{"title":"异构大规模MIMO蜂窝系统中用户公平性增强的有效导频污染缓解算法","authors":"Abhinaba Dey, P. Pattanayak","doi":"10.1109/SILCON55242.2022.10028928","DOIUrl":null,"url":null,"abstract":"Pilot contamination has now been noted as a significant barrier to the accurate calculation of channel state information (CSI). A heterogeneous massive multiple-input-multiple-output(MIMO) cellular system has been addressed in this work, where the user number in each cell is presumed to vary. The users of each cell also continue to utilize the same pilots. As a result, the massive MIMO cellular system architecture opens the possibility of both intra-cellular and inter-cellular pilot contamination. Two sub-optimal methods are developed in this article to reduce the aforementioned pilot contamination, allocating similar pilot signals to different users in an orderly fashion depending on how much interference they are deemed to suffer. The intracellular pilot contamination was resolved in the first method before the inter-cellular pilot contamination. According to the second method, the inter-cellular pilot contamination was solved before the intra-cellular pilot contamination. The goal of each of these methods is to increase user fairness. As a result, users with higher channel gains are allocated the pilots having maximal interference, and vice versa. By contrasting the efficacy of the developed algorithms with current pilot contamination mitigation methods for different system parameters, it has been demonstrated how effective they are.","PeriodicalId":183947,"journal":{"name":"2022 IEEE Silchar Subsection Conference (SILCON)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient Pilot Contamination Mitigation Algorithms for User Fairness Enhancement in Heterogeneous Massive MIMO Cellular Systems\",\"authors\":\"Abhinaba Dey, P. Pattanayak\",\"doi\":\"10.1109/SILCON55242.2022.10028928\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pilot contamination has now been noted as a significant barrier to the accurate calculation of channel state information (CSI). A heterogeneous massive multiple-input-multiple-output(MIMO) cellular system has been addressed in this work, where the user number in each cell is presumed to vary. The users of each cell also continue to utilize the same pilots. As a result, the massive MIMO cellular system architecture opens the possibility of both intra-cellular and inter-cellular pilot contamination. Two sub-optimal methods are developed in this article to reduce the aforementioned pilot contamination, allocating similar pilot signals to different users in an orderly fashion depending on how much interference they are deemed to suffer. The intracellular pilot contamination was resolved in the first method before the inter-cellular pilot contamination. According to the second method, the inter-cellular pilot contamination was solved before the intra-cellular pilot contamination. The goal of each of these methods is to increase user fairness. As a result, users with higher channel gains are allocated the pilots having maximal interference, and vice versa. By contrasting the efficacy of the developed algorithms with current pilot contamination mitigation methods for different system parameters, it has been demonstrated how effective they are.\",\"PeriodicalId\":183947,\"journal\":{\"name\":\"2022 IEEE Silchar Subsection Conference (SILCON)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Silchar Subsection Conference (SILCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SILCON55242.2022.10028928\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Silchar Subsection Conference (SILCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SILCON55242.2022.10028928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient Pilot Contamination Mitigation Algorithms for User Fairness Enhancement in Heterogeneous Massive MIMO Cellular Systems
Pilot contamination has now been noted as a significant barrier to the accurate calculation of channel state information (CSI). A heterogeneous massive multiple-input-multiple-output(MIMO) cellular system has been addressed in this work, where the user number in each cell is presumed to vary. The users of each cell also continue to utilize the same pilots. As a result, the massive MIMO cellular system architecture opens the possibility of both intra-cellular and inter-cellular pilot contamination. Two sub-optimal methods are developed in this article to reduce the aforementioned pilot contamination, allocating similar pilot signals to different users in an orderly fashion depending on how much interference they are deemed to suffer. The intracellular pilot contamination was resolved in the first method before the inter-cellular pilot contamination. According to the second method, the inter-cellular pilot contamination was solved before the intra-cellular pilot contamination. The goal of each of these methods is to increase user fairness. As a result, users with higher channel gains are allocated the pilots having maximal interference, and vice versa. By contrasting the efficacy of the developed algorithms with current pilot contamination mitigation methods for different system parameters, it has been demonstrated how effective they are.