# 6G Networks: Beyond Shannon Towards Semantic and Goal-Oriented Communications

arXiv: https://arxiv.org/abs/2011.14844 · HTML: https://mlsanity.com/paper/2011.14844/

## Key facts

- Cited by 112 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Nov 2020.

## Built on by (most cited first, 30 of 112)

- [Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications](https://mlsanity.com/paper/2207.09353/) (2022)
- [Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications](https://mlsanity.com/paper/2111.12444/) (2021)
- [Semantic Communications: Principles and Challenges](https://mlsanity.com/paper/2201.01389/) (2021)
- [Less Data, More Knowledge: Building Next Generation Semantic Communication Networks](https://mlsanity.com/paper/2211.14343/) (2022)
- [Task-Oriented Communication for Multi-Device Cooperative Edge Inference](https://mlsanity.com/paper/2109.00172/) (2021)
- [Generative Semantic Communication: Diffusion Models Beyond Bit Recovery](https://mlsanity.com/paper/2306.04321/) (2023)
- [Task-Oriented Image Transmission for Scene Classification in Unmanned Aerial Systems](https://mlsanity.com/paper/2112.10948/) (2021)
- [Robust Information Bottleneck for Task-Oriented Communication with Digital Modulation](https://mlsanity.com/paper/2209.10382/) (2022)
- [Performance Optimization for Semantic Communications: An Attention-based Reinforcement Learning Approach](https://mlsanity.com/paper/2208.08239/) (2022)
- [Semantics-Native Communication with Contextual Reasoning](https://mlsanity.com/paper/2108.05681/) (2021)
- [Neuro-Symbolic Causal Reasoning Meets Signaling Game for Emergent Semantic Communications](https://mlsanity.com/paper/2210.12040/) (2022)
- [Learning Semantics: An Opportunity for Effective 6G Communications](https://mlsanity.com/paper/2110.08049/) (2021)
- [Task-Oriented Communications for NextG: End-to-End Deep Learning and AI Security Aspects](https://mlsanity.com/paper/2212.09668/) (2022)
- [Task-Oriented Feature Compression for Multimodal Understanding via Device-Edge Co-Inference](https://mlsanity.com/paper/2503.12926/) (2025)
- [Neuromorphic Wireless Cognition: Event-Driven Semantic Communications for Remote Inference](https://mlsanity.com/paper/2206.06047/) (2022)
- [Reinforcement Learning-powered Semantic Communication via Semantic Similarity](https://mlsanity.com/paper/2108.12121/) (2021)
- [Semantic Channel Equalizer: Modelling Language Mismatch in Multi-User Semantic Communications](https://mlsanity.com/paper/2308.03789/) (2023)
- [Curriculum Learning for Goal-Oriented Semantic Communications with a Common Language](https://mlsanity.com/paper/2204.10429/) (2022)
- [Task-Oriented Over-the-Air Computation for Multi-Device Edge AI](https://mlsanity.com/paper/2211.01255/) (2022)
- [Wireless End-to-End Image Transmission System using Semantic Communications](https://mlsanity.com/paper/2302.13721/) (2023)
- [Adaptive Semantic Token Communication for Transformer-based Edge Inference](https://mlsanity.com/paper/2505.17604/) (2025)
- [Task-Oriented Communication for Edge Video Analytics](https://mlsanity.com/paper/2211.14049/) (2022)
- [Common Language for Goal-Oriented Semantic Communications: A Curriculum Learning Framework](https://mlsanity.com/paper/2111.08051/) (2021)
- [Cognitive Semantic Communication Systems Driven by Knowledge Graph](https://mlsanity.com/paper/2202.11958/) (2022)
- [Semantic Information Recovery in Wireless Networks](https://mlsanity.com/paper/2204.13366/) (2022)
- [Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/2205.03793/) (2022)
- [Dynamic Relative Representations for Goal-Oriented Semantic Communications](https://mlsanity.com/paper/2403.16986/) (2024)
- [Advanced Architectures Integrated with Agentic AI for Next-Generation Wireless Networks](https://mlsanity.com/paper/2502.01089/) (2025)
- [Neuro-Symbolic Artificial Intelligence (AI) for Intent based Semantic Communication](https://mlsanity.com/paper/2205.10768/) (2022)
- [Towards Semantic Communication Protocols: A Probabilistic Logic Perspective](https://mlsanity.com/paper/2207.03920/) (2022)

## Abstract (arXiv)

The goal of this paper is to promote the idea that including semantic and goal-oriented aspects in future 6G networks can produce a significant leap forward in terms of system effectiveness and sustainability. Semantic communication goes beyond the common Shannon paradigm of guaranteeing the correct reception of each single transmitted packet, irrespective of the meaning conveyed by the packet. The idea is that, whenever communication occurs to convey meaning or to accomplish a goal, what really matters is the impact that the correct reception/interpretation of a packet is going to have on the goal accomplishment. Focusing on semantic and goal-oriented aspects, and possibly combining them, helps to identify the relevant information, i.e. the information strictly necessary to recover the meaning intended by the transmitter or to accomplish a goal. Combining knowledge representation and reasoning tools with machine learning algorithms paves the way to build semantic learning strategies enabling current machine learning algorithms to achieve better interpretation capabilities and contrast adversarial attacks. 6G semantic networks can bring semantic learning mechanisms at the edge of the network and, at the same time, semantic learning can help 6G networks to improve their efficiency and sustainability.