Variable Autoencoder for Wireless Data Compression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Wireless data transmission systems face challenges in handling high bandwidth transmissions without causing latency and data inconsistency issues, especially in unstable and high interference network environments.
Innovation Solution
The method involves receiving data from a vehicle, extracting key frames, encoding them using a variable autoencoder to generate compressed data, transmitting this compressed data, and then reconstructing the data using a decoder to minimize bandwidth requirements and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high bandwidth data is transmitted wirelessly, then data transmission capacity is improved, but latency and data inconsistency issues worsen
Solution Approach 1:
The patent segments the data transmission process into two stages: local compression at the vehicle (using autoencoder) and subsequent transmission to the remote server. This segmentation allows high-bandwidth data to be processed locally before transmission, reducing the actual transmitted data volume and thereby reducing latency while maintaining transmission capacity.
Solution Approach 2:
The patent applies preliminary compression action at the vehicle before transmission to the remote server. The autoencoder compresses sensor data into latent space representations, so that when data is transmitted wirelessly, it is already compressed. This preliminary action reduces the transmission burden and minimizes latency during the actual wireless transmission phase.
2Speed
If data is transmitted in real-time, then responsiveness is improved, but data consistency and stability worsen in unstable networks
Solution Approach 1:
The patent creates a compressed copy of the data in latent space that preserves the essential information. The autoencoder learns to compress sensor data while maintaining the most important features, so that the compressed representation is a faithful copy that can be reconstructed later. This copying approach allows real-time transmission of reduced data while maintaining consistency through accurate reconstruction.
Solution Approach 2:
The patent changes the data representation parameters by transforming sensor data from the original high-dimensional space into a compressed latent space. This parameter transformation reduces data volume while preserving essential information, enabling real-time transmission that maintains data consistency even in unstable network conditions.
3Loss of time
If bandwidth is reduced to minimize latency, then transmission time is improved, but data quality and reconstruction accuracy worsen
Solution Approach 1:
The patent changes the representation parameters through the autoencoder's encoder and decoder networks. The encoder transforms data into a compressed latent space representation, and the decoder reconstructs it back to the original space. This parameter transformation achieves efficient compression that maintains high reconstruction accuracy, allowing reduced bandwidth transmission without sacrificing data quality.
Solution Approach 2:
The patent employs feedback mechanisms in the autoencoder architecture where the decoder tries to reconstruct the original data from the compressed latent representation. This feedback loop ensures that the compression process maintains sufficient accuracy, as the reconstruction quality is directly optimized during training. This feedback mechanism allows aggressive compression while preserving data quality.
Data Source
AI summary
A method for wireless data transmission and reconstruction includes receiving data from a vehicle, extracting key frames from the data, and encoding, using an encoder of a variable autoencoder, the key frames of the data into a latent space to generate compressed data. The method also includes transmitting the compressed data from the vehicle to a remote server. The method includes generating, using a decoder of the variable autoencoder, data points from the compressed data, where the data points are representative of the data received from the vehicle.