Data Transmission Using Variational Auto-Encoder Parameters
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Solution Overview
Problem
Existing data transmission methods in wireless communication systems require multiple data transmissions to improve precision, leading to high overheads due to the need for multiple samplings at the transmit end, which increases the data transmission amount and resource utilization.
Innovation Solution
A method where a receive end receives a parameter representing a probability distribution of a hidden variable, samples this distribution multiple times, and reconstructs the original data, reducing the need for multiple data transmissions by using the parameter to generate multiple samples in a single transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple times of sampling are performed at the transmit end to improve precision, then the precision of data reconstruction is improved, but the data transmission amount and overheads increase
Solution Approach 1:
The patent extracts only the essential parameters of the probability distribution (mean and variance) from the complete sampled data at the transmit end. Instead of transmitting all sampled data points, only these compact parameter representations are sent to the receive end, which can then regenerate the distribution and perform additional sampling locally to achieve high precision reconstruction with minimal transmission overhead.
Solution Approach 2:
The patent transforms the data representation from raw sampled values to probability distribution parameters (mean and variance). This parameter transformation enables the receive end to generate multiple samples from a compact parameter set, effectively achieving multiple times of sampling functionality without transmitting multiple complete data sets, thus resolving the contradiction between precision and transmission amount.
2Measurement precision
If multiple times of sampling are performed at the transmit end to improve precision, then the precision of data reconstruction is improved, but the transmission resources are consumed
Solution Approach 1:
The patent extracts only the essential parameters of the probability distribution (mean and variance) from the complete sampled data at the transmit end. Instead of transmitting all sampled data points, only these compact parameter representations are sent to the receive end, which can then regenerate the distribution and perform additional sampling locally to achieve high precision reconstruction with minimal transmission overhead.
Solution Approach 2:
The patent transforms the data representation from raw sampled values to probability distribution parameters (mean and variance). This parameter transformation enables the receive end to generate multiple samples from a compact parameter set, effectively achieving multiple times of sampling functionality without transmitting multiple complete data sets, thus resolving the contradiction between precision and transmission amount.
3Ease of operation
If complete data is transmitted directly from transmit end to receive end, then the data transmission is simple, but the transmission overheads are high when large amount of data needs to be transmitted
Solution Approach 1:
The patent extracts only the essential parameters of the probability distribution (mean and variance) from the complete sampled data at the transmit end. Instead of transmitting all sampled data points, only these compact parameter representations are sent to the receive end, which can then regenerate the distribution and perform additional sampling locally to achieve high precision reconstruction with minimal transmission overhead.
Solution Approach 2:
The patent transforms the data representation from raw sampled values to probability distribution parameters (mean and variance). This parameter transformation enables the receive end to generate multiple samples from a compact parameter set, effectively achieving multiple times of sampling functionality without transmitting multiple complete data sets, thus resolving the contradiction between precision and transmission amount.
Data Source
AI summary
A data transmission method and apparatus are described. The method includes a receive end receiving a first parameter, where the first parameter includes a parameter of a probability distribution of a hidden variable. The hidden variable is obtained by encoding first data by using an encoder of a variational auto-encoder. The receive end determines the probability distribution based on the first parameter, and samples the probability distribution M times to obtain M pieces of sampled data, where M is a positive integer. The receive end reconstructs the first data based on the M pieces of sampled data. According to the described data transmission method and apparatus, the first parameter is transmitted, so that the receive end can support a plurality of times of sampling, thereby reducing an amount of data transmitted over an air interface, and reducing data transmission overhead.