A massive multiple-input multiple-output (MIMO) system uses a large number of antennas in the base station (BS) to serve multiple users, which significantly improves the capacity of the system. However, in time division duplex (TDD) mode, the pilot contamination (PC) is inevitable due to the multiplexing of pilots. This paper proposed a pilot assignment based on graph coloring and location information (GC-LI) to improve the performance of users. Specifically, based on graph coloring, the proposed GC-LI algorithm combines location information like the angle of arrival (AoA), distance, and correlation to construct an interference graph. Then, we calculate the interference between any two users and use the postprocessing discrete Fourier transform (DFT) filtering process to effectively distinguish the users with nonoverlapping AoAs. Finally, according to the interference graph, the GC-LI algorithm is proposed to mitigate the intercell interference (ICI) between users with the same pilot by assigning different pilots to connected users with high ICI metrics based on some regulation. Simulation results show that the GC-LI algorithm is suitable for various types of cells. In addition, compared with the existing pilot assignment algorithms based on graph coloring, users’ average signal-to-interference-plus-noise ratio (SINR) and uplink achievable sum rate (ASR) are significantly improved.

中文翻译：

---

多小区多用户大规模MIMO系统中基于图着色和位置信息的导频分配

大规模多输入多输出（MIMO）系统在基站（BS）中使用大量天线来服务多个用户，显着提高了系统的容量。然而，在时分双工（TDD）模式下，由于导频复用，导频污染（PC）是不可避免的。本文提出了一种基于图着色和位置信息（GC-LI）的试点分配，以提高用户的性能。具体来说，基于图着色，所提出的 GC-LI 算法结合了到达角 (AoA)、距离和相关性等位置信息来构建干扰图。然后，我们计算任意两个用户之间的干扰，并使用后处理离散傅立叶变换 (DFT) 滤波过程来有效区分具有非重叠 AoA 的用户。最后，根据干扰图，提出了 GC-LI 算法，通过基于某种规则为具有高 ICI 度量的连接用户分配不同的导频，以减轻具有相同导频的用户之间的小区间干扰 (ICI)。仿真结果表明GC-LI算法适用于各种类型的细胞。此外，与现有的基于图形着色的导频分配算法相比，用户的平均信干噪比（SINR）和上行链路可实现总和率（ASR）得到显着提升。仿真结果表明GC-LI算法适用于各种类型的细胞。此外，与现有的基于图形着色的导频分配算法相比，用户的平均信干噪比（SINR）和上行链路可实现总和率（ASR）得到显着提升。仿真结果表明GC-LI算法适用于各种类型的细胞。此外，与现有的基于图形着色的导频分配算法相比，用户的平均信干噪比（SINR）和上行链路可实现总和率（ASR）得到显着提升。