论文标题
改善基于三重态的频道图表，对分布式大规模MIMO测量
Improving Triplet-Based Channel Charting on Distributed Massive MIMO Measurements
论文作者
论文摘要
频道图表的目的是从高维CSI中学习无线电环境的虚拟图，该图是由多Antenna无线系统获取的。由于在静态环境中，CSI是发射机位置的函数，因此可以使用降低性降低技术以自我监督的方式学习从CSI到通道图坐标的映射。基于最新的三重态方法在通过分布式大型MIMO通道音响器测量的多个数据集上进行了评估，并具有共同分配和分布式天线设置。通过将结果与从Genie Aded三胞胎生成器中学到的通道图进行比较，并通过测量数据从三胞胎中学到的结果来研究合适的三重态选择的重要性。最后，探索了学习的前向图表功能到相似的可传递性，但探索了不同的无线电环境。
The objective of channel charting is to learn a virtual map of the radio environment from high-dimensional CSI that is acquired by a multi-antenna wireless system. Since, in static environments, CSI is a function of the transmitter location, a mapping from CSI to channel chart coordinates can be learned in a self-supervised manner using dimensionality reduction techniques. The state-of-the-art triplet-based approach is evaluated on multiple datasets measured by a distributed massive MIMO channel sounder, with both co-located and distributed antenna setups. The importance of suitable triplet selection is investigated by comparing results to channel charts learned from a genie-aided triplet generator and learned from triplets on simulated trajectories through measured data. Finally, the transferability of learned forward charting functions to similar, but different radio environments is explored.
