Knowledge-Aided Semantic Communication Leveraging Probabilistic Graphical Modeling
In this paper, we propose a semantic communication approach based on probabilistic graphical model (PGM). The proposed approach involves constructing a PGM from a training dataset, which is then shared as common knowledge between the transmitter and receiver. We evaluate the importance of various semantic features and present a PGM-based compression algorithm designed to eliminate predictable portions of semantic information. Furthermore, we introduce a technique to reconstruct the discarded semantic information at the receiver end, generating approximate results based on the PGM. Simulation results indicate a significant improvement in transmission efficiency over existing methods, while maintaining the quality of the transmitted images.
Code (0)
등록된 구현이 없습니다.
Tasks
Semantic CommunicationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Environment Semantics Aided Wireless Communications: A Case Study of mmWave Beam Prediction and Blockage Prediction
In this paper, we propose an environment semantics aided wireless communication framework to reduce the transmission latency and improve the transmission reliability, where semantic information is extracted from environm…
Beam Predictionfeature selectionPredictionRadar Aided 6G Beam Prediction: Deep Learning Algorithms and Real-World Demonstration
This paper presents the first machine learning based real-world demonstration for radar-aided beam prediction in a practical vehicular communication scenario. Leveraging radar sensory data at the communication terminals …
Beam PredictionManagementPredictionWireless Environment Information Sensing, Feature, Semantic, and Knowledge: Four Steps Towards 6G AI-Enabled Air Interface
The air interface technology plays a crucial role in optimizing the communication quality for users. To address the challenges brought by the radio channel variations to air interface design, this article proposes a fram…
Dimensionality ReductionPosition-Aided Semantic Communication for Efficient Image Transmission: Design, Implementation, and Experimental Results
Semantic communication, augmented by knowledge bases (KBs), offers substantial reductions in transmission overhead and resilience to errors. However, existing methods predominantly rely on end-to-end training to construc…
PositionSemantic CommunicationTransceiver Cooperative Learning-aided Semantic Communications Against Mismatched Background Knowledge Bases
Semantic communications learned on background knowledge bases (KBs) have been identified as a promising technology for communications between intelligent agents. Existing works assume that transceivers of semantic commun…
DecoderQuantizationSemantic Communication