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超高密度分布式天线系统中用于协作干扰消除的动态聚类与协同用户调度

Dynamic Clustering and Coordinated User Scheduling for Cooperative Interference Cancellation on Ultra-High Density Distributed Antenna Systems.

作者信息

Maruta Kazuki

机构信息

Graduate School of Engineering, Chiba University, Chiba 263-8522, Japan.

出版信息

Entropy (Basel). 2018 Aug 19;20(8):616. doi: 10.3390/e20080616.

DOI:10.3390/e20080616
PMID:33265705
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7513143/
Abstract

This paper proposes dynamic clustering and user scheduling for previously conceived inter-cluster interference cancellation scheme on ultra-high density distributed antenna system (UHD-DAS). UHD-DAS is composed of one central unit (CU) and densely deployed remote radio units (RUs) serving as small cell access points. It can enhance spatial spectral efficiency by alleviating traffic load imposed per radio unit; however, intenser small cell deployment revives the inter-cell interference (ICI) problem. Cell clustering, cooperation of multiple RUs, can mitigate ICI partially, whereas inter-cluster interference (ICLI) still limits its possible capacity. Simplified ICLI cancellation based on localized RU cooperation was previously proposed to mitigate interference globally. The resolved issue is that it required frequency reuse distance to fully obtain its interference cancellation ability. This paper introduces dynamic clustering with coordinated user scheduling to ensure reuse distance without extra frequency reuse. Joint dynamic clustering and ICLI cancellation can effectively work and almost reaches ideal performance as full cooperative spatial multiplexing transmission.

摘要

本文针对超高密度分布式天线系统（UHD-DAS）中先前设想的簇间干扰消除方案提出了动态聚类和用户调度方法。UHD-DAS由一个中央单元（CU）和作为小小区接入点密集部署的远程无线电单元（RU）组成。它可以通过减轻每个无线电单元所承受的业务负载来提高空间频谱效率；然而，更密集的小小区部署又使小区间干扰（ICI）问题再次出现。小区聚类，即多个RU的协作，可以部分减轻ICI，而簇间干扰（ICLI）仍然限制了其可能的容量。先前曾提出基于局部RU协作的简化ICLI消除方法以全局减轻干扰。所解决的问题是，它需要频率复用距离才能充分获得其干扰消除能力。本文引入了具有协调用户调度的动态聚类，以确保在无需额外频率复用的情况下实现复用距离。联合动态聚类和ICLI消除可以有效工作，并且几乎达到了全协作空间复用传输的理想性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/1fbe6993f36f/entropy-20-00616-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/1336fcca2af3/entropy-20-00616-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/6aec027429aa/entropy-20-00616-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/a9f4fefc2ace/entropy-20-00616-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/bbf265c6a304/entropy-20-00616-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/827ef728f033/entropy-20-00616-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/6b1d2ece9f1d/entropy-20-00616-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/8ee1b15a83a3/entropy-20-00616-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/1fbe6993f36f/entropy-20-00616-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/1336fcca2af3/entropy-20-00616-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/6aec027429aa/entropy-20-00616-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/a9f4fefc2ace/entropy-20-00616-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/bbf265c6a304/entropy-20-00616-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/827ef728f033/entropy-20-00616-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/6b1d2ece9f1d/entropy-20-00616-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/8ee1b15a83a3/entropy-20-00616-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f3eb/7513143/1fbe6993f36f/entropy-20-00616-g008.jpg

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