Uplink Resource Allocation via UE Payload Pattern Reporting
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Solution Overview
Problem
Current wireless communication systems, particularly in 5G NR, face challenges in efficiently allocating uplink resources, leading to increased latency, overhead, and power consumption.
Innovation Solution
The proposed solution involves a method where user equipment (UE) provides network nodes with information about aggregation capabilities and payload pattern information for multiple uplink data flows, enabling the network to make informed decisions for resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional dynamic grant mechanisms are used for uplink resource allocation, then the network can allocate resources based on real-time needs, but latency increases and overhead is maximized
Solution Approach 1:
The patent applies preliminary action by having the UE report aggregation capability and payload pattern information to the network node in advance, enabling the network to pre-configure resource allocation parameters. This allows the network to make informed scheduling decisions without waiting for real-time requests, thereby reducing latency while maintaining efficient resource management.
2Manufacturing precision
If detailed payload pattern information is collected from UE, then resource allocation accuracy improves, but overhead increases
Solution Approach 1:
The patent applies parameter changes by transforming detailed payload pattern information into aggregated statistical parameters (such as average payload size, payload variability, and periodicity) that the network can use for resource allocation. This approach maintains allocation accuracy while significantly reducing the overhead of transmitting and processing detailed payload information from the UE.
3Productivity
If uplink resources are allocated without UE capability information, then allocation process is simpler, but resource utilization efficiency decreases
Solution Approach 1:
The patent applies self-service by having the UE autonomously report its aggregation capability and payload pattern information to the network node. This enables the network to optimize resource allocation based on actual UE characteristics without requiring complex external configuration or manual setup, thereby improving resource utilization efficiency while keeping the implementation practical.
Data Source
AI summary
A UE transmits information to a network node indicating at least one of an aggregation capability or payload pattern information for multiple uplink data flows of the UE and receives a grant of uplink resources for the multiple uplink data flows based on the information transmitted to the network node. A network node obtains information from a UE, the information indicating at least one of an aggregation capability or payload pattern information for multiple uplink data flows of the UE; and provides a grant of uplink resources for the multiple uplink data flows based on the information transmitted to the network node.