Virtual Queue Framework for Proactive Uplink Scheduling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current queue estimation methods in telecommunications networks, such as those used in HSUPA and LTE, are unrefined and reactive, leading to inefficiencies in scheduling and resource allocation, particularly for real-time services like VoIP, due to the lack of precise backlog state reconstruction and proactive scheduling capabilities.
Innovation Solution
The implementation of a Virtual Queue (VQ) framework that estimates both the size and generation time of packets, allowing for proactive scheduling by reconstructing the UE queues at the NodeB, enabling more accurate backlog state estimation and reducing signaling delay through predictive scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If queue estimation is performed using conventional reactive scheduling methods, then the scheduling process is simpler to implement, but the queue estimation accuracy deteriorates leading to unrefined backlog state reconstruction
Solution Approach 1:
The patent applies preliminary action by performing queue estimation at the UE before transmission and providing this estimation to the NodeB in advance. The UE reconstructs the queue state proactively and sends buffer status reports containing this pre-estimated information, allowing the NodeB to make scheduling decisions based on accurate pre-computed queue states rather than reacting to outdated information.
Solution Approach 2:
The patent introduces an intermediary mechanism where the UE acts as a mediator that performs queue reconstruction and estimation locally, then communicates this processed information to the NodeB. This intermediary approach allows the complex estimation logic to be distributed to the UE while the NodeB benefits from the refined queue information without implementing the complex estimation algorithms itself.
2Loss of time
If reactive scheduling is used where scheduling decisions are made after receiving uplink signaling requests, then the system responds to actual traffic needs, but signaling delay increases and proactive scheduling capability is lost
Solution Approach 1:
The patent enables proactive scheduling by having the UE perform queue estimation and send buffer status reports before the NodeB needs to make scheduling decisions. The UE reconstructs the queue state in advance and provides this information proactively, allowing the NodeB to anticipate traffic needs and allocate resources before actual transmission requests are made, thereby reducing signaling delay.
Solution Approach 2:
The patent implements a feedback mechanism where the UE continuously monitors its queue state and provides buffer status reports to the NodeB based on reconstructed queue information. This feedback loop allows the NodeB to receive updated queue state information regularly, enabling it to make informed scheduling decisions proactively rather than reactively, thus reducing overall signaling delay.
3Productivity
If conventional queue estimation methods are used without virtual queue reconstruction, then the implementation is simpler, but resource allocation efficiency deteriorates due to lack of precise backlog state information
Solution Approach 1:
The patent applies the copying principle by creating a virtual queue reconstruction at the UE that mirrors the actual queue state. The UE reconstructs the backlog state information and sends this copied queue information to the NodeB via buffer status reports. This copying approach allows the NodeB to make scheduling decisions based on an accurate replica of the queue state without needing to implement complex reconstruction algorithms, thus improving resource allocation efficiency while managing complexity.
4Reliability
If uplink scheduling waits for signaling requests from UEs, then the scheduling responds to actual traffic demands, but the scheduling latency increases and real-time service quality deteriorates
Solution Approach 1:
The patent improves real-time service quality by enabling the UE to perform preliminary queue estimation and send buffer status reports before the NodeB needs to make scheduling decisions. The UE reconstructs the queue state in advance and provides this information proactively, allowing the NodeB to anticipate traffic needs and allocate resources before actual transmission requests are made, thereby reducing scheduling latency and improving real-time service quality.
Solution Approach 2:
The patent implements continuous feedback where the UE monitors its queue state and provides regular buffer status reports to the NodeB based on reconstructed queue information. This feedback mechanism ensures the NodeB has up-to-date queue state information, enabling it to make timely scheduling decisions that meet real-time service requirements and reduce scheduling latency.
Data Source
AI summary
In a communication network, a node receives from user equipment information on the length of a queue of information units to be transmitted to the node from the user equipment. The information, for possible use by the node in scheduling transmission of these information units from the user equipment, is in the form of quantized queue length information indicative of a lower bound and an upper bound for the queue length. Transmission of information units from the user equipment to the node is detected at the node, and an improved estimate of the queue length is produced by correcting the lower bound and the upper bound via subtraction of the number of the detected information units transmitted from the user equipment to the node.