{"title":"基于字典的张量分解辅助毫米波MU-MIMO系统时变信道估计","authors":"Tongtong Weng, Wuyang Zhou","doi":"10.1109/ICCCS57501.2023.10150749","DOIUrl":null,"url":null,"abstract":"This research focuses on the multiple-input multiple-output (MIMO) mmWave systems' uplink time-varying channel estimation challenge. We convert the time-varying channel es-timation in the hybrid beamforming structure into a param-eter estimation problem that takes angles of arrival/departure (AoA/AoDs), Doppler shift, and path gains into account. We also suggest a two-stage channel estimation method. We describe the receiving signals as a third-order tensor in the initial stage and provide an algorithm that combines Matching Pursuit (MP) and Alternating Least Squares (ALS) called Dictionary-based Tensor Decomposition to estimate AoA/AoDs. In the second stage, we recover the Doppler shifts and paath gains using the estimated AoA/AoDs. The entire time-varying channel is finally restored. The simulation results demonstrate that the suggested method performs better than the traditional approach in terms of complexity and estimation accuracy.","PeriodicalId":266168,"journal":{"name":"2023 8th International Conference on Computer and Communication Systems (ICCCS)","volume":"4 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dictionary-Based Tensor Decomposition-Aided Time-Varying Channel Estimation for Millimeter Wave MU-MIMO Systems\",\"authors\":\"Tongtong Weng, Wuyang Zhou\",\"doi\":\"10.1109/ICCCS57501.2023.10150749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research focuses on the multiple-input multiple-output (MIMO) mmWave systems' uplink time-varying channel estimation challenge. We convert the time-varying channel es-timation in the hybrid beamforming structure into a param-eter estimation problem that takes angles of arrival/departure (AoA/AoDs), Doppler shift, and path gains into account. We also suggest a two-stage channel estimation method. We describe the receiving signals as a third-order tensor in the initial stage and provide an algorithm that combines Matching Pursuit (MP) and Alternating Least Squares (ALS) called Dictionary-based Tensor Decomposition to estimate AoA/AoDs. In the second stage, we recover the Doppler shifts and paath gains using the estimated AoA/AoDs. The entire time-varying channel is finally restored. The simulation results demonstrate that the suggested method performs better than the traditional approach in terms of complexity and estimation accuracy.\",\"PeriodicalId\":266168,\"journal\":{\"name\":\"2023 8th International Conference on Computer and Communication Systems (ICCCS)\",\"volume\":\"4 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 8th International Conference on Computer and Communication Systems (ICCCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCS57501.2023.10150749\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 8th International Conference on Computer and Communication Systems (ICCCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCS57501.2023.10150749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dictionary-Based Tensor Decomposition-Aided Time-Varying Channel Estimation for Millimeter Wave MU-MIMO Systems
This research focuses on the multiple-input multiple-output (MIMO) mmWave systems' uplink time-varying channel estimation challenge. We convert the time-varying channel es-timation in the hybrid beamforming structure into a param-eter estimation problem that takes angles of arrival/departure (AoA/AoDs), Doppler shift, and path gains into account. We also suggest a two-stage channel estimation method. We describe the receiving signals as a third-order tensor in the initial stage and provide an algorithm that combines Matching Pursuit (MP) and Alternating Least Squares (ALS) called Dictionary-based Tensor Decomposition to estimate AoA/AoDs. In the second stage, we recover the Doppler shifts and paath gains using the estimated AoA/AoDs. The entire time-varying channel is finally restored. The simulation results demonstrate that the suggested method performs better than the traditional approach in terms of complexity and estimation accuracy.