Variable-Size Data Burst Resource Allocation in 5G NR
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Solution Overview
Problem
Current wireless network technologies face challenges in efficiently managing variable-size data bursts for extended reality (XR) traffic in 5G NR networks, particularly in reducing latency and improving spectral efficiency, due to limitations in dynamic resource allocation and over-provisioning methods.
Innovation Solution
The implementation of a new resource allocation method that uses statistical distribution functions to predict and adjust uplink and downlink data transmissions, allowing for variable periodicity and grant size configurations in Configured Grant (CG) and Semi-Persistent Scheduling (SPS) types, enabling deterministic resource allocation based on predicted traffic patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If dynamic resource allocation is used for variable-size data bursts, then adaptability to traffic patterns is improved, but latency increases and spectral efficiency deteriorates
Solution Approach 1:
The patent applies preliminary action by using statistical distribution functions to predict future traffic patterns and proactively allocating resources in advance. The system pre-determines resource allocation based on predicted data burst characteristics, eliminating the need for reactive dynamic allocation and reducing latency while maintaining adaptability.
Solution Approach 2:
The patent implements dynamics by enabling variable periodicity and grant size configurations in Configured Grant and Semi-Persistent Scheduling. The resource allocation parameters are made adaptable through statistical distribution functions that can model different traffic patterns, allowing the system to dynamically adjust to varying data burst sizes without incurring latency penalties.
2Reliability
If over-provisioning methods are used for resource allocation, then reliability of data transmission is improved, but spectral efficiency deteriorates
Solution Approach 1:
The patent applies parameter changes by using statistical distribution functions to accurately model and predict traffic patterns. This enables precise resource allocation that matches actual data burst characteristics, eliminating both over-provisioning and under-provisioning. The system adjusts allocation parameters based on predicted traffic statistics, maintaining reliability while optimizing spectral efficiency.
3Device complexity
If fixed resource allocation is used for configured grant, then device complexity is reduced, but adaptability to variable data burst sizes deteriorates
Solution Approach 1:
The patent implements dynamics in configured grant by enabling variable periodicity and grant size configurations. The system maintains the simplicity of configured grant while adding adaptability through statistical distribution function-based predictions, allowing the grant parameters to dynamically adjust to variable data burst sizes without increasing operational complexity.
Data Source
AI summary
The present application relates to devices and components including apparatus, systems, and methods for transmission of variable-size data bursts. Applications to uplink data transmissions and applications to downlink data transmissions are described.