Dynamic Uplink Configured Grant for URLLC Latency
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Solution Overview
Problem
Current ultra-reliable low latency communications (URLLC) solutions in 5G networks face limitations such as high latency, poor spectrum efficiency, and inefficiency in resource allocation, which hinder their ability to support diverse URLLC services effectively.
Innovation Solution
The implementation of a dynamic uplink configured grant (UCG) system that dynamically selects modulation and coding schemes based on real-time radio channel conditions, allowing for flexible resource allocation and improved spectrum efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional uplink grant allocation is used, then resource allocation simplicity is maintained, but latency increases and spectrum efficiency deteriorates
Solution Approach 1:
The patent implements dynamic grant allocation where the network device dynamically determines uplink grant parameters (time-frequency resources, modulation and coding scheme) based on real-time channel conditions and URLLC service requirements, rather than using fixed static grants. This dynamic adaptation reduces latency by allocating resources promptly based on actual needs while maintaining manageable complexity through automated base station control.
Solution Approach 2:
The system employs feedback mechanisms where the network device receives channel state information and service requirements from the user equipment, then uses this feedback to dynamically adjust uplink grant allocations. This closed-loop approach optimizes latency performance by responding to real-time conditions while the automated feedback processing keeps system complexity manageable.
2Loss of energy
If static resource allocation is used, then system complexity is reduced, but spectrum efficiency deteriorates
Solution Approach 1:
The patent implements dynamic grant allocation where the network device dynamically determines uplink grant parameters (time-frequency resources, modulation and coding scheme) based on real-time channel conditions and URLLC service requirements, rather than using fixed static grants. This dynamic adaptation reduces latency by allocating resources promptly based on actual needs while maintaining manageable complexity through automated base station control.
Solution Approach 2:
The system dynamically changes key transmission parameters including modulation order, coding rate, and resource block allocation based on measured channel quality indicators. This parameter adaptation maximizes spectrum efficiency by matching transmission characteristics to current channel conditions, while the automated parameter selection algorithms keep implementation complexity manageable.
3Productivity
If dynamic grant allocation is implemented, then spectrum efficiency improves, but system complexity increases
Solution Approach 1:
The patent creates a universal dynamic grant allocation framework that handles multiple URLLC service types, channel conditions, and resource scenarios through a single integrated system at the base station. This multi-functional approach improves spectrum efficiency across diverse situations while consolidating complexity management in the network device rather than distributing it across multiple specialized components.
Solution Approach 2:
The system implements self-service mechanisms where the base station autonomously monitors channel conditions, determines appropriate grant parameters, and allocates resources without requiring complex manual configuration or intervention. This automated self-management improves spectrum efficiency through real-time adaptation while keeping system complexity manageable by eliminating the need for complex external control mechanisms.
4Reliability
If conventional scheduling is used, then system simplicity is maintained, but URLLC service support capability deteriorates
Solution Approach 1:
The patent implements dynamic grant allocation where the network device dynamically determines uplink grant parameters (time-frequency resources, modulation and coding scheme) based on real-time channel conditions and URLLC service requirements, rather than using fixed static grants. This dynamic adaptation reduces latency by allocating resources promptly based on actual needs while maintaining manageable complexity through automated base station control.
Solution Approach 2:
The system dynamically changes key transmission parameters including modulation order, coding rate, and resource block allocation based on measured channel quality indicators. This parameter adaptation maximizes spectrum efficiency by matching transmission characteristics to current channel conditions, while the automated parameter selection algorithms keep implementation complexity manageable.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, receiving, from a user equipment (UE) device, a scheduling request for a configured grant operation during performance of an ultra-reliable low latency communications (URLLC) service at the UE device, determining radio channel characteristics of a radio channel of the UE device, and determining an appropriate modulation and coding scheme for a dynamic configured grant for the UE device, wherein the appropriate modulation and coding scheme is selected based on the radio channel characteristics. Aspects of the disclosure further include communicating information about the dynamic configured grant to the UE device, including communicating an assigned modulation and coding scheme to the UE device for use during performance of the URLLC service at the device, and suspending further scheduling requests for additional dynamic configured grants during completion of the URLLC service at the device. Other embodiments are disclosed.


