{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:12:22Z","timestamp":1775067142248,"version":"3.50.1"},"reference-count":24,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,8,7]],"date-time":"2022-08-07T00:00:00Z","timestamp":1659830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In a reconfigurable intelligent surface (RIS) assisted millimeter Wave (mmWave) communication system, the channel coefficient increases exponentially with the number of RIS elements which results in expensive pilot overhead. Most previous works have proposed some channel estimation algorithms for the estimation accuracy of cascaded channels, which have improved the estimation accuracy, but the pilot overhead is discouraging in the estimation process. To improve the channel estimation accuracy with reduced pilot overhead, we propose a two-stage channel estimation protocol by exploiting semi-passive elements and the coherent time difference of the channel, where the quasi-static channel between the base stations (BS) and RIS is estimated at the RIS, and the user (UE)-RIS time-varying channel is estimated at the BS. In the first stage, we formulate the BS-RIS channel estimation as a mathematical optimization problem by an iterative weighting method and then propose a gradient descent (GD)-based algorithm to solve it. In the second stage, we first transform the received the UE-RIS signal model into an equivalent parallel factor (PARAFAC) tensor model and estimate the UE-RIS channel by the least-squares (LS) algorithm. The simulation results show that the proposed method has better estimation accuracy than the LS, compression sensing (CS) and minimum mean square error (MMSE) methods with less pilot overhead, and the spectral efficiency is improved by at least 10.5% compared to the other three methods.<\/jats:p>","DOI":"10.3390\/s22155908","type":"journal-article","created":{"date-parts":[[2022,8,9]],"date-time":"2022-08-09T04:16:55Z","timestamp":1660018615000},"page":"5908","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Two-Stage Channel Estimation for Semi-Passive RIS-Assisted Millimeter Wave Systems"],"prefix":"10.3390","volume":"22","author":[{"given":"Chengzuo","family":"Peng","sequence":"first","affiliation":[{"name":"School of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Honggui","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoqi","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuyan","family":"Qian","sequence":"additional","affiliation":[{"name":"School of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8281-3125","authenticated-orcid":false,"given":"Wenjuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yinhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Physics and Electronics, Central South University, Lushan South Road, Changsha 410083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"188171","DOI":"10.1109\/ACCESS.2020.3031392","article-title":"RIS-Assisted Coverage Enhancement in Millimeter-Wave Cellular Networks","volume":"8","author":"Nemati","year":"2020","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1109\/OJCOMS.2020.3015394","article-title":"Channel Estimation Techniques for Millimeter-Wave Communication Systems: Achievements and Challenges","volume":"1","author":"Hassan","year":"2020","journal-title":"IEEE Open J. Commun. Soc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3313","DOI":"10.1109\/TCOMM.2021.3051897","article-title":"Intelligent Reflecting Surface-Aided Wireless Communications: A Tutorial","volume":"69","author":"Wu","year":"2021","journal-title":"IEEE Trans. Commun."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1109\/MCOM.001.1900107","article-title":"Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network","volume":"58","author":"Wu","year":"2020","journal-title":"IEEE Commun. Mag."},{"key":"ref_5","first-page":"5394","article-title":"Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming","volume":"18","author":"Wu","year":"2019","journal-title":"IEEE Trans. Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1109\/LWC.2020.3020850","article-title":"Robust design for IRS-aided communication systems with user location uncertainty","volume":"10","author":"Hu","year":"2020","journal-title":"IEEE Commun. Lett."},{"key":"ref_7","first-page":"6648","article-title":"Joint Deployment and Multiple Access Design for Intelligent Reflecting Surface Assisted Networks","volume":"20","author":"Mu","year":"2021","journal-title":"IEEE Trans. Commun."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Mishra, D., and Johansson, H. (2019, January 12\u201317). Channel estimation and low-complexity beamforming design for passive intelligent surface assisted MISO wire less energy transfer. Proceedings of the 2019 IEEE International Conference on Acoustics, Speech Signal Process (ICASSP\u201919), Brighton, UK.","DOI":"10.1109\/ICASSP.2019.8683663"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Jensen, T.L., and Carvalho, E.D. (2020, January 4\u20138). On optimal channel estimation scheme for intelligent reflecting surfaces based on a minimum variance unbiased estimator. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Barcelona, Spain.","DOI":"10.1109\/ICASSP40776.2020.9053695"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1109\/OJCOMS.2020.2992791","article-title":"Intelligent reflecting surface-assisted multi-user MISO communication: Channel estimation and beamforming design","volume":"1","author":"Alwazani","year":"2020","journal-title":"IEEE Open J. Commun. Soc."},{"key":"ref_11","unstructured":"Lin, J., Wang, G., and Fan, R. (2020). Channel estimation for wireless communication systems assisted by large intelligent surfaces. arXiv."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6607","DOI":"10.1109\/TWC.2020.3004330","article-title":"Channel estimation for intelligent reflecting surface assisted multiuser communications: Framework, algorithms, and analysis","volume":"19","author":"Wang","year":"2020","journal-title":"IEEE Trans. Wireless Commun."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1109\/LWC.2019.2948632","article-title":"Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMO","volume":"9","author":"He","year":"2020","journal-title":"IEEE Commun. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1109\/LSP.2021.3059363","article-title":"TRICE: A channel estimation framework for RIS-aided millimeter-wave MIMO systems","volume":"28","author":"Ardah","year":"2021","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/LSP.2020.2998357","article-title":"Compressed channel estimation for intelligent reflecting surface-assisted millimeter wave systems","volume":"27","author":"Wang","year":"2020","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"44304","DOI":"10.1109\/ACCESS.2021.3064073","article-title":"Enabling large intelligent surfaces with compressive sensing and deep Learning","volume":"9","author":"Taha","year":"2021","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Taha, A., Alrabeiah, M., and Alkhateeb, A. (2019, January 9\u201313). Deep learning for large intelligent surfaces in millimeter wave and massive MIMO systems. Proceedings of the 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA.","DOI":"10.1109\/GLOBECOM38437.2019.9013256"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"9223","DOI":"10.1109\/TVT.2020.3005402","article-title":"Deep denoising neural network assisted compressive channel estimation for mmWave intelligent reflecting surfaces","volume":"69","author":"Liu","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Deng, H., Xu, F., Zhang, W., Liu, G., and Zhang, Y. (2022). Hybrid Precoding-Based Millimeter Wave Massive MIMO-NOMA Systems. Symmetry, 14.","DOI":"10.3390\/sym14020412"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"4649","DOI":"10.1109\/TSP.2016.2572041","article-title":"Super-resolution compressed sensing for line spectral estimation: An iterative reweighted approach","volume":"64","author":"Fang","year":"2016","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"8954","DOI":"10.1109\/TVT.2018.2842724","article-title":"Super-resolution channel estimation for mmWave massive MIMO with hybrid precoding","volume":"67","author":"Hu","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"7736","DOI":"10.1109\/TCOMM.2021.3072729","article-title":"Two-Timescale Channel Estimation for Reconfigurable Intelligent Surface Aided Wireless Communications","volume":"69","author":"Hu","year":"2021","journal-title":"IEEE Trans. Commun."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1137\/07070111X","article-title":"Tensor decompositions and applications","volume":"51","author":"Kolda","year":"2009","journal-title":"SIAM Rev."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1109\/JSTSP.2021.3061274","article-title":"Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Systems: A Tensor Modeling Approach","volume":"15","author":"Boyer","year":"2021","journal-title":"IEEE J. Sel. Top. Signal Process."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/15\/5908\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:05:30Z","timestamp":1760141130000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/15\/5908"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,7]]},"references-count":24,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["s22155908"],"URL":"https:\/\/doi.org\/10.3390\/s22155908","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,7]]}}}