瑞哲 黄

Mr. 瑞哲 黄


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 January 2026 in Sensors
Verified
Journal Article
Open access
PDF file
XWXianjing Wu
Xianjing Wu
瑞黄瑞哲 黄
瑞哲 黄
CWChuliang Wei
Chuliang Wei
XCXutao Chu
Xutao Chu
JCJunbin Chen
Junbin Chen
Shengjie ZhaoShengjie Zhao
Shengjie Zhao
The evolution towards 6G is set to transform Vehicle-to-Everything (V2X) networks by introducing advanced technologies such as Six-Dimensional Movable Antenna (6DMA). This technology endows Roadside Units (RSUs) with dynamic beam-steering capabilities, enabling adaptive coverage. However, traditional RSU deployment strategies, optimized for static coverage, are fundamentally mismatched with these new dynamic capabilities, leading to a critical deployment–optimization mismatch. This paper addresses this challenge by proposing DyDO, a novel Dynamic Deployment and Optimization framework for the utilization of 6DMA-RSUs. Our framework strategically decouples the problem into two modules operating on distinct timescales. On a slow timescale, an offline deployment module analyzes long-term historical traffic data to identify optimal RSU locations. This is guided by a newly proposed metric, the Dynamic Potential Score (DPS), which quantifies a location’s intrinsic value for dynamic adaptation by integrating spatial concentration, temporal volatility, and traffic magnitude. On a fast timescale, an online control module employs an efficient Sequential Angular Search (SAS) algorithm to perform real-time, adaptive beam steering based on immediate traffic patterns. Extensive experiments on a large-scale, real-world trajectory dataset demonstrate that DyDO outperforms conventional static deployment methodologies. This work highlights the necessity of dynamic-aware deployment to fully unlock the potential of 6DMA in future V2X systems.