{"title":"基于可重构智能表面辅助物联网的干扰抑制","authors":"Xiangcheng Lin","doi":"10.1117/12.2639159","DOIUrl":null,"url":null,"abstract":"Cellular-based Internet of Things (IoT) network has huge potential, i.e., enhancing security, promoting smart cities, and so on, while the interference will become very serious with the increasing densification of cells. Reconfigurable intelligent surface (RIS) has tremendous potential to alleviate interference. In this paper, we use RIS to improve the system performance via reducing the interference from neighboring cells and users in the same cell. We establish an optimization problem to maximize data rate with the constraint of the power of base stations (BSs). Due to the nonconvexity of the optimization problem, it’s difficult to obtain the optimal passive beamforming and active beamforming directly. Thus, we propose the fractional programming (FP) method to approximate non-convex objective function to tractable forms. Then, we utilize an improved block coordinate descent (BCD) algorithm to find suitable passive and active beamforming for the presented two convex functions. Simulation results demonstrate that the BCD method has better system performance than the non-RIS and random phase schemes.","PeriodicalId":336892,"journal":{"name":"Neural Networks, Information and Communication Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interference mitigation based on reconfigurable intelligent surface-assisted Internet of Things\",\"authors\":\"Xiangcheng Lin\",\"doi\":\"10.1117/12.2639159\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cellular-based Internet of Things (IoT) network has huge potential, i.e., enhancing security, promoting smart cities, and so on, while the interference will become very serious with the increasing densification of cells. Reconfigurable intelligent surface (RIS) has tremendous potential to alleviate interference. In this paper, we use RIS to improve the system performance via reducing the interference from neighboring cells and users in the same cell. We establish an optimization problem to maximize data rate with the constraint of the power of base stations (BSs). Due to the nonconvexity of the optimization problem, it’s difficult to obtain the optimal passive beamforming and active beamforming directly. Thus, we propose the fractional programming (FP) method to approximate non-convex objective function to tractable forms. Then, we utilize an improved block coordinate descent (BCD) algorithm to find suitable passive and active beamforming for the presented two convex functions. Simulation results demonstrate that the BCD method has better system performance than the non-RIS and random phase schemes.\",\"PeriodicalId\":336892,\"journal\":{\"name\":\"Neural Networks, Information and Communication Engineering\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Networks, Information and Communication Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2639159\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Networks, Information and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2639159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interference mitigation based on reconfigurable intelligent surface-assisted Internet of Things
Cellular-based Internet of Things (IoT) network has huge potential, i.e., enhancing security, promoting smart cities, and so on, while the interference will become very serious with the increasing densification of cells. Reconfigurable intelligent surface (RIS) has tremendous potential to alleviate interference. In this paper, we use RIS to improve the system performance via reducing the interference from neighboring cells and users in the same cell. We establish an optimization problem to maximize data rate with the constraint of the power of base stations (BSs). Due to the nonconvexity of the optimization problem, it’s difficult to obtain the optimal passive beamforming and active beamforming directly. Thus, we propose the fractional programming (FP) method to approximate non-convex objective function to tractable forms. Then, we utilize an improved block coordinate descent (BCD) algorithm to find suitable passive and active beamforming for the presented two convex functions. Simulation results demonstrate that the BCD method has better system performance than the non-RIS and random phase schemes.