Javad Gholipour | Searcharxiv

arXiv2026

Semantic Communication Through the Lens of Context-Dependent Channel Modeling

Semantic communication has emerged as a promising paradigm for next-generation networks, yet several fundamental challenges remain unresolved. Building on the probabilistic model of semantic communication and leveraging the concept of context, this paper examines a specific subclass of semantic communication problems, where semantic noise originates solely from the semantic channel, assuming an ideal physical channel. To model this system, we introduce a virtual state-dependent channel, where the state-representing context-plays a crucial role in shaping communication. We further analyze the representational capability of the semantic encoder and explore various semantic communication scenarios in the presence of semantic noise, deriving capacity results for some cases and achievable rates for others.

cs.IT↗

arXiv2025

Semantic Communication: From Philosophical Conceptions Towards a Mathematical Framework

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).

cs.IT↗