Buffer Size Tables for High Throughput Wireless
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Solution Overview
Problem
Current buffer size reporting in 5G wireless communication systems, such as 5G NR, results in large step sizes between encoding points, leading to inefficient resource utilization and increased padding of transport blocks, particularly for high data throughput applications like extended reality (XR), which can waste radio resources and increase power consumption.
Innovation Solution
Introducing new buffer size tables with reduced step sizes for larger values of k, allowing for more precise indication of buffer sizes through unique logical channel identifiers (LCIDs), enabling the network to accurately reflect larger buffer sizes and reduce resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard buffer size tables are used in 5G NR, then device complexity is reduced and ease of operation is maintained, but measurement precision of buffer sizes deteriorates due to large step sizes between encoding points
Solution Approach 1:
The patent divides the buffer size reporting into multiple separate buffer size tables, each optimized for specific buffer size ranges. Instead of using a single standard table with large step sizes, the system segments the reporting into tables with different granularities - finer step sizes for smaller buffers and coarser step sizes for larger buffers, thereby improving measurement precision without uniformly increasing complexity across all ranges.
Solution Approach 2:
The patent applies different step sizes locally to different buffer size ranges. Each buffer size table is configured with step sizes appropriate for its specific range, allowing fine-grained precision where needed (smaller buffers) and coarser granularity where acceptable (larger buffers). This local optimization improves overall measurement precision while managing device complexity through selective application.
2Productivity
If larger step sizes are used in buffer size encoding, then device complexity is reduced and processing is simplified, but resource utilization efficiency deteriorates due to increased padding of transport blocks
Solution Approach 1:
The patent makes the buffer size table configuration dynamic by allowing the network to configure different tables with varying step sizes based on application requirements. For high data throughput applications like XR, the system can dynamically select or configure tables with smaller step sizes to improve resource utilization efficiency, while for other applications, larger step sizes can be used to maintain simplicity.
Solution Approach 2:
The patent changes the parameters of the buffer size tables, specifically the step sizes between encoding points, to optimize for different scenarios. By adjusting these parameters, the system can achieve better resource utilization efficiency when needed without permanently increasing device complexity, as the parameter changes are applied selectively based on traffic characteristics.
3Use of energy by moving object
If standard buffer size tables with larger step sizes are used, then processing speed is maintained and device complexity is low, but energy consumption increases due to increased padding and retransmissions
Solution Approach 1:
The patent performs preliminary configuration of buffer size tables with appropriate step sizes before actual data transmission. By pre-configuring tables optimized for specific application types (e.g., XR applications with smaller step sizes), the system avoids the need for increased padding and retransmissions during operation, thereby reducing power consumption without adding runtime complexity.
Data Source
AI summary
Aspects described herein relate to encoding a buffer size in a buffer status report based on a newly defined buffer size table that can have reduced step sizes for larger buffer sizes. Other aspects relate to decoding the buffer size in the buffer status report. The newly defined buffer size table can better accommodate buffer size reporting for high data throughput applications.