and signaling overhead become excessively high
Solution Approach 1:
The patent applies preliminary action by having the UE report traffic characteristics (such as packet size distribution and inter-arrival time) in advance before actual scheduling occurs. The network node uses these pre-reported characteristics to determine scheduling parameters and allocate resources proactively, reducing the need for complex real-time computations and continuous signaling during actual data transmission.
Solution Approach 2:
The patent changes parameters by transforming the scheduling approach from dynamic real-time adjustments to static pre-determined parameters based on reported traffic characteristics. The network node determines scheduling parameters (such as resource allocation patterns) based on the reported packet size distribution and inter-arrival time, converting variable real-time scheduling into fixed pre-planned allocations that reduce computational overhead.
2Adaptability or versatility
If QoS mechanisms are used to classify traffic and provide application layer knowledge, then application-based access policies can be implemented, but signaling overhead increases due to buffer status indication signalling
Solution Approach 1:
The patent extracts the essential traffic classification information from continuous buffer status indication signaling. Instead of requiring ongoing signaling to maintain QoS knowledge, the system extracts key traffic characteristics (packet size distribution, inter-arrival time) during initial setup or periodic reporting, and uses these extracted parameters for subsequent scheduling decisions, eliminating the need for continuous signaling.
Solution Approach 2:
The patent applies preliminary action by collecting and reporting traffic characteristics in advance before actual scheduling occurs. The UE reports packet size distribution and inter-arrival time parameters beforehand, allowing the network node to pre-determine scheduling parameters and allocate resources without requiring continuous buffer status indication signaling during data transmission.
3Quantity of substance
If semi persistent scheduling is used to reduce resource allocation signaling for VoIP, then multiple sub frames can be scheduled with a single resource allocation, but the approach is limited to VoIP-like traffic with constant data rate
Solution Approach 1:
The patent achieves universality by creating a scheduling mechanism that can handle multiple traffic types (VoIP, DASH, and other data services) using the same basic framework. The network node determines scheduling parameters based on reported traffic characteristics from any traffic type, allowing the system to adaptively apply resource allocation strategies suitable for each traffic type while using a unified signaling approach, thus extending SPS beyond VoIP to various data services.
Data Source
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AI summary
The invention relates to a client device (100) and a network access node (300) for efficient scheduling of data traffic based on data traffic characteristics. In this respect the client device (100) interacts with the network access node (300) by transmitting a first control message (502) to a network access node (300) indicating an initial traffic information for a data packet session associated with the client device (100); receiving a second control message (504) from the network access node (300) indicating a first time window for a first moving average for the data packet session and a second time window for a second moving average for the data packet session; determining an additional traffic information for the data packet session based on the first time window and the second time window; and transmitting a third control message (506) to the network access node (300) indicating the additional traffic information for the data packet session. Furthermore, the invention also relates to corresponding methods and a computer program.