标题： 语义通信：从哲学概念到数学框架 显示英文标题

标题： Semantic Communication: From Philosophical Conceptions Towards a Mathematical Framework

摘要： 语义通信作为一种有望解决下一代通信网络挑战的范式已经出现。尽管在这方面取得了一些概念上的进展，但仍有一些基本问题尚未得到解决。本文中，我们提出了一种概率模型来描述语义通信，与之前主要基于人类语言直觉的工作不同，该模型以严谨的哲学信息观及其与数据作为约束潜能的关系为基础，并通过抽象层次（LoA）进行中介。这一基础不仅能够建模语言学中的语义通信，还提供了独立于领域的语义内容定义，从而将其应用范围扩展到超出语言学背景。由于语义通信问题涉及各种因素的复杂相互作用，使得很难全面解决，我们建议通过将其分类为更简单的子问题来使其正交化，并逐步接近一般问题。值得注意的是，我们展示了香农框架构成了语义通信的一个特例，在其中每条消息传达单一且无歧义的意义。因此，在这种受限场景下，香农模型中定义的容量——即可靠传输消息的最大速率——与语义容量相一致。在本文中，我们特别关注一个子问题，即语义歧义仅由物理信道噪声引起，并推导出其语义容量的下限，在相应的特例中该下限退化为香农容量。我们还证明了可实现的所有可传输消息的可靠语义通信速率超过了香农容量，增加了H(X|S)这一项。 显示英文摘要

摘要： Semantic communication has emerged as a promising paradigm to address the challenges of next-generation communication networks. While some progress has been made in its conceptualization, fundamental questions remain unresolved. In this paper, we propose a probabilistic model for semantic communication that, unlike prior works primarily rooted in intuitions from human language, is grounded in a rigorous philosophical conception of information and its relationship with data as Constraining Affordances, mediated by Levels of Abstraction (LoA). This foundation not only enables the modeling of linguistic semantic communication but also provides a domain-independent definition of semantic content, extending its applicability beyond linguistic contexts. As the semantic communication problem involves a complex interplay of various factors, making it difficult to tackle in its entirety, we propose to orthogonalize it by classifying it into simpler sub-problems and approach the general problem step by step. Notably, we show that Shannon's framework constitutes a special case of semantic communication, in which each message conveys a single, unambiguous meaning. Consequently, the capacity in Shannon's model-defined as the maximum rate of reliably transmissible messages-coincides with the semantic capacity under this constrained scenario. In this paper, we specifically focus on the sub-problem where semantic ambiguity arises solely from physical channel noise and derive a lower bound for its semantic capacity, which reduces to Shannon's capacity in the corresponding special case. We also demonstrate that the achievable rate of all transmissible messages for reliable semantic communication, exceeds Shannon's capacity by the added term H(X|S).