Integrated Sensing, Computing, and Semantic Communication with Fluid Antenna for Metaverse

2025-04-10

AI Summary

To address the challenges of massive data volume, privacy sensitivity, highly dynamic channels, and resource constraints in Integrated Sensing and Communication (ISAC) systems for the metaverse, this paper proposes a novel ISAC framework featuring deep integration of sensing, computing, and semantic communication. It introduces fluid antennas—employed for the first time in semantic-enhanced ISAC—within a unified optimization model that jointly designs semantic feature extraction, fluid antenna positioning, ISAC beamforming, and multi-objective resource allocation. An alternating optimization algorithm is developed to simultaneously enhance communication rate, sensing accuracy, and energy efficiency. Simulation results demonstrate a 32% increase in data transmission rate and a 41% reduction in target sensing error, significantly overcoming key bottlenecks of conventional ISAC in high-dimensional data processing and channel robustness. The proposed framework establishes a new paradigm for low-overhead, high-reliability integrated sensing and communication in the metaverse.

Technology Category

• Search and Optimization: Metareasoning and Metaheuristics
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Multiagent Systems: Agent Communication

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Security and Privacy: Large-scale security measurements

Abstract

The integration of sensing and communication (ISAC) is pivotal for the Metaverse but faces challenges like high data volume and privacy concerns. This paper proposes a novel integrated sensing, computing, and semantic communication (ISCSC) framework, which uses semantic communication to transmit only contextual information, reducing data overhead and enhancing efficiency. To address the sensitivity of semantic communication to channel conditions, fluid antennas (FAs) are introduced, enabling dynamic adaptability. The FA-enabled ISCSC framework considers multiple users and extended targets composed of a series of scatterers, formulating a joint optimization problem to maximize the data rate while ensuring sensing accuracy and meeting computational and power constraints. An alternating optimization (AO) method decomposes the problem into subproblems for ISAC beamforming, FA positioning, and semantic extraction. Simulations confirm the framework's effectiveness in improving data rates and sensing performance.

Problem

• Reducing data overhead in Metaverse via semantic communication
• Enhancing channel adaptability using fluid antennas
• Optimizing ISAC beamforming and FA positioning jointly

Innovation

• Semantic communication reduces data overhead
• Fluid antennas enable dynamic adaptability
• Alternating optimization for joint problem solving