# Semantic Communications in Networked Systems: A Data Significance Perspective

arXiv: https://arxiv.org/abs/2103.05391 · HTML: https://mlsanity.com/paper/2103.05391/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Mar 2021.

## Built on by (most cited first, 24 of 24)

- [Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications](https://mlsanity.com/paper/2207.09353/) (2022)
- [Less Data, More Knowledge: Building Next Generation Semantic Communication Networks](https://mlsanity.com/paper/2211.14343/) (2022)
- [Joint Source-Channel Coding: Fundamentals and Recent Progress in Practical Designs](https://mlsanity.com/paper/2409.17557/) (2024)
- [Performance Optimization for Semantic Communications: An Attention-based Reinforcement Learning Approach](https://mlsanity.com/paper/2208.08239/) (2022)
- [Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach](https://mlsanity.com/paper/2304.12502/) (2023)
- [Semantic Information Recovery in Wireless Networks](https://mlsanity.com/paper/2204.13366/) (2022)
- [Semantics-Empowered Communication: A Tutorial-cum-Survey](https://mlsanity.com/paper/2212.08487/) (2022)
- [Deep Learning for Wireless Networked Systems: a joint Estimation-Control-Scheduling Approach](https://mlsanity.com/paper/2210.00673/) (2022)
- [Agent-driven Generative Semantic Communication with Cross-Modality and Prediction](https://mlsanity.com/paper/2404.06997/) (2024)
- [Effective Communication with Dynamic Feature Compression](https://mlsanity.com/paper/2401.16236/) (2024)
- [Semantic-aware Digital Twin for Metaverse: A Comprehensive Review](https://mlsanity.com/paper/2305.18304/) (2023)
- [Reasoning with the Theory of Mind for Pragmatic Semantic Communication](https://mlsanity.com/paper/2311.18224/) (2023)
- [Semantic and Effective Communication for Remote Control Tasks with Dynamic Feature Compression](https://mlsanity.com/paper/2301.05901/) (2023)
- [Task-Oriented Prediction and Communication Co-Design for Haptic Communications](https://mlsanity.com/paper/2302.11064/) (2023)
- [IRS-Enhanced Secure Semantic Communication Networks: Cross-Layer and Context-Awared Resource Allocation](https://mlsanity.com/paper/2411.01821/) (2024)
- [BRIEDGE: EEG-Adaptive Edge AI for Multi-Brain to Multi-Robot Interaction](https://mlsanity.com/paper/2403.15432/) (2024)
- [Observation Compression in Rate-Limited Closed-Loop Distributed ISAC Systems: From Signal Reconstruction to Control](https://mlsanity.com/paper/2505.01780/) (2025)
- [Deep Semantic Inference over the Air: An Efficient Task-Oriented Communication System](https://mlsanity.com/paper/2508.12748/) (2025)
- [Semantic Waveforms for AI-Native 6G Networks](https://mlsanity.com/paper/2602.13316/) (2026)
- [MASK: Multi-Agent Semantic K-Scheduling for Risk-Sensitive 6G Robotics](https://mlsanity.com/paper/2606.11249/) (2026)
- [Wireless Backdoor Attack and Defense for Semantic Communications over Multiple Access Channel](https://mlsanity.com/paper/2606.30595/) (2026)
- [Multi-Agent Transformer for Queue-Level XR Traffic Scheduling in TSN Networks](https://mlsanity.com/paper/2608.05340/) (2026)
- [Communication Reduction via Semantic-Based Encoding in DMPC Using LSTMs](https://mlsanity.com/paper/2608.17592/) (2026)
- [Managing Context and Communication in Distributed Agentic UAV Swarms](https://mlsanity.com/paper/2610.01569/) (2026)

## Abstract (arXiv)

We present our vision for a departure from the established way of architecting and assessing communication networks, by incorporating the semantics of information for communications and control in networked systems. We define semantics of information, not as the meaning of the messages, but as their significance, possibly within a real time constraint, relative to the purpose of the data exchange. We argue that research efforts must focus on laying the theoretical foundations of a redesign of the entire process of information generation, transmission and usage in unison by developing: advanced semantic metrics for communications and control systems; an optimal sampling theory combining signal sparsity and semantics, for real-time prediction, reconstruction and control under communication constraints and delays; semantic compressed sensing techniques for decision making and inference directly in the compressed domain; semantic-aware data generation, channel coding, feedback, multiple and random access schemes that reduce the volume of data and the energy consumption, increasing the number of supportable devices.