Rateless JSCC Packet Scheduling for Stable Semantic Radio Links

The patent merges source encoding and channel encoding functions into a unified joint source and channel coding (JSCC) framework. By training encoder and decoder neural networks jointly to minimize end-to-end semantic loss, the system achieves optimized data transfer effectiveness while managing implementation complexity through integrated architecture design.

The patent creates a universal JSCC framework that can handle multiple communication scenarios and semantic applications through a single integrated system. The neural network-based encoder-decoder pair is designed to be application-agnostic, working effectively for video streaming, robotic control, and other semantic communication tasks without requiring separate specialized systems.

The patent implements dynamic packet length adaptation through rateless coding, where the encoder can generate variable-length coded packets based on channel conditions and network requirements. The system dynamically adjusts the amount of coded data transmitted while maintaining stable QoS through the neural network decoder's ability to handle variable input lengths and reconstruct semantic information effectively.

The patent changes the packet length parameter dynamically while maintaining QoS stability through the rateless coding framework. By allowing the coded packet length to vary according to channel conditions and semantic importance, the system optimizes resource utilization while the trained neural networks ensure reliable reconstruction across different packet lengths.

The patent combines separate source encoding and channel encoding functions into a unified JSCC system. The neural network encoder simultaneously performs source compression and channel coding, while the decoder jointly performs channel decoding and source reconstruction, achieving improved data transfer efficiency through optimized end-to-end semantic communication.

The patent creates multi-functional neural network components that perform both source and channel coding functions within a single framework. The encoder network handles both compression and error protection, while the decoder network performs both error correction and reconstruction, simplifying the overall system architecture while improving efficiency.