A Survey on Semantic Communications for Intelligent Wireless Networks

Iyer, Sridhar; Khanai, Rajashri; Torse, Dattaprasad A.; Pandya, Rahul Jashvantbhai; Rabie, Khaled M.; Pai, Krishna; Khan, Wali Ullah; Fadlullah, Zubair Md.

doi:10.1007/s11277-022-10111-7

Cited by 22 publications

(8 citation statements)

References 96 publications

(122 reference statements)

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“…Different semantic communication strategies have been proposed to enhance the reliability of communication systems [19]. The work of [9]- [11] studied semantic communication systems in P2P scenarios with text applications.…”

Section: B Related Workmentioning

confidence: 99%

Cooperative Semantic Communication With On-Demand Semantic Forwarding

Tang,

Huang,

et al. 2024

IEEE Open J. Commun. Soc.

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In this paper, a deep learning-based cooperative semantic communication system is proposed on relay channels. In order to enhance the reliability and adaptability of the system to varying channel conditions, an on-demand semantic forwarding framework is established, where the relay attempts to recover and re-transmit the source semantic information, as required by the destination. To be specific, for determining whether a semantic forwarding is needed from the relay, a semantic similarity check (SSC) is proposed, based on which the degree of semantic information recovery at the destination can be accurately estimated. On the other hand, in order to effectively merge the semantic information received through different paths, a semantic combining (SeC) method is proposed by combining the semantic features abstracted from both the direct link and the relay link. For achieving a desirable performance trade-off between the degree of semantic information recovery and the transmit energy consumption, a new metric of semantic energy efficiency (SEE) is proposed. Simulation results verify the performance gains achieved by the proposed cooperative semantic communication system with on-demand semantic forwarding, as compared to the state-of-the-art schemes employing separate source-channel coding in low-to-medium signal-to-noise ratio (SNR) regimes. Furthermore, as compared to the case with alwaysforwarding, almost the same performance is achieved by the proposed on-demand forwarding, but with energy consumption.

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Section: B Related Workmentioning

confidence: 99%

Cooperative Semantic Communication With On-Demand Semantic Forwarding

Tang,

Huang,

et al. 2024

IEEE Open J. Commun. Soc.

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“…On the one hand, the semantic connotation is elusive to define and quantify. On the other hand, the generation mechanisms and processes of semantics remain obscure [3,8,16]. In this section, we introduce the essence of semantics and examine various definitions of semantic entropy.…”

Section: Semantic Entropymentioning

confidence: 99%

Semantic Communication: A Survey of Its Theoretical Development

Xin,

Fan,

Letaief

2024

Entropy

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In recent years, semantic communication has received significant attention from both academia and industry, driven by the growing demands for ultra-low latency and high-throughput capabilities in emerging intelligent services. Nonetheless, a comprehensive and effective theoretical framework for semantic communication has yet to be established. In particular, finding the fundamental limits of semantic communication, exploring the capabilities of semantic-aware networks, or utilizing theoretical guidance for deep learning in semantic communication are very important yet still unresolved issues. In general, the mathematical theory of semantic communication and the mathematical representation of semantics are referred to as semantic information theory. In this paper, we introduce the pertinent advancements in semantic information theory. Grounded in the foundational work of Claude Shannon, we present the latest developments in semantic entropy, semantic rate-distortion, and semantic channel capacity. Additionally, we analyze some open problems in semantic information measurement and semantic coding, providing a theoretical basis for the design of a semantic communication system. Furthermore, we carefully review several mathematical theories and tools and evaluate their applicability in the context of semantic communication. Finally, we shed light on the challenges encountered in both semantic communication and semantic information theory.

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“…The authors of [28] discuss cross-layer interaction, goaloriented communication applications, and semantic communications trends. This article highlights challenges and potential solutions for practical implementation in 6G wireless technology.…”

Section: B Related Workmentioning

confidence: 99%

Toward Natively Intelligent Semantic Communications and Networking

Trevlakis,

Pappas,

Boulogeorgos

2024

IEEE Open J. Commun. Soc.

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As the process of envisioning, researching, and strategizing for 6G communications has commenced, we present our vision on the role of semantic communications (SemCom) in the beyond 5G era. In the following discourse, we delve into the factors that may impede the progress of research and implementation of 6G with the objective of catering to the semantically enriched communication requirements of the 2030s. In addition, we proceed to establish the fundamental attributes of SemCom and engage in an examination of the requisite technological modalities. In order to bolster this overarching vision, we introduce a semantic networking architecture that encapsulates and characterizes various application scenarios of SemCom. Expanding on the concept of point-to-point SemCom systems the semantic networking architecture focuses on extracting and filtering goal specific semantic information at the source before transmitting signals. It also involves decoding and post processing semantics at the destination. What sets this networking architecture apart is its transformation into a multi-user distributed, edge-to-cloud network with deadline constraint traffic. Given its complexity, implementing such an architecture necessitates frameworks for extracting and representing knowledge theoretical models to predict and manage multiple time varying deadline/delay constrained traffic flows that may cause significant congestion in the network as well, as innovative metrics infused with semantics to measure performance while encapsulating its inherent relevance. Finally, we provide research considerations and future directions towards the integration of semantics in the forthcoming 6G wireless systems.

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A Survey on Semantic Communications for Intelligent Wireless Networks

Cited by 22 publications

References 96 publications

Cooperative Semantic Communication With On-Demand Semantic Forwarding

Cooperative Semantic Communication With On-Demand Semantic Forwarding

Semantic Communication: A Survey of Its Theoretical Development

Toward Natively Intelligent Semantic Communications and Networking

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