The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Intelligent walls as autonomous parts of smart indoor environments
Abstract
This study introduces the concept of an intelligent wall as an autonomous part of a smart indoor environment for cognitive wireless networks. Here, an intelligent wall is a wall inside a building equipped with an active frequency-selective surface, simple low-cost sensors and a cognitive engine with machine-learning ability. Using simulations, it has been shown that the smart environment based on intelligent walls can react to the immediate demands of an indoor wireless system, control radio coverage and, consequently, influence the overall system performance. The concept of the intelligent walls is described and evaluated based on a simple implementation of an arrangement of two intelligent walls in a conference centre scenario. Artificial neural networks were employed in the cognitive engine. Elementary orthogonal frequency division multiple access static system simulations are used to analyse the influence of the smart environment on the system performance. Results are discussed in detail and typical characteristics of the aforementioned system are derived and summarised.
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Cites
RADAR: an in-building RF-based user location and tracking system
Bahl, P., & Padmanabhan, V. N. (2002) · Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064) · doi:10.1109/infcom.2000.832252 · Cited by 8,380
Cited by
Wireless Communications Through Reconfigurable Intelligent Surfaces
Basar, E., Di Renzo, M., De Rosny, J., Debbah, M., Alouini, M.-S., & Zhang, R. (2019) · IEEE Access · doi:10.1109/access.2019.2935192 · Cited by 3,394
Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come
Renzo, M. D., Debbah, M., Phan-Huy, D.-T., Zappone, A., Alouini, M.-S., Yuen, C., Sciancalepore, V., Alexandropoulos, G. C., Hoydis, J., Gacanin, H., et al. (2019) · EURASIP Journal on Wireless Communications and Networking · doi:10.1186/s13638-019-1438-9 · Cited by 1,717
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey
Gong, S., Lu, X., Hoang, D. T., Niyato, D., Shu, L., Kim, D. I., & Liang, Y.-C. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3004197 · Cited by 1,035
Massive Access for 5G and Beyond
Chen, X., Ng, D. W. K., Yu, W., Larsson, E. G., Al-Dhahir, N., & Schober, R. (2021) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3019724 · Cited by 681
Jiang, T., Cheng, H. V., & Yu, W. (2021) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2021.3078502 · Cited by 290
Metadata
- Authors
- Subrt, L., & Pechac, P.
- Venue
- IET Communications
- Published
- 2012-05-22
- Volume
- 6
- Issue
- 8
- Pages
- 1004-1010
- ISSN
- 1751-8628 (ISSN-L)
- 1751-8636
- OpenAlex
- W2037866776
- Cited by
- 208
- References
- 1
- FWCI
- 4.22
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
