Massive MIMO is expected to play an important role in the development of 5G networks. This paper addresses the issue of pilot contamination and scalability in massive MIMO systems. The current practice of reusing orthogonal pilot sequences in adjacent cells leads to difficulty in differentiating incoming inter- and intra-cell pilot sequences. One possible solution is to increase the number of orthogonal pilot sequences, which results in dedicating more space of coherence block to pilot transmission than data transmission. This, in turn, also hinders the scalability of massive MIMO systems, particularly in accommodating a large number of IoT devices within a cell. To overcome these challenges, this paper devises an innovative pilot allocation scheme based on the data transfer patterns of IoT devices. The scheme assigns orthogonal pilot sequences to clusters of devices instead of individual devices, allowing multiple devices to utilize the same pilot for periodically transmitting data. Moreover, we formulate the pilot assignment problem as a graph coloring problem and use the max k-cut graph partitioning approach to overcome the pilot contamination in a multicell massive MIMO system. The proposed scheme significantly improves the spectral efficiency and enables the scalability of massive MIMO systems; for instance, by using ten orthogonal pilot sequences, we are able to accommodate 200 devices with only a 12.5% omission rate.

翻译：大规模MIMO预计将在5G网络的发展中发挥重要作用。本文探讨了大规模MIMO系统中的导频污染与可扩展性问题。当前在相邻小区中复用正交导频序列的做法，导致难以区分小区内外的导频序列。一种可能的解决方案是增加正交导频序列的数量，但这会使得相干块中用于导频传输的空间多于数据传输，进而限制大规模MIMO系统的可扩展性，尤其是在小区内容纳大量物联网设备时。为应对这些挑战，本文基于物联网设备的数据传输模式设计了一种创新的导频分配方案。该方案将正交导频序列分配给设备簇而非单个设备，允许多个设备利用相同的导频定期传输数据。此外，我们将导频分配问题建模为图着色问题，并采用最大k割图划分方法克服多小区大规模MIMO系统中的导频污染。所提方案显著提升了频谱效率，并实现了大规模MIMO系统的可扩展性；例如，使用十个正交导频序列即可容纳200个设备，仅产生12.5%的遗漏率。