Scedasticity descriptor of terrestrial wireless communications channels for multipath clustering datasets

Citation Author(s):
Submitted by:
Jojo Blanza
Last updated:
Wed, 08/16/2023 - 21:50
Data Format:
0 ratings - Please login to submit your rating.


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.


Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in any component of these datasets/codes are trade names, service marks, trademarks or registered trademarks of their respective owners. The author(s)/publisher(s)/authorizing body is/are not associated with any product or vendor mentioned in any component of these datasets/codes.

The inclusion of an organization name, product, or service in any part of these datasets/codes should not be construed as an endorsement of such organization, product, or service, nor is failure to include an organization name, product, or service to be construed as disapproval.

Any component or publication of these datasets/codes is designed to provide accurate and authoritative information in regard to the subject matter covered. Every attempt has been made to ensure accuracy at the time of publication. Any component or publication of these datasets/codes is made on the understanding that the the author(s)/publisher(s)/authorizing body is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought.

Any statements expressed in any component or publication of these datasets/codes are those of the individual authors and do not necessarily represent the views of the authors' affiliations, which takes no responsibility for any statement made herein. No reference made in this publication to any specific method, product, process, or service constitutes or implies an endorsement, recommendation, or warranty thereof by the authors' affiliations. The materials are for general information only and do not represent a standard of the authors' affiliations, nor are they intended as a reference in applicable  specifications, contracts, regulations, statutes, or any other legal document. The authors' affiliations makes no representation or warranty of any kind, whether express or implied, concerning the accuracy, completeness, suitability, or utility of any information, apparatus, product, or process discussed in this publication, and assumes no liability therefor. The information contained in these materials should not be used without first securing competent advice with respect to its suitability for any general or specific application. Anyone utilizing such information assumes all liability arising from such use, including but not limited to infringement of any patent or patents.