Analysis of 5.8 GHz Network for Line of Sight (LOS) and Non-Line of Sight (NLOS) in Suburban Environment

Ikha Fadzila Md Idris, Tan Kim Geok, Noor Ziela Abd Rahman, Mohd Haffizzi Md Idris

Abstract


This paper presents the findings of radio wave characterization based on the measurement data at 5.8 GHz. The measurement data were collected by a testbed channel, which links with the following scenarios: a single tree, a row of trees, a row of trees and a road, a row of trees, a road, and a building. These experiments were conducted at University Teknologi Malaysia (UTM) Skudai, Johor to represent the suburban environment. The links consist of pairs of transmitting and receiving antennas that deploy the path of a line of sight (LOS) and non-line of sight (NLOS) radio propagation wave networks. Based on the measurement data analysis, the general issue concerning the statistical probability distribution and the characteristics of LOS and NLOS are examined and discussed. Note that 5.8 GHz technology can be used in both LOS and NLOS scenarios, but its performance varies based on the presence of obstacles and signal propagation characteristics. Other prominent experimental analysis methods, such as hypothesis testing and goodness of fit tests, are implemented to consolidate the findings. The analysis found that the empirical probability density function of LOS and NLOS channels follows Gaussian, Rayleigh, and Rician distribution. Predicting specific future technological developments, such as the availability of 5.8 GHz technology, is challenging because it depends on various factors, including research and development efforts, regulatory decisions, market demand, and technological advancements.

Keywords


Transmitter; receiver; radio wave propagation; line of sight; non-line of sight

Full Text:

PDF

References


R. Dangi, P. Lalwani, G. Choudhary, I. You, and G. Pau, “Study and Investigation on 5G Technology: A Systematic Review,†Sensors 2022, vol. 26, no. 22, 2022. https://doi.org/10.3390/s22010026

A. Sufyan, K. B. Khan, O. A. Khashan, T. Mir, and U. Mir, “From 5G to beyond 5G: A Comprehensive Survey of Wireless Network Evolution, Challenges, and Promising Technologies,†Electron. 2023, vol. 12, no. 10, p. 1200, 2023. https://doi.org/10.3390/electronics12102200

T. Hsiung and Y. Kanza, “SimCT: Spatial Simulation of Urban Evolution to Test Resilience of 5G Cellular Networks,†in Proceedings of the 2nd ACM SIGSPATIAL International Workshop on GeoSpatial Simulation, 2019, pp. 1–8. https://doi.org/10.1145/3356470.3365526

J. Du, D. Chizhik, and R. Feick, “Suburban Fixed Wireless Access Channel Measurements and Models at 28 GHz for 90% Outdoor Coverage,†IEEE Trans. Antenna Propag., vol. 68, no. 1, pp. 411–421, 2020. https://doi/10.1109/TAP.2019.2935110.

M. M. Khan, “Design and Analysis of a Compact UWB Band Notch Antenna for Wireless Communication,†Eng. Proc. 3, vol. 1, no. 6, pp. 1–6, 2020. https://doi.org/10.3390/IEC2020-06974

W. Peng, X. Li, H. Zhang, Z. Liu, and W. Song, “A 5.8 GHz high-gain flexible receiving antenna for wireless power transmission,†AIP Adv., vol. 12, no. 12, 2022. https://doi.org/10.3390/IEC2020-06974

N. Z. A. Rahman, T. K. Geok, T. A. Rahman, I. F. M. Idris, and N. A. A. Hamzah, “Modeling of Dynamic Effect of Vegetation for Fixed Wireless Access,†Wirel. Pers. Commun., vol. 96, no. 1, pp. 709–728, 2017.https:// 10.1007/s11277-017-4240-1

Q. Hou, M. Chai, and H. Wang, “Dynamic modeling of traffic noise in both indoor and outdoor environments by using a ray tracing method,†Build. Environ., vol. 121, pp. 225–237, 2017. https://doi.org/10.1016/j.buildenv.2017.05.031

Y. H. Santana, R. M. Alonso, G. G. Nieto, L. Martens, W. Joseph, and D. Plets, “Indoor Genetic Algorithm-Based 5G Network Planning Using a Machine Learning Model for Path Loss Estimation,†J. Appl. Phys., vol. 12, p. 3923, 2022. https://doi.org/10.3390/app12083923

N. Shabbir et al., “Vision towards 5G: Comparison of radio propagation models for licensed and unlicensed indoor femtocell sensor networks,†Phys. Commun., vol. 47, pp. 1–11, 2021. https://doi.org/10.1016/j.phycom.2021.101371

K. Haneda et al., “Radio propagation modeling methods and tools,†in Inclusive Radio Communications for 5G and Beyond, 2021, pp. 7–48. https://doi.org/10.1016/B978-0-12-820581-5.00008-0

N. Rajesh et al., “Statistical Characterization and Modeling of Radio Frequency Signal Propagation in Mobile Broadband Cellular Next Generation Wireless Networks,†Comput. Intell. Neurosci., 2023. https://doi.org/10.1155/2023/5236566

S. K. . R. Wickramasinghe and K. A. Razak, “The Impact of The Telecommunication Industry as a Moderator on Poverty Alleviation and Educational Programmes to Achieve Sustainable Development Goals In Developing Countries,†J. Informatics Web Eng., vol. 2, no. 1, pp. 25–37, 2023. https://doi.org/10.33093/jiwe.2023.2.1.3

J. M. Romero-Jerez, F. J. Lopez-Martinez, J. F. Paris, and A. J. Goldsmith, “The Fluctuating Two-Ray Fading Model: Statistical Characterization and Performance Analysis,†IEEE Trans. Wirel. Commun., vol. 16, no. 50, pp. 4420–4432, 2017.https://doi. 10.1109/TWC.2017.2698445.

R. Aleksiejunas, “Statistical Approximations of LOS/NLOS Probability in Urban Environment,†ArXiv, vol. abs/2001.1, 2020

https://doi.org/10.48550/arXiv.2001.11813.

N. Díaz, J. Guerra, M. Freire, and J. C. Aviles, “Vehicle Blocking Effect in an Urban NLOS Radio Link Operating in the 28 GHz Band,†in 2019 IEEE 2nd International Conference on Electronics and Communication Engineering, 2019, pp. 133–138. https://doi.org/10.48550/arXiv.2001.11813

M. D. Buhari, T. B. Susilo, I. Khan, and B. O. Sadiq, “Statistical LOS/NLOS Classification for UWB Channels,†KIU J. Sci. Eng. Technol., vol. 2, no. 1, 2023. https://doi.org/10.48550/arXiv.2001.11813

R. Aleksiejunas, A. Cesiul, and K. Svirskas, “Statistical LOS/NLOS Channel Model for Simulations of Next Generation 3GPP Networks,†Elektron. IR ELEKTROTECHNIKA, vol. 24, no. 5, pp. 74–79, 2018

https://doi.org/10.5755/j01.eie.24.5.21847. https://dx.doi.org/10.5755/j01.eie.24.5.21847

C. G. Ruiz, A. Pascual-Iserte, and O. Munoz, “Analysis of Blocking in mmWave Cellular Systems: Characterization of the LOS and NLOS Intervals in Urban Scenarios,†IEEE Trans. Veh. Technol., vol. 69, no. 12, pp. 16247–16252, 2020.https://doi. 10.1109/TVT.2020.3037125.

I. Mohammed, S. Gopalam, I. B. Collings, and S. V. Hanly, “Closed Form Approximations for UAV Line-of-Sight Probability in Urban Environments,†IEEE Access, vol. 11, pp. 40162–40174, 2023.https://10.1109/ACCESS.2023.3267808

M. K. Samimi and T. S. Rappaport, “3-D Millimeter-Wave Statistical Channel Model for 5G Wireless System Design,†IEEE Trans. Microw. Theory Tech., vol. 64, no. 7, pp. 2207–2220, 2016. https://doi.10.1109/TMTT.2016.2574851.

Muhammad Zeeshan Asghar, S. A. Memon, and J. Hämäläinen, “Evolution of Wireless Communication to 6G: Potential Applications and Research Directions,†vol. 14, no. 10, p. 6356, 2022. https://doi.org/10.3390/su14106356

M. Quispe, J. Olivares, J. Samaniego, and R. Morán, “Technical and economic analysis of TVWS and 5.8 GHz Wi-Fi systems for rural areas,†in 2022 IEEE XXIX International Conference on Electronics, Electrical Engineering and Computing (INTERCON), 2022, pp. 1–4. https://10.1109/INTERCON55795.2022.9870159

C. Sudhamani, M. Roslee, L. L. Chuan, A. Waseem, A. F. Osman, and M. H. Jusoh, “Performance Analysis of a Millimeter Wave Communication System in Urban Micro, Urban Macro, and Rural Macro Environments,†J. Energies, vol. 16, no. 14, p. 5358, 2023. https://doi.org/10.3390/en16145358

H. Kou, “Wireless Communication System and Its Application in Big Data Remote Monitoring and Decision-Making,†vol. 2022, p. 10, 2022. https://doi.org/10.1155/2022/8161917

W. Yu, F. Sohrabi, and T. Jiang, “Role of Deep Learning in Wireless Communications,†vol. 2, no. 2, pp. 56–72, 2022. https://doi.org/10.1109/MBITS.2022.3212978

M. Chai and J. Yang, “Parameter estimation of network signal normal distribution applied to carbonization depth in wireless networks,†EURASIP J. Wirel. Commun. Netw., vol. 2020, no. 1, pp. 1–15. https://doi.org/10.1186/s13638-020-01694-5

F. Yilmaz, M. O. Hasna, and K. Qaraqe, “Alternative expressions of the PDF and CDF for Gamma, η−μ and κ−μ shadowed distributions,†Phys. Commun., vol. 56, 2023. https://doi.org/10.1016/j.phycom.2022.10

J. W. Browning, S. L. Cotton, D. Morales-Jimenez, and D. Morales-Jimenez, “The Rician Complex Envelope Under Line of Sight Shadowing,†IEEE Commun. Lett., vol. 12, no. 2182–2186, 2019. https://doi.10.1109/LCOMM.2019.2939304.

A. T. Adeniran, O. Faweya*, T. O. Ogunlade, and K. O. Balogun, “Derivation of Gaussian Probability Distribution: A New Approach,†Appl. Math., vol. 11, no. 6, pp. 436–446, 2020. https:// doi.10.1109/LCOMM.2019.2939304.

A. Dmitriev, A. Ryzhov, and C. Sierra-Teran, “Statistical Characteristics of Differential Communication Scheme Based on Chaotic Radio Pulses,†Electron. 2023, vol. 12, no. 6, p. 1495, 2023. https://doi.org/10.3390/electronics12061495

Y. Chen, D. Zhang, and Q. Zhu, “Markov chain modelling of ordered Rayleigh fading channels in non-orthogonal multiple access wireless networks,†IET Signal Process., vol. 17, no. 3, p. 11, 2023. https://doi.org/10.1049/sil2.12191

H. M. Almongy, E. M. Almetwally, H. M. Aljohani, A. S. Alghamdi, and E. H. Hafez, “A new extended rayleigh distribution with applications of COVID-19 data,†Results Phys., vol. 23, pp. 1–9, 2021. https://doi.org/10.1016/j.rinp.2021.104012

S. Mendonça, B. Damásio, L. C. de Freitas, L. Oliveira, M. Cichy, and A. Nicita, “The rise of 5G technologies and systems: A quantitative analysis of knowledge production,†Sci. Direct, vol. 46, no. 4, p. 102327, 2022. https://doi.org/10.1016/j.telpol.2022.102327

D. Bajoivć, B. Sinopoli, and Joã, “Sensor selection for hypothesis testing in wireless sensor networks: a Kullback-Leibler based approach,†in IEEE Conference on Decision and Control, 2009, pp. 1659–1664. https://doi.10.1109/CDC.2009.5400743

D. Passos, F. G. O. Passos, B. dos S. Silva, and C. Albuquerque, “Modeling the performance of the link quality hypothesis test estimator mechanism in wireless networks,†Wirel. Networks, vol. 27, pp. 4065–4081, 2021. https://doi.org/10.1080/03610926.2021.1977961

M. Walter and M. Schnell, “Statistical distribution of line-of-sight and reflected path in the aeronautical channel,†in 2011 IEEE/AIAA 30th Digital Avionics Systems Conference, 2011, pp. 4D1-1-. https://doi.org/10.1109/DASC.2011.6095909

M. Saculinggan and E. A. Balase, “Empirical Power Comparison Of Goodness of Fit Tests for Normality In The Presence of Outliers,†J. Phys. Conf. Ser., vol. 435, 2013.https://doi. 10.1088/1742-6596/435/1/012041

J. Xia et al., “Performance Analysis of Normality Test Loss for Intelligent RSCNN Denoiser Design With Application to Channel Decoding,†in 2022 IEEE/CIC International Conference on Communications in China (ICCC), 2022, pp. 748–753. https://doi.org/10.1109/ICCC55456.2022.9880755

“Hypothesis testing for the inverse Gaussian distribution mean based on ranked set sampling,†vol. 90, no. 13, pp. 2384–2394. https://doi.org/10.1080/00949655.2020.1777294

S. Bonovas and D. Piovani, “On p-Values and Statistical Significance,†J. Clin. Med., vol. 12, no. 3, p. 900, 2023. https://doi.org/10.3390/jcm12030900

M. Tsagris and N. Pandis, “Normality test: Is it necessary?,†Stat. Res. Des., vol. 159, no. 4, pp. 548–549, 2021. https://doi.org/10.1016/j.ajodo.2021.01.003

K. Ota;, Q. Wu;, P. Mamassian;, and L. Maloney, “Visual cue estimation with non-gaussian distribution,†J. Vis., vol. 20, no. 11, p. 1436, 2020. https://doi.org/10.1167/jov.20.11.1436

J. Rodu and K. Kafadar, “The q–q Boxplot,†J. Comput. Graph. Stat., vol. 31, no. 1, pp. 26–39, 2022. https://doi.org/10.1080/10618600.2021.1938586

A. K. Yadav, K. Singh, and P. K. Srivastava, “Probabilistic Estimation of Comprehensive Utility Based on User Preference and Network Condition for Network Selection in Future in HetNet,†J. Supercomput., 2023. https://doi.org/10.1007/s11227-023-05595-4

E. Björnson; and L. Sanguinetti, “Rayleigh Fading Modeling and Channel Hardening for Reconfigurable Intelligent Surfaces,†IEEE Wirel. Commun. Lett., vol. 10, no. 4, pp. 830–834, 2020. https://doi.org/10.1109/LWC.2020.3046107

L. Klozar and J. Prokopec, “Propagation path loss models for mobile communication,†Proc. 21st Int. Conf. Radioelektronika 2011, no. 2, pp. 1–4, Apr. 2011. https://doi.org/10.1109/RADIOELEK.2011.5936478




DOI: http://dx.doi.org/10.18517/ijaseit.13.6.19048

Refbacks

  • There are currently no refbacks.


Published by INSIGHT - Indonesian Society for Knowledge and Human Development