6D Movable Antenna for Internet of Vehicles: CSI-Free Dynamic Antenna Configuration

2026-03-25

AI Summary

This work addresses the challenge of real-time optimization of six-dimensional movable antennas (6DMA) in highly dynamic vehicular networks, where rapid spatiotemporal channel variations hinder conventional approaches. To overcome this, the paper proposes a low-complexity, instantaneous channel state information-free (CSI-Free) dynamic antenna configuration method—marking the first integration of 6DMA into vehicular communications. By jointly leveraging vehicle trajectory predictions and offline prior knowledge of directional antenna responses, the scheme optimizes both antenna positions and orientations at each reconfiguration instant to maximize the average sum rate over a future time window. Extensive simulations in a typical urban intersection scenario demonstrate that the proposed approach significantly outperforms fixed antenna arrays and simplified 6DMA baselines, achieving substantial gains in sum rate.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Application Domains: Mobility, Driving & Flight

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Deploying six-dimensional movable antenna (6DMA) systems in Internet-of-Vehicles (IoV) scenarios can greatly enhance spectral efficiency. However, the high mobility of vehicles causes rapid spatio-temporal channel variations, posing a significant challenge to real-time 6DMA optimization. In this work, we pioneer the application of 6DMA in IoV and propose a low-complexity, instantaneous channel state information (CSI)-free dynamic configuration method. By integrating vehicle motion prediction with offline directional response priors, the proposed approach optimizes antenna positions and orientations at each reconfiguration epoch to maximize the average sum rate over a future time window. Simulation results in a typical urban intersection scenario demonstrate that the proposed 6DMA scheme significantly outperforms conventional fixed antenna arrays and simplified 6DMA baseline schemes in terms of total sum rate.

Problem

• Internet of Vehicles
• 6D Movable Antenna
• channel variation
• real-time optimization
• high mobility

Innovation

• 6D Movable Antenna
• Internet of Vehicles
• CSI-Free
• Dynamic Antenna Configuration
• Vehicle Motion Prediction