A Study on Indoor Scenario Channel Clustering and Analysis Acceleration

In order to better understand and develop channel models, it is necessary to identify clusters within the channel. Given the complexity of existing clustering algorithms, an automatic and highly accurate clustering algorithm becomes particularly important. Measurements were conducted in both corridors and corners, with the acquired channel data subsequently analyzed for clustering by using the K-PowerMeans algorithm. Moreover, along with the USRP X310 system, a hardware platform was designed to form a lightweight measurement framework capable of synchronous data acquisition and real-time channel analysis.