@article{tian_hu_li_wang_zhang_2023, title={Machine Learning-Assisted Codebook Design for MMSE Channel Estimation}, ISSN={["2164-7038"]}, DOI={10.1109/ICCWORKSHOPS57953.2023.10283641}, abstractNote={In order to realize the high spectral efficiency promised by the new radio, the channel estimation algorithm shall be carefully designed to achieve high accuracy. Conventional optimal estimation techniques require the knowledge of secondorder statistics, which is difficult to compute in real-time systems. In this work, we propose a machine learning-assisted codebook design for minimum mean square error (MMSE) channel estimation, where ML techniques are applied to cluster the channels that minimize the sum normalized mean square error (MSE). Specifically, we use k-medoids as the clustering method and we propose the normalized mismatched weight error performance as the clustering dissimilarity measure. Simulation results demonstrate the close-to-optimal channel estimation performance with reasonable codebook size, and robustness to signal-to-noise-ratio (SNR) changes and truncated codeword length.}, journal={2023 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS, ICC WORKSHOPS}, author={Tian, Xiaowen and Hu, Yeqing and Li, Yang and Wang, Tiexing and Zhang, Jianzhong}, year={2023}, pages={283–288} }
 @article{tian_gonzalez-prelcic_heath_2022, title={Optimizing the Deployment of Reconfigurable Intelligent Surfaces in MmWave Vehicular Systems}, ISSN={["2576-6813"]}, DOI={10.1109/GLOBECOM48099.2022.10001015}, abstractNote={Millimeter wave (MmWave) systems are vulnerable to blockages, which cause signal drop and link outage. One solution is to deploy reconfigurable intelligent surfaces (RISs) to add a strong non-line-of-sight path from the transmitter to receiver. To achieve the best performance, the location of the deployed RIS should be optimized for a given site, considering the distribution of potential users and possible blockers. In this paper, we find the optimal location, height and downtilt of RIS working in a realistic vehicular scenario. Because of the proximity between the RIS and the vehicles, and the large electrical size of the RIS, we consider a 3D geometry including the elevation angle and near-field beamforming. We provide results on RIS configuration in terms of both coverage ratio and area-averaged rate. We find that the optimized RIS improves the area-averaged rate fifty percent over the case without a RIS, as well as further improvements in the coverage ratio.}, journal={2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022)}, author={Tian, Xiaowen and Gonzalez-Prelcic, Nuria and Heath, Robert W., Jr.}, year={2022}, pages={5261–5266} }