Quantum communication has reached a rate bottleneck, yet enhancing its throughput remains of profound significance. Here we propose a scheme termed quantum semantic communication-a novel paradigm that integrates semantic communication with quantum secure direct communication to realize highly efficient, task-oriented, and intrinsically secure information transmission. In quantum semantic communication, meaningful semantic content is directly encoded into quantum states, whereby the fundamental laws of quantum physics guarantee inherent eavesdropping-detection capability and information-theoretic security. By harnessing semantic compression and artificial intelligence-assisted encoding strategies, this approach surpasses the intrinsic rate constraints of conventional quantum secure direct communication. Simulation results show that quantum semantic communication can surpass the Wyner secure information bound compared with conventional quantum secure direct communication systems and demonstrate its potential to break through the linear distance bound of quantum communication. These findings pave the way for high-rate secure communication.
Quantum communication has reached a rate bottleneck, yet enhancing its throughput remains of profound significance. Here we propose a scheme termed quantum semantic communication-a novel paradigm that integrates semantic communication with quantum secure direct communication to realize highly efficient, task-oriented, and intrinsically secure information transmission. In quantum semantic communication, meaningful semantic content is directly encoded into quantum states, whereby the fundamental laws of quantum physics guarantee inherent eavesdropping-detection capability and information-theoretic security. By harnessing semantic compression and artificial intelligence-assisted encoding strategies, this approach surpasses the intrinsic rate constraints of conventional quantum secure direct communication. Simulation results show that quantum semantic communication can surpass the Wyner secure information bound compared with conventional quantum secure direct communication systems and demonstrate its potential to break through the linear distance bound of quantum communication. These findings pave the way for high-rate secure communication.
Quantum communication has reached a rate bottleneck, yet enhancing its throughput remains of profound significance. Here, we propose a scheme termed semantic quantum secure direct communication (QSDC), which is a novel paradigm integrating semantic communication with QSDC to realize highly efficient, task-oriented, and intrinsically secure information transmission. In semantic QSDC, meaningful semantic content is directly encoded into quantum states, whereby the fundamental laws of quantum physics guarantee inherent eavesdropping-detection capability and information-theoretic security. By harnessing semantic compression and artificial intelligence–assisted encoding strategies, this approach surpasses the intrinsic rate constraints of conventional QSDC. Simulation results show that semantic QSDC can surpass the Shannonian mutual information bound compared with conventional QSDC systems and demonstrate its potential to break through the linear rate-transmittance bound of quantum communication. These findings pave the way for high-rate secure communication.
Quantum Secure Direct Communication (QSDC), a paradigm-shifting breakthrough in quantum communication, exploits quantum states for unmediated information transmission. Rooted in the inviolable fundamental laws of quantum mechanics, QSDC enables ultrasensitive detection of even the faintest eavesdropping attempts, guaranteeing true communication security solely when no interference exists. If eavesdropping or intrusion is detected mid-transmission, the system instantly alerts users and severs data flow, shielding them from unauthorized tracking and mitigating hacker threats. Over two decades, QSDC has seen extraordinary advancements, currently attaining kilobit-per-second transmission over 100 km of commercial optical fiber. However, its practical scalability remains constrained by insufficient transmission rates, a critical bottleneck. Semantic communication, which drastically boosts transmission efficiency by extracting core information features, nevertheless stays vulnerable to malicious intrusions. Integrating these paradigms promises to simultaneously enhance equivalent data rate and security. Herein, we propose and experimentally validate a quantum semantic communication scheme, applying it to 3D point clouds. It achieves a 46.30-fold efficiency gain over direct transmission, surpassing both Wyner and Shannon capacity limits. This breakthrough not only clears the path for large-scale QSDC deployment but also marks a pivotal milestone in quantum information science.
This paper explores the integration of Quantum Communication Networks (QCNs), semantic communication, and covert communication within the context of 6G and future wireless networks. Introducing a new Quantum Semantic Communications (QSC) framework that capitalizes on advancements in quantum machine learning and semantic representations, this framework dramatically enhances resource efficiency in QCN s. It does so by embedding only relevant classical data into compact, high-dimensional quantum states for transmission, achieving a potential resource reduction of 50-75% while boosting quantum semantic fidelity. The paper further examines Artificial Intelligence's (AI) transformative role in upgrading tra-ditional communication paradigms into more efficient semantic communication systems, utilizing deep learning and end-to-end methodologies to ensure precise conveyance and interpretation of meanings in transmitted information. Additionally, it explores incorporating covert communication strategies within systems supported by a Reconfigurable Intelligent Surface (STAR-RIS) and Non-Orthogonal Multiple Access (NOMA), emphasizing the enhanced security and stealth necessary for modern networks. By merging these sophisticated communication strategies, the paper anticipates a new era of telecommunications that significantly surpasses existing security, efficiency, and semantic accuracy capabilities, marking a progressive step towards future networks optimized for secure, efficient, and meaning-focused communication in the quantum and AI era.
Semantic communications prioritize transmitting meaningful information over raw data in communication systems. However, these systems face significant optimization challenges, particularly concerning resource efficiency and fidelity due to the costly and delicate nature of photonic resources. Quantum computing offers promising solutions to these challenges through its unique capabilities, such as superposition and entanglement, within high-dimensional Hilbert spaces. This survey reviews the integration of quantum computing into semantic communications, tracing developments from foundational concepts to current advancements. It explores how quantum embeddings and machine learning techniques enhance semantic representation and transmission, enabling the encoding and processing of only relevant information. This approach addresses issues of polysemy and contextual variations in large datasets more effectively than classical methods. Key topics include the utilization of quantum probability and cognition in semantic analysis, optimization of quantum protocols for faster information retrieval, and the role of variational quantum circuits in improving computation latency, communication bandwidth, data privacy, and transmission delays. It also examines the implications for future communication systems like next-generation networks. It highlights the shift towards intelligent computing-intensive architectures and the support for advanced applications such as extended reality and holographic communications. Potential pathways are identified to achieve more efficient, secure, and intelligent data transmission, aiming to provide researchers and practitioners with a thorough understanding of this emerging field, outlining open research challenges and future directions to inspire further exploration and innovation.
This paper proposes a novel architecture for a distributed semantic network leveraging the unique properties of quantum entanglement. The core concept involves encoding semantic data into the entangled superposition states of multiple quantum bits (qubits) distributed across physically separated nodes. This approach aims to achieve ultra-high bandwidth and ultra-low latency data transmission and storage, overcoming the limitations of classical communication channels. Each node comprises a quantum processor and an entanglement generator. The distributed processing and storage of semantic data are then facilitated through the inherent correlations provided by quantum entanglement. This architecture represents a significant departure from conventional data networking paradigms and offers a pathway toward realizing fundamentally faster and more efficient distributed systems. The key elements of this system are the generation and distribution of highly entangled states and the subsequent manipulation of these states for data encoding and retrieval. This research explores the theoretical foundations and potential applications of this quantum-enhanced distributed semantic network.
This paper proposes a novel information encoding and decoding scheme leveraging the unique properties of quantum entanglement. The core concept involves utilizing multi-particle entangled states for superposition-based encoding and subsequent information recovery through measurement outcomes. Furthermore, the scheme incorporates entanglement-assisted eavesdropping detection and error correction mechanisms. The theoretical analysis demonstrates the potential to surpass the classical channel capacity limit, fundamentally altering the landscape of information transmission. The proposed approach explores the physical boundaries of information transfer, offering a new pathway for quantum communication protocols. The key mathematical elements underpinning the system are presented, including the quantum state description, measurement operators, and the relevant equations governing the process. The system's performance is evaluated through theoretical modeling, highlighting its advantages in terms of information rate and security.