From Street Canyons To Corridors: Adapting Urban Propagation Models for an Indoor IQRF Network

dc.contributor.author Doyan, Talip Eren
dc.contributor.author Yalcinkaya, Bengisu
dc.contributor.author Dogan, Deren
dc.contributor.author Dalveren, Yaser
dc.contributor.author Derawi, Mohammad
dc.date.accessioned 2026-01-05T15:21:30Z
dc.date.available 2026-01-05T15:21:30Z
dc.date.issued 2025
dc.description.abstract Among wireless communication technologies underlying Internet of Things (IoT)-based smart buildings, IQRF (Intelligent Connectivity Using Radio Frequency) technology is a promising candidate due to its low power consumption, cost-effectiveness, and wide coverage. However, effectively modeling the propagation characteristics of IQRF in complex indoor environments for simple and accurate network deployment remains challenging, as architectural elements like walls and corners cause substantial signal attenuation and unpredictable propagation behavior. This study investigates the applicability of a site-specific modeling approach, originally developed for urban street canyons, to characterize peer-to-peer (P2P) IQRF links operating at 868 MHz in typical indoor scenarios, including line-of-sight (LoS), one-turn, and two-turn non-line-of-sight (NLoS) configurations. The received signal powers are compared with well-known empirical models, including international telecommunication union radio communication sector (ITU-R) P.1238-9 and WINNER II, and ray-tracing simulations. The results show that while ITU-R P.1238-9 achieves lower prediction error under LoS conditions with a root mean square error (RMSE) of 5.694 dB, the site-specific approach achieves substantially higher accuracy in NLoS scenarios, maintaining RMSE values below 3.9 dB for one- and two-turn links. Furthermore, ray-tracing simulations exhibited notably larger deviations, with RMSE values ranging from 7.522 dB to 16.267 dB and lower correlation with measurements. These results demonstrate the potential of site-specific modeling to provide practical, computationally efficient, and accurate insights for IQRF network deployment planning in smart building environments. en_US
dc.identifier.doi 10.3390/s25226950
dc.identifier.issn 1424-8220
dc.identifier.scopus 2-s2.0-105022884158
dc.identifier.uri https://doi.org/10.3390/s25226950
dc.identifier.uri https://hdl.handle.net/20.500.14411/11040
dc.language.iso en en_US
dc.publisher MDPI en_US
dc.relation.ispartof Sensors en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Internet of Things en_US
dc.subject Smart Buildings en_US
dc.subject Iqrf en_US
dc.subject Indoor Propagation Modeling en_US
dc.subject Diffraction en_US
dc.subject Site-Specific Model en_US
dc.title From Street Canyons To Corridors: Adapting Urban Propagation Models for an Indoor IQRF Network
dc.type Article en_US
dspace.entity.type Publication
gdc.author.scopusid 60211468400
gdc.author.scopusid 57736344000
gdc.author.scopusid 57824405000
gdc.author.scopusid 51763497600
gdc.author.scopusid 35408917600
gdc.author.wosid Dalveren, Yaser/Lzg-3460-2025
gdc.author.wosid Yalcinkaya, Bengisu/Abd-4291-2020
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
gdc.bip.popularityclass C5
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.description.department Atılım University en_US
gdc.description.departmenttemp [Doyan, Talip Eren; Yalcinkaya, Bengisu] Atilim Univ, Dept Elect & Elect Engn, TR-06830 Ankara, Turkiye; [Yalcinkaya, Bengisu] Izmir Bakircay Univ, Dept Comp Engn, TR-35665 Izmir, Turkiye; [Dogan, Deren] Univ Politecn Valencia, Sch Telecommun Engn, Valencia 46022, Spain; [Dalveren, Yaser] Izmir Bakircay Univ, Dept Elect & Elect Engn, TR-35665 Izmir, Turkiye; [Derawi, Mohammad] Norwegian Univ Sci & Technol, Dept Elect Syst, N-2815 Gjovik, Norway en_US
gdc.description.issue 22 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 6950
gdc.description.volume 25 en_US
gdc.description.woscitationindex Science Citation Index Expanded
gdc.description.wosquality Q2
gdc.identifier.openalex W7105704222
gdc.identifier.pmid 41305160
gdc.identifier.wos WOS:001624524500001
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gdc.virtual.author Gökdoğan, Bengisu Yalçınkaya
gdc.virtual.author Doğan, Deren
gdc.virtual.author Dalveren, Yaser
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