Goal-Oriented Semantic Communications for 6G Networks
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Abstract (arXiv)
Upon the arrival of emerging devices, including Extended Reality (XR) and Unmanned Aerial Vehicles (UAVs), the traditional communication framework is approaching Shannon's physical capacity limit and fails to guarantee the massive amount of transmission within latency requirements. By jointly exploiting the context of data and its importance to the task, an emerging communication paradigm shift to semantic level and effectiveness level is envisioned to be a key revolution in Sixth Generation (6G) networks. However, an explicit and systematic communication framework incorporating both semantic level and effectiveness level has not been proposed yet. In this article, we propose a generic goal-oriented semantic communication framework for various tasks with diverse data types, which incorporates both semantic level information and effectiveness-aware performance metrics. We first analyze the unique characteristics of all data types, and summarise the semantic information, along with corresponding extraction methods. We then propose a detailed goal-oriented semantic communication framework for different time-critical and non-critical tasks. In the goal-oriented semantic communication framework, we present the goal-oriented semantic information, extraction methods, recovery methods, and effectiveness-aware performance metrics. Last but not least, we present a goal-oriented semantic communication framework tailored for Unmanned Aerial Vehicle (UAV) control task to validate the effectiveness of the proposed goal-oriented semantic communication framework.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Oct 2022.
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Citing papers per year: 2024: 3; 2025: 3; 2026: 1.
7 papers.
- 2025The Larger the Merrier? Efficient Large AI Model Inference in Wireless Edge Networkscited by 6
- 2024Goal-Oriented Semantic Communication for Wireless Image Transmission via Stable Diffusioncited by 3
- 2024Goal-Oriented Semantic Communication for Wireless Visual Question Answeringcited by 3
- 2024Low-Latency Task-Oriented Communications with Multi-Round, Multi-Task Deep Learningcited by 2
- 2025Robust and Efficient Communication in Multi-Agent Reinforcement Learningcited by 2
- 2026Quantization-Aware Collaborative Inference for Large Embodied AI Modelscited by 1
- 2025Goal-Oriented Multi-Agent Semantic Networking: Unifying Intents, Semantics, and Intelligencecited by 0
- 2026Quantization-Aware Collaborative Inference for Large Embodied AI Models13 Feb 2026
- 2025Goal-Oriented Multi-Agent Semantic Networking: Unifying Intents, Semantics, and Intelligence30 Nov 2025
- 2025Robust and Efficient Communication in Multi-Agent Reinforcement Learning14 Nov 2025
- 2025The Larger the Merrier? Efficient Large AI Model Inference in Wireless Edge Networks14 May 2025
- 2024Low-Latency Task-Oriented Communications with Multi-Round, Multi-Task Deep Learning15 Nov 2024
- 2024Goal-Oriented Semantic Communication for Wireless Visual Question Answering3 Nov 2024
- 2024Goal-Oriented Semantic Communication for Wireless Image Transmission via Stable Diffusion1 Aug 2024