Positioning Report Compression for Low-Latency 5G Accuracy
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Solution Overview
Problem
Current positioning techniques in wireless networks face challenges in meeting the high accuracy and low latency requirements for 5G industrial use cases, such as logistics and autonomous vehicles, due to the need to balance report size and transmission latency, leading to inefficiencies in positioning report compression and decompression processes.
Innovation Solution
A training-based compression algorithm and decompression algorithm are jointly trained with a distance correction algorithm to generate and process compressed positioning reports, allowing for efficient data transmission while maintaining positioning accuracy, using neural networks and autoencoders to optimize code size and compression levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the positioning report size is increased to improve positioning accuracy, then positioning accuracy is improved, but transmission latency increases
Solution Approach 1:
The patent extracts and transmits only the most critical positioning measurement data in a compressed format, separating essential information from redundant data. This allows the positioning report to be sufficiently small for low-latency transmission while still containing enough information to achieve the required positioning accuracy through intelligent data selection and compression techniques.
Solution Approach 2:
The patent dynamically adjusts reporting parameters such as compression level, data granularity, and measurement frequency based on positioning accuracy requirements and network conditions. By changing these parameters adaptively, the system optimizes the balance between positioning accuracy and transmission latency, sending more detailed data only when high accuracy is required.
2Loss of time
If the positioning report is compressed to reduce transmission latency, then transmission latency is reduced, but positioning accuracy deteriorates
Solution Approach 1:
The patent introduces an intelligent compression algorithm as an intermediary between the positioning measurement process and data transmission. This intermediary selectively compresses data while preserving critical positioning information, using techniques such as differential encoding, predictive algorithms, and intelligent data filtering to maintain accuracy while reducing report size.
Solution Approach 2:
The patent performs preliminary processing and pre-compression of positioning data before transmission, preparing optimized data structures and predicting required precision levels in advance. This preliminary action allows the system to transmit compressed data that can be quickly decompressed and processed, reducing overall latency while maintaining accuracy.
3Measurement precision
If the positioning report is split into multiple messages to transmit large data, then positioning accuracy is maintained, but transmission latency increases
Solution Approach 1:
The patent segments positioning data into hierarchical groups based on importance and temporal relevance, transmitting critical data in priority segments while bundling less critical information. This intelligent segmentation allows partial processing of high-priority data to achieve positioning accuracy while reducing overall transmission time through prioritized delivery.
Data Source
AI summary
A positioning reports producer (101) comprising: —means for receiving one or more reference signals for positioning a target end device; —means for receiving a set of trained parameters defining a training-based compression algorithm, the set of trained parameters being obtained by a joint training of the training-based compression algorithm and one or more training-based algorithms implemented in a positioning reports consumer (102); —means for generating a compressed positioning report by running the training-based compression algorithm; and —means for sending the compressed positioning report to the positioning reports consumer (102).