Edit Content

NANCY project has received funding from the Smart Networks and Services Joint Undertaking (SNS JU) under the European Union’s Horizon Europe research and innovation programme under Grant Agreement No 101096456. 

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the SNS JU. Neither the European Union nor the granting authority can be held responsible for them.

Project Data

The Future of Communications: A Deep Dive into 6G and Semantic Communications

Posted by



Authors: Stylianos E. Trevlakis  

Nikolaos Pappas 

Alexandros-Apostolos A. Boulogeorgos 

Organization: InnoCube  

As we stand on the brink of a new era in wireless communications, the journey towards 6G has already begun. NANCY aims to shed light on the role of Semantic Communications (SemCom) in the beyond 5G era, and the challenges that may arise as we strive to meet the semantically enriched communication needs of the 2030s. 

The SemCom Vision 

At the heart of our vision for 6G is SemCom, a paradigm that goes beyond traditional point-to-point systems. SemCom focuses on extracting and filtering goal-specific semantic information at the source before transmitting signals, and decoding and post-processing semantics at the destination. This approach transforms the networking architecture into a multi-user distributed, edge-to-cloud network with deadline constraint traffic. 

Implementing such an architecture is complex. It requires frameworks for extracting and representing knowledge, theoretical models to predict and manage multiple time-varying deadline/delay constrained traffic flows, and innovative metrics infused with semantics to measure performance while encapsulating its inherent relevance. 

SemCom vs Conventional Communication Systems 

In conventional communication systems, the focus is on mitigating interference and ensuring robust performance. The semantic information carried by the messages is often overlooked. However, when we consider the semantic and effectiveness layers, the conventional communication system can be transformed into a SemCom system. 

In a SemCom system, the semantic transmitter and receiver perform additional intelligent operations that take into account the transmitted semantic information. The semantic encoder uses the source knowledge base to extract the necessary semantic information, which is then sent into the channel encoder for transmission through the wireless channel. At the destination, the received signal undergoes a semantic decoding operation and semantic inference to accomplish a desired action with respect to a communication objective or task. 

The Semantic Networking Architecture 

Building upon point-to-point SemCom systems, we introduce a semantic networking architecture that accounts for goal-specific semantic extraction and filtering at the source, as well as semantic decoding and post-processing at the destination. This architecture evolves the communication paradigm into a multiuser, distributed, deep-edge-to-cloud networking architecture with multiple traffic flows. 

The semantic source and destination are considered natively intelligent agents (human, software, or hardware) capable of environmental perception and autonomous operation to achieve certain goals. The source generates a message that is conveyed over the stochastic channel to the destination. With the help of SemCom, this procedure evolves into a more intelligent concept where the source is tasked to convey the gathered semantic information to the destination. 

Guidelines for Developing SemCom Approaches 

When developing SemCom approaches for point-to-point communication and networking, it’s important to create structured methods for exchanging information that carries rich semantic information. Here are some guidelines to consider: 

  • Clearly define the models used to encode and decode information. 
  • Establish proper semantic knowledge representation to ensure consistency across entities within the communication network. 
  • Integrate mechanisms for filtering to eliminate or minimize semantic noise. 
  • Incorporate redundancy in communication to enhance error detection and correction capabilities. 
  • Utilize existing standards and ontologies as a foundation to build upon established conventions. 
  • Consider the range of devices, platforms, and systems that may be involved in the network. 
  • Address security concerns related to coding by protecting against semantic attacks or unauthorized manipulation of semantic information. 
  • Design dynamic processes for coding that can adapt to changes in the communication environment over time. 
  • Implement context processing by considering the surrounding context of communication. 

As we move towards the integration of semantics in the forthcoming 6G wireless systems, these considerations will play a crucial role in shaping the future of communications. 



S. E. Trevlakis, N. Pappas and A. -A. A. Boulogeorgos, “Towards Natively Intelligent Semantic Communications and Networking,” in IEEE Open Journal of the Communications Society