Prescheduling Uplink Resources via UE Communication Patterns
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Solution Overview
Problem
Current prescheduling methods in wireless networks lead to waste of resources and power due to pre-allocated uplink resources not being requested or used by UEs, resulting in increased latency.
Innovation Solution
Implementing a method where UEs send prescheduling parameters indicative of their communication patterns to the network, allowing the scheduler to pre-allocate uplink resources based on anticipated data requirements, thereby reducing latency and resource wastage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If predictive prescheduling is implemented to reduce UL scheduling latency, then latency is reduced, but resources and power are wasted due to pre-allocated resources not being used
Solution Approach 1:
The patent applies preliminary action by having the network node pre-allocate uplink resources to the UE based on predicted communication needs. The scheduler predicts when the UE will need to transmit data and reserves resources in advance, reducing scheduling latency while avoiding complete waste through intelligent prediction rather than blanket pre-allocation
Solution Approach 2:
The patent implements feedback mechanisms where the network node monitors actual communication patterns and resource usage. Based on this feedback, the scheduler adjusts future prescheduling decisions to improve accuracy, reducing both latency and resource waste by learning from past predictions and correcting erroneous allocations
2Manufacturing precision
If prescheduling parameters are sent from UE to network node, then resource allocation accuracy is improved, but communication overhead increases
Solution Approach 1:
The patent extracts only the essential prescheduling parameters needed for accurate resource allocation from the UE to the network node. Instead of transmitting complete communication patterns or excessive data, only critical parameters such as predicted data arrival times, data volume estimates, and priority levels are extracted and transmitted, maintaining allocation accuracy while minimizing overhead
Data Source
AI summary
Example embodiments presented herein are directed towards a wireless device and a network node, and corresponding methods therein, for prescheduling uplink communications in a wireless network. Such prescheduling is performed prior to the time the uplink communication is needed. According to the example embodiments, the prescheduling is performed with the network node having knowledge of a communication pattern of the wireless device via at least one prescheduling parameter obtained by the network node.