Modeling and Analysis of Short Distance Sub-Terahertz Communication Channel via Mixture of Gamma Distribution

With the recent developments on opening terahertz (THz) spectrum for experimental purposes by Federal Communications Commission, transceivers operating in range of 0.1THz-10THz, which are known as THz bands, will enable ultra-high throughput wireless communications. However, actual implementation high-speed and high reliability band communication systems should start with providing extensive knowledge regards to propagation channel characteristics. Considering huge bandwidth rapid changes characteristics channels, ray tracing one-shot statistical modeling not adequate define an accurate model. In this work, we propose Gamma mixture based via expectation-maximization (EM) algorithm. First, maximum likelihood estimation (MLE) is applied characterize model parameters, then EM algorithm used compute MLEs unknown parameters measurement data. The accuracy proposed investigated using Weighted relative mean difference (WMRD) error metrics, Kullback-Leibler (KL)-divergence, Kolmogorov-Smirnov (KS) test show between probability density functions (PDFs) that obtained designed environment. To efficiently evaluate performance method more realistic scenarios, all analysis done examining data from a campaign 240 GHz 300 frequency range, well-isolated anechoic chamber. According WMRD KL-divergence, KS results, PDFs generated distributions fit histogram It shown instead taking pseudo-average sub-bands wide band, models allows determining precisely.