Scedasticity descriptor of terrestrial wireless communications channels for multipath clustering datasets

Citation Author(s):
Jojo
Blanza
Submitted by:
Jojo Blanza
Last updated:
Wed, 08/16/2023 - 21:50
DOI:
10.21227/4khe-gx08
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Abstract 

Fifth-generation (5G) wireless systems increased the bandwidth, improved the speed, and shortened the latency of communications systems. Various channel models are developed to study 5G. These channel models reproduce the stochastic properties of multiple-input multiple-output (MIMO) antennas by generating wireless multipath components (MPCs). The MPCs that have similar properties in delay, angles of departure, and angles of arrival form clusters. The multipaths and multipath clusters serve as datasets and are clustered to understand the properties of 5G. These datasets generated by the COST 2100, IMT-2020, QuaDRiGa, and WINNER II channel models are tested for their homoscedasticity based on Johansen's procedure. Results show that the COST 2100, QuaDRiGa, and WINNER II datasets are heteroscedastic, while the IMT-2020 dataset is homoscedastic.

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