Dynamic Buffer Size Signaling for Wireless Networks
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Solution Overview
Problem
Current buffer status report (BSR) tables in wireless communication networks are statically predefined, leading to quantization errors and inefficiencies in resource allocation, particularly for next-generation communication modes like extended reality (XR), which require different buffer size distributions, resulting in increased latency and decreased spectral efficiency.
Innovation Solution
A method involving the use of BSR quantization reference tables with offset equations to dynamically adjust buffer sizes based on traffic parameters, allowing for flexible and adaptive resource allocation without the need for extensive network signaling or memory storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If static BSR tables are used to reduce signaling overhead, then communication overhead is reduced, but quantization errors increase and spectral efficiency decreases
Solution Approach 1:
The patent transforms static BSR tables into dynamic tables that adapt to different traffic types. The network node configures multiple BSR tables corresponding to different traffic types (eMBB, URLLC, XR), and the appropriate table is selected based on the active traffic type. This dynamic adaptation reduces quantization errors while maintaining compact representation, resolving the contradiction between signaling overhead reduction and buffer size indication precision.
Solution Approach 2:
The patent changes the distribution parameters of buffer sizes in BSR tables to match different traffic characteristics. Each traffic type has optimized buffer size distributions (e.g., exponential for eMBB, uniform for XR), which minimizes quantization errors for that specific traffic type. This parameter optimization allows the system to maintain high precision with fewer table entries, reducing signaling overhead while improving spectral efficiency.
2Device complexity
If a single fixed BSR table distribution is used to cover all use cases, then device complexity is reduced, but quantization errors increase for specific traffic types
Solution Approach 1:
The patent segments the single BSR table into multiple traffic-type-specific tables. Each table is optimized for a specific traffic type (eMBB, URLLC, XR) with appropriate buffer size distributions. The network node configures multiple BSR tables corresponding to different traffic types, and the UE selects the appropriate table based on the active traffic type. This segmentation allows each table to be optimized for its specific traffic type, improving quantization accuracy without significantly increasing device complexity.
Solution Approach 2:
The patent creates a universal BSR table configuration mechanism that serves multiple traffic types. The network node configures multiple BSR tables that can be selectively applied based on traffic type, making the system universally applicable to different communication scenarios. This multi-functionality approach allows the system to maintain low device complexity while achieving high quantization accuracy for each specific traffic type through selective table usage.
3Adaptability or versatility
If dynamic signaling of entire BSR tables is used to adapt to different use cases, then adaptability improves, but network resource consumption increases
Solution Approach 1:
The patent extracts only the essential configuration parameters from full BSR tables and transmits them via compact RRC signaling. Instead of signaling entire tables, the network node transmits compact configurations including table size, buffer size values, and distribution type. This extraction approach maintains high adaptability for different traffic types while significantly reducing network resource consumption compared to transmitting complete tables.
Solution Approach 2:
The patent performs preliminary configuration of BSR tables through RRC signaling before actual data transmission. The network node pre-configures multiple BSR tables corresponding to different traffic types, and the UE stores these for later use. When a specific traffic type becomes active, the UE simply selects the pre-configured table without requiring additional signaling. This preliminary action reduces real-time network resource consumption while maintaining high adaptability.
Data Source
AI summary
Methods, apparatus and systems for signaling buffer sizes in a communication network are disclosed.