Zhang, J., Liu, W. orcid.org/0000-0003-2968-2888, Tennant, A. et al. (3 more authors) (2022) Performance evaluation of spatial scattering modulation in the indoor environment. In: 2022 International Symposium on Wireless Communication Systems (ISWCS). Proceedings of 2022 International Symposium on Wireless Communication Systems (ISWCS), 19-22 Oct 2022, Hangzhou, China. Institute of Electrical and Electronics Engineers (IEEE) ISBN 9781665455459
Abstract
In this paper, a state-of-the-art massive MIMO modulation system, spatial scattering modulation (SSM), is evaluated considering practical indoor wireless environments for the first time. Firstly, the SSM system is reviewed, which works under the narrowband sparse physical channel model and exploits beamspace domain resources to enhance spectral efficiency via analog beamforming. Secondly, to generate parameters for the narrowband sparse physical channel model in a specific indoor environment, channel prediction is performed based on the intelligent ray launching algorithm (IRLA), which has been verified via practical measurements. Therein, building structures and large objects in the indoor environment are modelled. Thirdly, an approach is proposed for characterizing ergodic average bit error probability (ABEP) to evaluate the SSM system in the indoor environment. Finally, numerical experiments are carried out, which show that channel models widely adopted in existing literature for evaluations of the SSM system are oversimplified.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. This accepted manuscript version is available under a Creative Commons Attribution CC BY licence. (http://creativecommons.org/licenses/by/4.0) |
Keywords: | Spatial scattering modulation; massive MIMO; analog beamforming; intelligent ray launching algorithm; indoor radio wave propagation; bit error probability |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 24 Nov 2022 17:15 |
Last Modified: | 24 Nov 2022 17:15 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/iswcs56560.2022.9940429 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:193708 |
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