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A new path loss model based on the volumetric occupancy rate for the pine forests at 5G frequency band

Published online by Cambridge University Press:  20 November 2020

Abdullah Genc Open the ORCID record for Abdullah Genc [Opens in a new window]
Abdullah Genc*
Affiliation:
Department of Mechatronics Engineering, Isparta University of Applied Sciences, Isparta 32260, Turkey
*
Author for correspondence: Abdullah Genc, E-mail: [email protected]
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Abstract

In this paper, a new empirical path loss model based on frequency, distance, and volumetric occupancy rate is generated at the 3.5 and 4.2 GHz in the scope of 5G frequency bands. This study aims to determine the effect of the volumetric occupancy rate on path loss depending on the foliage density of the trees in the pine forest area. Using 4.2 GHz and the effect of the volumetric occupancy rate contributes to the literature in terms of novelty. Both the reference measurements to generate a model and verification measurements to verify the proposed models are conducted in three different regions of the forest area with double ridged horn antennas. These regions of the artificial forest area consist of regularly sorted and identical pine trees. Root mean square error (RMSE) and R-squared values are calculated to evaluate the performance of the proposed model. For 3.5 and 4.2 GHz, while the RMSEs are 3.983 and 3.883, the values of R-squared are 0.967 and 0.963, respectively. Additionally, the results are compared with four path loss models which are commonly used in the forest area. The proposed one has the best performance among the other models with values 3.98 and 3.88 dB for 3.5 and 4.2 GHz.

Keywords

Path loss modelvolumetric occupancy rate5G frequency bandpenetration loss
Type
EM Field Theory
Information
International Journal of Microwave and Wireless Technologies , Volume 13 , Issue 2 , March 2021 , pp. 144 - 153
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press in association with the European Microwave Association

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References

Meng, YS, Lee, YH and Ng, BC (2009) Empirical near ground path loss modeling in a forest at VHF and UHF bands. IEEE Transactions on Antennas Propagation 57, 1461–1468.CrossRefGoogle Scholar
Meng, YS, Lee, YH and Ng, BC (2009) Study of propagation loss prediction in forest environment. Progress in Electromagnetics Research 17, 117–133.CrossRefGoogle Scholar
Kurnaz, O and Helhel, S (2014) Near ground propagation model for pine tree forest environment. AEU-International Journal of Electronics and Communications 68, 944–950.CrossRefGoogle Scholar
Forest area, Food and Agriculture Organization (2020) The World Bank. Available at https://data.worldbank.org/indicator/AG.LND.FRST.ZS (date last accessed 14 February 2020).Google Scholar
Silva, JC, Siqueira, GL and Castellanos, P (2018) Propagation model for path loss through vegetated environments at 700–800 MHz band. Journal of Microwaves, Optoelectronics and Electromagnetic Applications 17, 179–187.CrossRefGoogle Scholar
Azevedo, JA (2011) Santos FE: an empirical propagation model for forest environments at tree trunk level. IEEE Transactions on Antennas Propagation 59, 2357–2367.CrossRefGoogle Scholar
Joshi, GG, Dietrich, CB, Anderson, CR, Newhall, WG and David, WA (2005) Near-ground channel measurements over line-of-sight and forested paths. IEE Proceedings - Microwaves, Antennas and Propagation 152 589–596.CrossRefGoogle Scholar
Smith, DP, Messier, GG and Wasson, MW (2016) Boreal forest low antenna height propagation measurements. IEEE Transactions on Antennas Propagation 64, 4004–4011.CrossRefGoogle Scholar
Rao, TR, Balachander, D, Tiwari, N and Prasad, M (2013) Ultra-high frequency near-ground short-range propagation measurements in forest and plantation environments for wireless sensor networks. IET Wireless Sensor Systems 3, 80–84.CrossRefGoogle Scholar
Leonor, NR, Caldeirinha, RF, Fernandes, TR, Ferreira, D and Sánchez, MG (2014) A 2D ray-tracing based model for micro-and millimeter-wave propagation through vegetation. IEEE Transactions on Antennas Propagation 62, 6443–6453.CrossRefGoogle Scholar
Adewumi, AS and Olabisi, O (2018) Characterization and modeling of vegetation effects on UHF propagation through a long forested channel. Progress in Electromagnetics Research 73, 9–16.CrossRefGoogle Scholar
Leonor, NR, Sánchez, MG, Fernandes, TR and Caldeirinha, RF (2018) A 2D ray-tracing based model for wave propagation through forests at micro-and millimeter wave frequencies. IEEE Access 6, 32097–32108.CrossRefGoogle Scholar
Leonor, NR, Caldeirinha, RF and Sánchez, MG (2017) Fernandes TR: a two-dimensional ray-tracing-based model for propagation through vegetation: a practical assessment using ornamental plants at 60 GHz. IEEE Antennas and Propagation Magazine 59, 145–150.CrossRefGoogle Scholar
Gay-Fernández, JA and Cuiñas, I (2014) Short-term modeling in vegetation media at wireless network frequency bands. IEEE Transactions on Antennas Propagation 62, 3330–3337.CrossRefGoogle Scholar
Anderson, CR, Volos, HI and Buehrer, RM (2013) Characterization of low-antenna ultrawideband propagation in a forest environment. IEEE Transactions on Vehicular Technology 62, 2878–2895.CrossRefGoogle Scholar
Gay-Fernandez, JA and Cuinas, I (2013) Peer to peer wireless propagation measurements and path-loss modeling in vegetated environments. IEEE Transactions on Antennas Propagation 61, 3302–3311.CrossRefGoogle Scholar
Helhel, S (2016) Volume scattering from corn and wheat canopies at 32 GHz. 22nd International Conference on Applied Electromagnetics and Communications (ICECOM), Croitia, pp. 1–5.Google Scholar
Blaunstein, N, Kovacs, IZ, Ben-Shimol, Y, Andersen, JB and Katz, D (2003) Prediction of UHF path loss for forest environments. Radio Science 38, 1–16.CrossRefGoogle Scholar
Picallo, I, Klaina, H, Lopez-Iturri, P, Aguirre, E and Celaya-Echarri, M (2019) A radio channel model for d2d communications blocked by single trees in forest environments. Sensors 19, 1–16.CrossRefGoogle ScholarPubMed
Eras, L. EC, da Silva, DK, Barros, FB, Correia, LM and Cavalcante, G (2018) A radio propagation model for mixed paths in Amazon environments for the UHF band. Wireless Communications and Mobile Computing 2018, 1–16.CrossRefGoogle Scholar
Wang, F and Sarabandi, K (2005) An enhanced millimeter-wave foliage propagation model. IEEE Transactions on Antennas Propagation 53, 2138–2145.CrossRefGoogle Scholar
Liao, D and Sarabandi, K (2007) Modeling and simulation of near-earth propagation in presence of a truncated vegetation layer. IEEE Transactions on Antennas Propagation 55, 949–957.CrossRefGoogle Scholar
Zhang, Y, Anderson, CR, Michelusi, N, Love, DJ and Baker, KR (2019) Propagation modeling through foliage in a coniferous forest at 28 GHz. IEEE Wireless Communication Letters 8, 901–904.CrossRefGoogle Scholar
Hejselbæk, J, Nielsen, JØ, Fan, W and Pedersen, GF (2018) Empirical study of near ground propagation in forest terrain for internet-of-things type device-to-device communication. IEEE Access 6, 54052–54063.CrossRefGoogle Scholar
Shutimarrungson, N and Wuttidittachotti, P (2019) Realistic propagation effects on wireless sensor networks for landslide management. EURASIP Journal of Wireless Communication 94, 1–14.Google Scholar
Kurnaz, O, Bitigan, M and Helhel, S (2012) Procedure of near ground propagation model development for pine tree forest environment. Progress in Electromagnetics Research Symposium Proceedings, Moscow, Russia, pp. 1403–1406.Google Scholar
Chen, HY (2001) Kuo Y: calculation of radio loss in forest environments by an empirical formula. Microwave and Optical Technology Letters 31, 474–480.CrossRefGoogle Scholar
Al-Nuaimi, M and Stephens, R (1998) Measurements and prediction model optimisation for signal attenuation in vegetation media at centimetre wave frequencies. IEE Proceedings - Microwaves, Antennas and Propagation 145, 201–206.CrossRefGoogle Scholar
Azpilicueta, L, López-Iturri, P, Aguirre, E, Mateo, I and Astrain, JJ (2014) Analysis of radio wave propagation for ISM 2.4 GHz wireless sensor networks in inhomogeneous vegetation environments. Sensors 14, 23650–23672.CrossRefGoogle ScholarPubMed
Arslan, E and Kaymaz, I (2020) Visitor perception of recreational ecosystem services and their role in landscape management of Gölcük Nature Park. Turkey. International Journal of Sustainable Development & World Ecology 27, 202–213.CrossRefGoogle Scholar
Li, Q, Zhang, H, Lu, Y, Zheng, T and Lv, Y (2019) A new method for path-loss modeling. International Journal of Microwave Wireless Technology 11, 739–746.CrossRefGoogle Scholar
Ozturk, M, Sevim, UK, Akgol, O, Unal, E and Karaaslan, M (2020) Investigation of the mechanic, electromagnetic characteristics and shielding effectiveness of concrete with boron ores and boron containing wastes. Construction and Building Materials 252, 1–11.CrossRefGoogle Scholar
Ozturk, M, Depci, T, Karaaslan, M, Sevim, UK, Akgol, O and Hacioglu, SO (2020) Synergetic effect of waste tire rubber and mil scale on electromagnetic wave attenuation properties of new generation mortar. Journal of Building Engineering 30, 1–7.CrossRefGoogle Scholar
Özkan, V, Yapici, A, Karaaslan, M and Akgöl, O (2020) Electromagnetic scattering properties of MWCNTs/graphene doped epoxy layered with PVC nanofiber/E-glass composites. Journal of Electronic Materials 49, 2249–2256.CrossRefGoogle Scholar
Ozturk, M, Depci, T, Bahceci, E, Karaaslan, M, Akgol, O and Sevim, UK (2020) Production of new electromagnetic wave shielder mortar using waste mill scales. Construction and Building Materials 242, 1–9.CrossRefGoogle Scholar