Shanko Chura Aredo, Y. Negash, Y. Wondie, Feyisa Debo, Rajaveerappa Devadas, Abreham Fekadu
{"title":"大规模MIMO系统的密度感知协同预编码技术","authors":"Shanko Chura Aredo, Y. Negash, Y. Wondie, Feyisa Debo, Rajaveerappa Devadas, Abreham Fekadu","doi":"10.1109/ict4da53266.2021.9672239","DOIUrl":null,"url":null,"abstract":"Communication via millimeter-wave (mm-wave) has grown in favor as an alternative to the existing radio mobile communication technology for providing high gigabit-per-second data speeds. Because of the millimeter wave's short wavelengths, a large number of antennas may be placed in a compacted physical dimension to make a greater aperture and obtain a substantial gain in antenna arrays. Dirty paper coding (DPC) beamforming efficiently cancels the interference that the transmitter is aware of, resulting in increased capacity, energy, and spectral efficiency of mmWave enabled massive MIMO connectivity. However, the use of this techniques leads to complexity due to successive interference cancellation at detection when the number of users grow large. In this paper, a cooperative processing based multi-user precoding is presented for down-link mm-wave massive MIMO systems and thus cooperative precoding be implicitly designed by considering the digital beamforming solution which is obtained from the dirty paper after comparing the output of linear precoding schemes. The precoders are chosen and the system total rate is calculated based on the difficulty of detections based on user densities within virtual cells. Simulation results show that the proposed approach outperforms traditional digital beamforming in terms of sum rate.","PeriodicalId":371663,"journal":{"name":"2021 International Conference on Information and Communication Technology for Development for Africa (ICT4DA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Density Aware Cooperative Precoding Technique for Massive MIMO Systems\",\"authors\":\"Shanko Chura Aredo, Y. Negash, Y. Wondie, Feyisa Debo, Rajaveerappa Devadas, Abreham Fekadu\",\"doi\":\"10.1109/ict4da53266.2021.9672239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Communication via millimeter-wave (mm-wave) has grown in favor as an alternative to the existing radio mobile communication technology for providing high gigabit-per-second data speeds. Because of the millimeter wave's short wavelengths, a large number of antennas may be placed in a compacted physical dimension to make a greater aperture and obtain a substantial gain in antenna arrays. Dirty paper coding (DPC) beamforming efficiently cancels the interference that the transmitter is aware of, resulting in increased capacity, energy, and spectral efficiency of mmWave enabled massive MIMO connectivity. However, the use of this techniques leads to complexity due to successive interference cancellation at detection when the number of users grow large. In this paper, a cooperative processing based multi-user precoding is presented for down-link mm-wave massive MIMO systems and thus cooperative precoding be implicitly designed by considering the digital beamforming solution which is obtained from the dirty paper after comparing the output of linear precoding schemes. The precoders are chosen and the system total rate is calculated based on the difficulty of detections based on user densities within virtual cells. Simulation results show that the proposed approach outperforms traditional digital beamforming in terms of sum rate.\",\"PeriodicalId\":371663,\"journal\":{\"name\":\"2021 International Conference on Information and Communication Technology for Development for Africa (ICT4DA)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Information and Communication Technology for Development for Africa (ICT4DA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ict4da53266.2021.9672239\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Information and Communication Technology for Development for Africa (ICT4DA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ict4da53266.2021.9672239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Density Aware Cooperative Precoding Technique for Massive MIMO Systems
Communication via millimeter-wave (mm-wave) has grown in favor as an alternative to the existing radio mobile communication technology for providing high gigabit-per-second data speeds. Because of the millimeter wave's short wavelengths, a large number of antennas may be placed in a compacted physical dimension to make a greater aperture and obtain a substantial gain in antenna arrays. Dirty paper coding (DPC) beamforming efficiently cancels the interference that the transmitter is aware of, resulting in increased capacity, energy, and spectral efficiency of mmWave enabled massive MIMO connectivity. However, the use of this techniques leads to complexity due to successive interference cancellation at detection when the number of users grow large. In this paper, a cooperative processing based multi-user precoding is presented for down-link mm-wave massive MIMO systems and thus cooperative precoding be implicitly designed by considering the digital beamforming solution which is obtained from the dirty paper after comparing the output of linear precoding schemes. The precoders are chosen and the system total rate is calculated based on the difficulty of detections based on user densities within virtual cells. Simulation results show that the proposed approach outperforms traditional digital beamforming in terms of sum rate.