论文标题
无细胞大型MIMO系统中的飞行员重复使用：一种多样的聚类方法
Pilot Reuse in Cell-Free Massive MIMO Systems: A Diverse Clustering Approach
论文作者
论文摘要
最近已提出了分布式或无单元格（CF）大量多输入，多重输出（MMIMO），以回答当前以网络为中心系统的局限性，以提供高率无处不在的传输。提供统一服务水平的能力使CF MMIMO成为超过5G和6G网络的潜在技术。准确的通道状态信息（CSI）的获取对于不同的CF MMIMO操作至关重要。因此，上行链路试验训练阶段用于有效估计传输通道。可用的正交试点信号的数量有限，重用这些飞行员将增加副驾驶干扰。这会导致不良效果称为试验污染，可以降低系统性能。因此，需要适当的试点重用策略来减轻飞行员污染的影响。在本文中，我们将CF MMIMO中的试点分配作为一个多样化的聚类问题，并提出了一种迭代性最大值搜索方案来解决该方案。在这种方法中，我们首先构成用户设备（UES）的簇，以使集群内多样性最大化，然后为同一集群中所有UES分配相同的飞行员。数值结果表明，有关上行链路和下行平均链路平均和每个用户数据速率的其他方法，所提出的技术优越性。
Distributed or Cell-free (CF) massive Multiple-Input, Multiple-Output (mMIMO), has been recently proposed as an answer to the limitations of the current network-centric systems in providing high-rate ubiquitous transmission. The capability of providing uniform service level makes CF mMIMO a potential technology for beyond-5G and 6G networks. The acquisition of accurate Channel State Information (CSI) is critical for different CF mMIMO operations. Hence, an uplink pilot training phase is used to efficiently estimate transmission channels. The number of available orthogonal pilot signals is limited, and reusing these pilots will increase co-pilot interference. This causes an undesirable effect known as pilot contamination that could reduce the system performance. Hence, a proper pilot reuse strategy is needed to mitigate the effects of pilot contamination. In this paper, we formulate pilot assignment in CF mMIMO as a diverse clustering problem and propose an iterative maxima search scheme to solve it. In this approach, we first form the clusters of User Equipments (UEs) so that the intra-cluster diversity maximizes and then assign the same pilots for all UEs in the same cluster. The numerical results show the proposed techniques' superiority over other methods concerning the achieved uplink and downlink average and per-user data rate.
