5G sets the foundation for an era of creativity with its faster speeds, increased data throughput, reduced latency, and enhanced IoT connectivity, all enabled by Massive MIMO (M-MIMO) technology. M-MIMO boosts network efficiency and enhances user experience by employing intelligent user scheduling. This paper presents a user scheduling scheme and pilot assignment strategy designed for IoT devices, emphasizing mitigating pilot contamination, a key obstacle to improving spectral efficiency (SE) and system scalability in M-MIMO networks. We utilize a user clustering-based pilot allocation scheme to boost IoT device scalability in M-MIMO systems. Additionally, our smart pilot allocation minimizes interference and enhances SE by treating pilot assignment as a graph coloring problem, optimizing it through integer linear programming (ILP). Recognizing the computational complexity of ILP, we introduced a binary search-based heuristic predicated on interference threshold to expedite the computation, while maintaining a near-optimal solution. The simulation results show a significant decrease in the required pilot overhead (about 17%), and substantial enhancement in SE (about 8-14%).

翻译：5G以其更快的速度、更高的数据吞吐量、更低的延迟以及增强的物联网连接能力，为创新时代奠定了基础，这一切均得益于大规模MIMO（M-MIMO）技术的支持。M-MIMO通过采用智能用户调度，提升了网络效率并改善了用户体验。本文提出了一种针对物联网设备的用户调度方案与导频分配策略，重点缓解导频污染——这是制约M-MIMO网络中频谱效率（SE）和系统可扩展性的关键障碍。我们采用基于用户聚类的导频分配方案，以提升M-MIMO系统中物联网设备的可扩展性。此外，我们的智能导频分配通过将导频分配问题建模为图着色问题，并利用整数线性规划（ILP）进行优化，从而最小化干扰并增强SE。考虑到ILP的计算复杂度，我们引入了一种基于干扰阈值的二分搜索启发式算法，以加速计算过程，同时保持接近最优的解。仿真结果显示，所需导频开销显著降低约17%，且SE获得约8-14%的显著提升。