Codebook-Based Data Transmission for Low-Overhead Communication
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Solution Overview
Problem
The increasing number of terminal devices and the integration of artificial intelligence in communication systems lead to high data transmission overheads, which existing technologies have not effectively addressed.
Innovation Solution
A data transmission method that involves encoding data using a first encoding network and a data codebook, where the apparatus determines an index of the data and sends information about this index, reducing data transmission overheads by processing the index through information protection and channel codebooks for error correction and efficient communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is transmitted directly without encoding, then transmission simplicity is maintained, but data transmission overheads increase
Solution Approach 1:
The patent extracts the essential information from the original data by encoding it into a compact representation. The encoding network processes the input data to generate a compressed encoded form that retains the critical information while removing redundant elements, thereby reducing transmission overhead without requiring transmission of the complete original data set
Solution Approach 2:
The patent transforms the data from its original parameter representation into an encoded parameter space. By changing the representation parameters through the encoding network and data codebook, the data is converted into a more efficient format for transmission, reducing the quantity of data that needs to be transmitted while preserving the essential information content
2Quantity of substance
If data is compressed to reduce transmission overheads, then transmission efficiency improves, but data accuracy deteriorates
Solution Approach 1:
The patent implements a feedback mechanism through the use of a data codebook that stores reference encoded data. The encoding process compares the encoded data against the codebook entries and selects the closest match, ensuring that the compressed representation maintains high fidelity to the original data. This feedback loop preserves data accuracy while achieving compression
Solution Approach 2:
The patent prepares the data compression process in advance by training the encoding network and populating the data codebook with representative encoded data patterns. This preliminary preparation ensures that when actual data compression occurs, the system has pre-established reference points and optimized encoding parameters that cushion against potential accuracy loss during the compression process
3Reliability
If traditional encoding methods are used, then implementation simplicity is maintained, but anti-noise performance deteriorates
Solution Approach 1:
The patent combines multiple protective mechanisms into a composite information protection system. The encoded data undergoes both encoding network transformation and data codebook mapping, creating a multi-layered protection structure that enhances anti-noise performance. This composite approach integrates different protection techniques to achieve superior reliability compared to single-method encoding
Solution Approach 2:
The patent performs information protection actions in advance by pre-training the encoding network and pre-populating the data codebook with robust reference patterns. This preliminary preparation ensures that the encoded data structure is inherently more resistant to noise before transmission occurs, rather than attempting to correct errors after they occur during transmission
Data Source
AI summary
A first apparatus obtains data; determines an index of the data based on a first encoding network and a first data codebook, where the first encoding network is for encoding the data, and the first data codebook includes a correspondence between encoded data and the index; and sends information about the index of the data.