One-to-Many Semantic Communication Systems: Design, Implementation, Performance Evaluation

Hu, Han; Zhu, Xiaolei; Zhou, Fuhui; Wu, Wei; Hu, Rose Qingyang; Zhu, Hongbo

doi:10.1109/lcomm.2022.3203984

Cited by 31 publications

(16 citation statements)

References 14 publications

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“…is observed that the performance and stability of all the semantic communication systems at low SNR are significantly better than those of the traditional communication systems. Moreover, it is clear that our proposed multi-user cognitive semantic communication achieve better performance than MR-DeepSC [33]. The reasons are as follows.…”

Section: Rxmentioning

confidence: 95%

“…Specifically, the DNN-based approaches, such as the joint source-channel coding (JSCC) approach [32] and the DeepSC approach [11], are compared with our proposed single-user cognitive semantic communication system. Besides, our proposed multi-user cognitive semantic communication system is compared with the MR-DeepSC approach [33]. Our proposed systems and other DNN-based benchmark systems are presented in Table VII.…”

Section: Performance Comparisonmentioning

confidence: 99%

“…On the one hand, the semantic correction algorithm is exploited to correct the semantic errors occurring at the transmission and improves the robustness of our proposed communication system. On the other hand, a semantic recognizer based on the DistilBERT is built to distinguish different users according to the different emotions [33]. Different users have their own private knowledge graphs.…”

Section: Rxmentioning

confidence: 99%

See 2 more Smart Citations

Cognitive Semantic Communication Systems Driven by Knowledge Graph: Principle, Implementation, and Performance Evaluation

Zhou¹,

Li²,

Xu³

et al. 2023

Preprint

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Semantic communication is envisioned as a promising technique to break through the Shannon limit.However, semantic inference and semantic error correction have not been well studied. Moreover, error correction methods of existing semantic communication frameworks are inexplicable and inflexible, which limits the achievable performance. In this paper, to tackle this issue, a knowledge graph is exploited to develop semantic communication systems. Two cognitive semantic communication frameworks are proposed for the single-user and multiple-user communication scenarios. Moreover, a simple, general, and interpretable semantic alignment algorithm for semantic information detection is proposed. Furthermore, an effective semantic correction algorithm is proposed by mining the inference rule from the knowledge graph. Additionally, the pre-trained model is fine-tuned to recover semantic information. For the multiuser cognitive semantic communication system, a message recovery algorithm is proposed to distinguish messages of different users by matching the knowledge level between the source and the destination.Extensive simulation results conducted on a public dataset demonstrate that our proposed single-user and multi-user cognitive semantic communication systems are superior to benchmark communication systems

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Section: Rxmentioning

confidence: 95%

Section: Performance Comparisonmentioning

confidence: 99%

Section: Rxmentioning

confidence: 99%

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Cognitive Semantic Communication Systems Driven by Knowledge Graph: Principle, Implementation, and Performance Evaluation

Zhou¹,

Li²,

Xu³

et al. 2023

Preprint

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“…In addition to the aforementioned wireless SemCom techniques, the rapidly evolving state-of-the-art research landscape of SemCom also encompasses numerous SemCom techniques and trends such as cognitive SemCom [122]; implicit SemCom [123]; adaptive SemCom [124]; contextbased SemCom [99], [125]; digital SemCom [126], [127]; SemCom with conceptual spaces [128]; inverse SemCom [129]; one-to-many SemCom [130]; cooperative SemCom [131]; strategic SemCom [132]; and encrypted SemCom [133]. These wireless SemCom techniques have also been corroborated to outperform traditional wireless communication techniques in low SNR regimes.…”

Section: A Wireless Semcommentioning

confidence: 99%

Making Sense of Meaning: A Survey on Metrics for Semantic and Goal-Oriented Communication

2023

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Semantic communication (SemCom) aims to convey the meaning behind a transmitted message by transmitting only semantically-relevant information. This semantic-centric design helps to minimize power usage, bandwidth consumption, and transmission delay. SemCom and goal-oriented SemCom (or effectiveness-level SemCom) are therefore promising enablers of 6G and developing rapidly. Despite the surge in their swift development, the design, analysis, optimization, and realization of robust and intelligent SemCom as well as goal-oriented SemCom are fraught with many fundamental challenges. One of the challenges is that the lack of unified/universal metrics of SemCom and goal-oriented SemCom can stifle research progress on their respective algorithmic, theoretical, and implementation frontiers. Consequently, this survey paper documents the existing metrics -scattered in many references -of wireless SemCom, optical SemCom, quantum SemCom, and goal-oriented wireless SemCom. By doing so, this paper aims to inspire the design, analysis, and optimization of a wide variety of SemCom and goal-oriented SemCom systems. This article also stimulates the development of unified/universal performance assessment metrics of SemCom and goal-oriented SemCom, as the existing metrics are purely statistical and hardly applicable to reasoning-type tasks that constitute the heart of 6G and beyond.

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“…Based on the findings of [19], an approximation of the semantic similarity curve was studied in [21] along with the utilization of DeepSC for NOMA-based systems, while in [22] a quality of experience (QoE) maximization problem was analyzed. Moreover, in [23], the design and use of a DeepSC-like DNN were examined for serving two users. In this case, the training loss function was modified to take into account both users.…”

Section: A Literature Reviewmentioning

confidence: 99%

Hybrid Semantic-Shannon Communications

Evgenidis¹,

Mitsiou²,

Tegos³

et al. 2023

Preprint

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<p>Recently, semantic communications have been considered as a promising beyond-Shannon paradigm to reduce network traffic and increase reliability, thus making wireless networks more energy efficient, robust, and sustainable. However, the performance is limited by the efficiency of the semantic transceivers, i.e., the achievable “similarity” between the transmitted and the received signal. If a strict similarity requirement holds, semantic transmission may not be applicable, thus Shannon communication is mandatory. In this paper, for the first time in the literature, we propose a multi-carrier Hybrid Semantic-Shannon communication system, where without loss of generality, the case of text transmission is investigated. To this end, a joint semantic-Shannon transmission selection and power allocation optimization problem is formulated, aiming to minimize the transmission delay, while it guarantees a strict similarity threshold. Despite its non-convexity, by utilizing alternating optimization the problem is separated into a convex and a mixed linear integer programming one, both of which can be optimally solved. Moreover, to improve the performance of the proposed hybrid scheme, a novel association of text sentences to subcarriers is proposed based on the sentence’s data size and subcarriers’ channel gains. We show that the proposed association is optimal in terms of transmission time delay. Numerical results and simulations verify the effectiveness of the proposed hybrid semantic-Shannon communication method and the derived sentence-to-subcarrier association, and provide useful insights on the designing parameters of such systems. </p>

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One-to-Many Semantic Communication Systems: Design, Implementation, Performance Evaluation

Cited by 31 publications

References 14 publications

Cognitive Semantic Communication Systems Driven by Knowledge Graph: Principle, Implementation, and Performance Evaluation

Cognitive Semantic Communication Systems Driven by Knowledge Graph: Principle, Implementation, and Performance Evaluation

Making Sense of Meaning: A Survey on Metrics for Semantic and Goal-Oriented Communication

Hybrid Semantic-Shannon Communications

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