Semantic Signal Generation for Low-Latency Wireless Communication
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Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently transmitting and receiving signals between semantic layers in a source and destination, particularly in tasks requiring high reliability and low latency, and there is a need for methods to update background knowledge and learning information to enhance communication capabilities.
Innovation Solution
The proposed solution involves generating and transmitting semantic communication signals using contrastive learning, where devices exchange capability information and semantic communication-related information to update shared knowledge, utilizing a transceiver and processor to generate and receive these signals, and employing a transform head with dense layers and non-linear functions for fine-tuning and transfer-learning operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional wireless communication systems are used for transmitting signals between semantic layers, then basic communication functionality is maintained, but communication reliability and latency performance are insufficient for high-reliability and low-latency tasks
Solution Approach 1:
The patent changes the fundamental parameters of communication by introducing semantic source coding that operates at the semantic layer rather than traditional data layers. This involves transforming communication from raw bit transmission to meaning-based transmission, where the source device generates semantic representations and the destination device performs downstream tasks directly on these representations, thereby achieving both high reliability and efficiency
Solution Approach 2:
The patent introduces semantic representations as an intermediary between the source and destination devices. Instead of directly transmitting raw data, the system uses semantic source coding to create intermediate representations that carry meaningful information, allowing the destination to perform tasks more efficiently while maintaining communication reliability
2Productivity
If devices transmit and receive semantic communication signals using contrastive learning and transform heads with dense layers, then task-oriented communication performance is improved, but device complexity increases
Solution Approach 1:
The patent segments the communication system into distinct functional components: capability information exchange modules, semantic source coding modules, transform head modules with dense layers, and downstream task execution modules. This segmentation allows each component to be optimized independently while working together to achieve task-oriented communication efficiency
Solution Approach 2:
The patent implements preliminary actions through capability information exchange before actual communication begins. Devices first exchange capability information to determine suitable encoding and decoding parameters, then use contrastive learning to pre-process and optimize semantic representations before transmission, reducing the complexity of real-time processing
3Adaptability or versatility
If devices exchange capability information and update background knowledge through semantic communication, then adaptability to different communication scenarios is improved, but information processing time increases
Solution Approach 1:
The patent implements feedback mechanisms where destination devices send capability information back to source devices, and where semantic representations are updated based on downstream task performance. This feedback loop allows continuous adaptation to different communication scenarios while minimizing time loss through efficient iterative updates of background knowledge
Solution Approach 2:
The patent introduces dynamic adaptability by allowing devices to adjust their semantic coding parameters and background knowledge based on real-time capability information exchange. The system can dynamically switch between different encoding strategies and update knowledge bases adaptively, balancing the trade-off between versatility and processing time
Data Source
AI summary
The present disclosure may provide a method for operating a first device in a wireless communication system. The method may include receiving, by the first device, a capability information request for the first device from a second device, transmitting capability information of the first device to the second device, in case that the first device being a device equipped with a semantic communication capability based on the capability information of the first device, receiving semantic communication-related information from the second device, generating a semantic communication signal based on the semantic communication-related information, and transmitting the semantic communication signal to the second device. Herein, the semantic communication signal is related to share information, and an update of the share information may be performed based on an operation of a downstream task performed in the second device.