No CrossRef data available.
The study of shadowing effect for LTE and 5G networks in suburban environment
Published online by Cambridge University Press: 15 December 2023
Abstract
The presence of obstacles in the propagation path is a critical factor in air-to-ground (AG) communication. The behavior of wireless signal propagation depends on several variables, such as frequency, building height, elevation angle, and street design. This paper aims to compare the three established line of sight (LOS) probability model based on actual site data, including the building geometry in suburban environment. The comparison between these three models using the site data provide a guideline for selecting the LOS probability model based on the optimistic and pessimistic predictions. The shadowing loss was evaluated at frequencies 2 and 3.5 GHz with an elevation angle of 20° in two suburban locations at Universiti Tun Hussein Onn Malaysia. Three prediction models, ITU-R P.1410-5, Holis and Pechac, and Pang et al., available in the literature were used to identify and compare the line-of-sight probability. By focusing on the shadowing model in suburban area, the guideline for optimizing LOS communications or navigation in these challenging environments can be developed. The finding highlights the importance of considering building height in AG communication for network performance evaluation and design.
Keywords
- Type
- Research Paper
- Information
- Copyright
- © The Author(s), 2023. Published by Cambridge University Press in association with the European Microwave Association
References
Khawaja, W, Guvenc, I, Matolak, DW, Fiebig, UC and Schneckenburger, N (2019) A survey of air-to-ground propagation channel modeling for unmanned aerial vehicles. IEEE Communications Surveys and Tutorials 21(3), 2361–2391.CrossRefGoogle Scholar
Pérez Fontán, F and Mariño Espiñeira, P (2008) Modeling the Wireless Propagation Channel. UK: John Wiley & Sons Ltd.CrossRefGoogle Scholar
Matolak, DW and Sun, R (2017) Air-ground channel characterization for unmanned aircraft systems – Part III: the suburban and near-urban environments. IEEE Transactions on Vehicular Technology 66(8), 6607–6618.CrossRefGoogle Scholar
Sun, R, Matolak, DW and Rayess, W (2017) Air-ground channel characterization for unmanned aircraft systems – Part IV: airframe shadowing. IEEE Transactions on Vehicular Technology 66(9), 7643–7652.CrossRefGoogle Scholar
Meng, YS and Lee, YH (2012) Study of shadowing effect by aircraft maneuvering for air-to-ground communication. AEU – International Journal of Electronics and Communications 66(1), 7–11.CrossRefGoogle Scholar
Mielke, DM, Schneckenburger, N, Fiebig, UC, Walter, M and Bellido-Manganell, M (2021) Analysis of the dominant signal component of the air-ground channel based on measurement data at C-band. IEEE Transactions on Vehicular Technology 70(4), 2955–2968.CrossRefGoogle Scholar
Amorim, R, Nguyen, H, Mogensen, P, Kovács, IZ, Wigard, J and Sørensen, TB (2017) Radio channel modeling for UAV communication over cellular networks. IEEE Wireless Communications Letters 6(4), 514–517.CrossRefGoogle Scholar
Nathan, S, David, WM and Alphan, S (2022) Measurement and modeling of low-altitude air-ground channels in two frequency bands. In 2022 Integrated Communication, Navigation and Surveillance Conference (ICNS), May, 1–10.Google Scholar
Zhu, Q, Wang, C, Hua, B, Mao, K, Jiang, S and Yao, M (2021) 3GPP TR 38.901 channel model. In Tafazolli, R, Chatzimisios, P and Wang, C-L (eds), Wiley 5G Ref: The Essential 5G Reference Online. UK: John Wiley & Sons, Ltd, 1–35.Google Scholar
ITU-R P.1410-5 (2012) Propagation data and prediction methods required for the design of terrestrial broadband radio access systems in a Frequency Range from 3 to 60 GHz.Google Scholar
Song, M, Huo, Y, Liang, Z, Dong, X and Lu, T (2022) Air-to-ground large-scale channel characterization by ray tracing. IEEE Access 10(December), 125930–125941.CrossRefGoogle Scholar
Holis, J and Pechac, P (2008) Elevation dependent shadowing model for mobile communications via high altitude platforms in built-up areas. IEEE Transactions on Antennas and Propagation 56(4), 1078–1084.CrossRefGoogle Scholar
Pang, M, Zhu, Q, Bai, F, Li, Z, Mao, K and Tian, Y (2021) Height-dependent LoS probability model for A2G Mm wave communications under built-up scenarios. Computer Science 878, 1209–1217.Google Scholar
Pang, M, Zhu, Q, Wang, C-X, Lin, Z, Liu, J, Lv, C and Li, Z (2023) Geometry-based stochastic probability models for the LoS and NLoS paths of A2G channels under Urban Scenarios. IEEE Internet of Things Journal 10(3), 2360–2372.CrossRefGoogle Scholar
Xiang, L, Jing, X and Hongying, T (2018) Analysis of frequency-dependent line-of-sight probability in 3-D environment. IEEE Communications Letters 22(8), 1732–1735.Google Scholar
Cui, Z, Guan, K, Briso-Rodriguez, C, Ai, B and Zhong, Z (2020) Frequency-dependent line-of-sight probability modeling in built-up environments. IEEE Internet of Things Journal 7(1), 699–709.CrossRefGoogle Scholar
Malaysian Communications and Multimedia Commission (2019) Allocation of spectrum bands for mobile broadband service in Malaysia. https://www.mcmc.gov.my/skmmgovmy/media/General/pdf/PI-Allocation-of-spectrum-bands-for-mobile-broadband-service-in-Malaysia_1.pdf (accessed 21 August 2022).Google Scholar