An experimentally validated fading model for THz wireless systems

Evangelos N. Papasotiriou*, Alexandros Apostolos A. Boulogeorgos, Katsuyuki Haneda, Mar Francis de Guzman, Angeliki Alexiou

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)
72 Downloads (Pure)

Abstract

As the wireless world moves towards the sixth generation (6G) era, the demand of supporting bandwidth-hungry applications in ultra-dense deployments becomes more and more imperative. Driven by this requirement, both the research and development communities have turned their attention into the tera hertz (THz) band, where more than 20 GHz of contiguous bandwidth can be exploited. As a result, novel wireless system and network architectures have been reported promising excellence in terms of reliability, massive connectivity, and data-rates. To assess their feasibility and efficiency, it is necessary to develop stochastic channel models that account for the small-scale fading. However, to the best of our knowledge, only initial steps have been so far performed. Motivated by this, this contribution is devoted to take a new look to fading in THz wireless systems, based on three sets of experimental measurements. In more detail, measurements, which have been conducted in a shopping mall, an airport check-in area, and an entrance hall of a university towards different time periods, are used to accurately model the fading distribution. Interestingly, our analysis shows that conventional distributions, such as Rayleigh, Rice, and Nakagami-m, lack fitting accuracy, whereas, the more general, yet tractable, alpha-mu distribution has an almost-excellent fit. In order to quantify their fitting efficiency, we used two well-defined and widely-accepted tests, namely the Kolmogorov-Smirnov and the Kullback-Leibler tests. By accurately modeling the THz wireless channel, this work creates the fundamental tools of developing the theoretical and optimization frameworks for such systems and networks.

Original languageEnglish
Article number18717
Number of pages14
JournalScientific Reports
Volume11
Issue number1
DOIs
Publication statusPublished - 21 Sep 2021
MoE publication typeA1 Journal article-refereed

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