Transform-Base Data Compression for Wireless Transmission Overhead
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Solution Overview
Problem
In next-generation wireless communication systems, the direct processing and transmission of data oriented to new scenarios, such as imaging and AI data, leads to excessive occupation of channel resources, necessitating a reduction in transmission overheads.
Innovation Solution
A unified compression framework based on transform bases is employed to compress data flexibly according to its type, using preconfigured or real-time determined transform base indication information to enhance compression efficiency and reduce data transmission overheads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data oriented to new scenarios is directly processed and transmitted, then transmission reliability is maintained, but channel resource occupation increases excessively
Solution Approach 1:
The patent extracts only the essential features and characteristics of the data oriented to new scenarios, transforming them into a condensed representation that retains transmission reliability while significantly reducing channel resource occupation. The extraction process identifies key data elements that maintain functionality while removing redundant information.
Solution Approach 2:
The patent applies parameter changes by transforming the data into a different representation format with altered characteristics. The transformation changes the data structure and parameters to achieve more efficient channel resource utilization while preserving the essential information needed for reliable transmission.
2Quantity of substance
If data compression is applied to reduce transmission overheads, then channel resource occupation decreases, but compression performance and data quality may deteriorate
Solution Approach 1:
The patent applies local quality by applying different compression strategies and transformation methods to different parts or types of data oriented to new scenarios. Each data component receives a tailored compression approach that maintains its specific quality requirements while achieving overall transmission overhead reduction.
Solution Approach 2:
The patent implements dynamic compression performance adjustment by adapting the compression level and method based on the specific characteristics of each data type. The system dynamically selects transformation parameters to maintain compression performance within acceptable ranges while optimizing transmission efficiency.
3Device complexity
If a unified compression framework is applied to all data types, then device complexity is reduced, but adaptability to different data types decreases
Solution Approach 1:
The patent implements a unified compression framework with multi-functionality that can handle various data types oriented to new scenarios through a single transformation process. The universal framework incorporates adaptive mechanisms that automatically adjust to different data characteristics, providing both simplicity and versatility.
Solution Approach 2:
The patent segments the unified compression framework into modular components that can independently process different data types. This segmentation allows the framework to maintain overall simplicity while adapting to specific data type requirements through configurable processing stages.
Data Source
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AI summary
A communication method and apparatus are provided. The method includes: obtaining to-be-compressed data, where the to-be-compressed data includes first data; determining at least one first transform base based on a first data type of the first data; determining second data based on the at least one first transform base and the first data; and sending the second data to a first device. According to the method provided in this application, a unified compression framework based on a transform base is proposed for the to-be-compressed data. At least one first transform base can be flexibly determined based on a data type of the first data, so that the first data is compressed based on the at least one first transform base. This ensures compression performance, enhances compression efficiency, and reduces data transmission overheads.