{"title":"基于PARAFAC模型的MIMO中继系统信道估计算法研究","authors":"Kuiyuan Zhang, Jianping Li, E. J. Guo","doi":"10.1109/ICRITO.2017.8342426","DOIUrl":null,"url":null,"abstract":"For the semi-blind estimation problem of two-hop multi-input multi-output amplified forwarding (MIMO-AF) relay system, the parallel factor (PARAFAC) model is constructed for the received signal. Using the uniqueness of its decomposition, an ALS-LS algorithm is proposed. Based on the algorithm of least squares alternating (ALS) and adding relaxation factor, the ALS algorithm is used to achieve certain convergence conditions. The estimation result of the former algorithm is taken as the initial value, and then based on the ALS algorithm adding relaxation factor, using the relaxation factor to change the gradient direction, so as to speed up the convergence rate. And the performance of the channel model is analyzed by different parameters of the channel model. Simulation results show: compared with the existing least squares alternate algorithm, the complexity and iteration times of the algorithm are reduced, and the convergence speed of the algorithm is accelerated.","PeriodicalId":357118,"journal":{"name":"2017 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research on channel estimation algorithm of MIMO relay system based on PARAFAC model\",\"authors\":\"Kuiyuan Zhang, Jianping Li, E. J. Guo\",\"doi\":\"10.1109/ICRITO.2017.8342426\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the semi-blind estimation problem of two-hop multi-input multi-output amplified forwarding (MIMO-AF) relay system, the parallel factor (PARAFAC) model is constructed for the received signal. Using the uniqueness of its decomposition, an ALS-LS algorithm is proposed. Based on the algorithm of least squares alternating (ALS) and adding relaxation factor, the ALS algorithm is used to achieve certain convergence conditions. The estimation result of the former algorithm is taken as the initial value, and then based on the ALS algorithm adding relaxation factor, using the relaxation factor to change the gradient direction, so as to speed up the convergence rate. And the performance of the channel model is analyzed by different parameters of the channel model. Simulation results show: compared with the existing least squares alternate algorithm, the complexity and iteration times of the algorithm are reduced, and the convergence speed of the algorithm is accelerated.\",\"PeriodicalId\":357118,\"journal\":{\"name\":\"2017 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRITO.2017.8342426\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRITO.2017.8342426","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on channel estimation algorithm of MIMO relay system based on PARAFAC model
For the semi-blind estimation problem of two-hop multi-input multi-output amplified forwarding (MIMO-AF) relay system, the parallel factor (PARAFAC) model is constructed for the received signal. Using the uniqueness of its decomposition, an ALS-LS algorithm is proposed. Based on the algorithm of least squares alternating (ALS) and adding relaxation factor, the ALS algorithm is used to achieve certain convergence conditions. The estimation result of the former algorithm is taken as the initial value, and then based on the ALS algorithm adding relaxation factor, using the relaxation factor to change the gradient direction, so as to speed up the convergence rate. And the performance of the channel model is analyzed by different parameters of the channel model. Simulation results show: compared with the existing least squares alternate algorithm, the complexity and iteration times of the algorithm are reduced, and the convergence speed of the algorithm is accelerated.