{"title":"毫米波MIMO-OFDM系统的有效波束形成训练和信道估计","authors":"Hanyu Wang, Jun Fang, Huiping Duan, Hongbin Li","doi":"10.1109/SAM48682.2020.9104337","DOIUrl":null,"url":null,"abstract":"We consider the problem of channel estimation for millimeter wave (mmWave) MIMO-OFDM systems. To efficiently probe the channel, the transmitter forms multiple beams simultaneously and steer them towards different directions. The objective of this paper is to devise the beamtraining patterns and develop an efficient algorithm to estimate the channel. By exploiting the common sparsity inherent in MIMO-OFDM mmWave channels, we develop a sparse bipartite graph coding-based method for joint beamforming training and channel estimation. Simulation results are provided to show the effectiveness of the proposed method.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"4 0 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Efficient Beamforming Training and Channel Estimation for mmWave MIMO-OFDM Systems\",\"authors\":\"Hanyu Wang, Jun Fang, Huiping Duan, Hongbin Li\",\"doi\":\"10.1109/SAM48682.2020.9104337\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the problem of channel estimation for millimeter wave (mmWave) MIMO-OFDM systems. To efficiently probe the channel, the transmitter forms multiple beams simultaneously and steer them towards different directions. The objective of this paper is to devise the beamtraining patterns and develop an efficient algorithm to estimate the channel. By exploiting the common sparsity inherent in MIMO-OFDM mmWave channels, we develop a sparse bipartite graph coding-based method for joint beamforming training and channel estimation. Simulation results are provided to show the effectiveness of the proposed method.\",\"PeriodicalId\":6753,\"journal\":{\"name\":\"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"volume\":\"4 0 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAM48682.2020.9104337\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM48682.2020.9104337","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient Beamforming Training and Channel Estimation for mmWave MIMO-OFDM Systems
We consider the problem of channel estimation for millimeter wave (mmWave) MIMO-OFDM systems. To efficiently probe the channel, the transmitter forms multiple beams simultaneously and steer them towards different directions. The objective of this paper is to devise the beamtraining patterns and develop an efficient algorithm to estimate the channel. By exploiting the common sparsity inherent in MIMO-OFDM mmWave channels, we develop a sparse bipartite graph coding-based method for joint beamforming training and channel estimation. Simulation results are provided to show the effectiveness of the proposed method.
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