Multi Robot-assisted Channel Estimation for 6G Upper Mid-band Communications

To meet the growing demands for high data rates, the millimeter-wave (mmWave) band has gained much attention with its wide bandwidth. However, its inherent drawbacks, such as severe propagation loss and weak connectivity, have constrained its practical implementation. As a promising alternative, the upper mid-band (7–24 GHz) spectrum, also known as frequency range 3 (FR3), offers a favorable balance between high capacity and robust connectivity. Despite these advantages, efficient channel estimation in FR3 remains challenging, not only due to rapidly changing environments but also due to limited adaptability of existing methods. To overcome this issue, we propose a novel multi robot-assisted channel estimation (MR-CE) framework for upper mid-band systems. By leveraging LiDAR-equipped robots to capture both quasi-static and dynamic environmental features, our approach rapidly and accurately extracts key channel parameters for upper mid-band channel estimation. Numerical evaluations demonstrate that MR-CE significantly outperforms conventional techniques in terms of normalized mean square error (NMSE), highlighting its potential for robust and adaptive channel estimation in future 6G networks.