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Rain fade margin of terrestrial line-of-sight (LOS) links for 5G networks in Peninsular Malaysia

Published online by Cambridge University Press:  19 May 2021

Shi Jie Seah ,
Siat Ling Jong Open the ORCID record for Siat Ling Jong [Opens in a new window] ,
Hong Yin Lam  and
Jafri Din
Shi Jie Seah
Affiliation:
Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia
Siat Ling Jong*
Affiliation:
Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia
Hong Yin Lam
Affiliation:
Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia, 84600 Hub Pendidikan Tinggi Pagoh, Km 1, Jalan Panchor, Johor, Malaysia
Jafri Din
Affiliation:
Wireless Communication Center, School of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Malaysia
*
Author for correspondence: Siat Ling Jong, E-mail: [email protected]
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Abstract

Advanced telecommunication systems are moving toward a high data transfer rate and wider bandwidth. The 5G communication network has recently been implemented for such aims. However, 5G networks operating with high operating frequency (typically above 20 GHz) could lead to impairments because of the atmospheric phenomena mainly precipitation and especially heavy rain. To address this, an optimum rain fade margin for the 5G network in Peninsular Malaysia is proposed using 77 sites of the rain-gauge network, which convert 1-h rain data to 1-min rain data by means of the international telecommunication union recommendation (ITU-R) P.837-7 model. Long-term rain attenuation statistics are obtained from ITU-R P.530-17 and the synthetic storm technique. The predicted rain attenuation is also presented in monthly statistics and in rain attenuation contour maps. The analysis showed that at 99.99% of link availability, the optimum rain fade margin operating at 26 GHz link should be in the range of 6.50 to 10 dB and 7 to 11 dB at 28 GHz link for a 5G network. Such information is useful for network operators and system engineers for the operation of 5G terrestrial microwave links in heavy rain regions.

Keywords

Fade marginrain attenuationattenuation map5G
Type
EM Field Theory
Information
International Journal of Microwave and Wireless Technologies , Volume 14 , Special Issue 6: EuCAP 2020 Special Issue , July 2022 , pp. 750 - 760
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press in association with the European Microwave Association

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References

Ghosh, A, Maeder, A, Baker, M and Chandramouli, D (2019) 5G evolution: a view on 5G cellular technology beyond 3GPP release 15. IEEE Access 7, 127639–127651.CrossRefGoogle Scholar
Andrews, JG, Buzzi, S, Choi, W, Hanly, SV, Lozano, A, Soong, ACK and Zhang, JC (2014) What will 5G be? IEEE Journal on Selected Areas in Communications 32, 1065–1082.CrossRefGoogle Scholar
Vora, MLJ (2015) Evolution of mobile generation technology : 1G to 5G and review of upcoming wireless technology 5G. International Journal of Modern Trends in Engineering and Research 2, 281–290.Google Scholar
Matricciani, E (1996) Physical-mathematical model of the dynamics of rain attenuation based on rain rate time series and a two-layer vertical structure of precipitation. Radio Science 31, 281–295.CrossRefGoogle Scholar
Mandeep, JS (2009) Rain attenuation statistics over a terrestrial link at 32.6 GHz at Malaysia. IET Microwaves, Antennas & Propagation 3, 1086–1093.CrossRefGoogle Scholar
Capsoni, C and Luini, L (2013) The SC EXCELL model for prediction of rain attenuation on terrestrial radio links. Electronics Letters 49, 307–308.Google Scholar
Luini, L and Capsoni, C (2011) MultiEXCELL: a new rain field model for propagation applications. IEEE Transactions on Antennas and Propagation 59, 4286–4300.CrossRefGoogle Scholar
Lam, HY, Luini, L, Din, J, Capsoni, C and Panagopoulos, AD (2012) Investigation of rain attenuation in equatorial Kuala Lumpur. IEEE Antennas and Wireless Propagation Letters 11, 1002–1005.CrossRefGoogle Scholar
Yunus, MM, Din, J, Jong, SL and Lam, HY (2018) Slant path Ka-band rain attenuation statistics in equatorial Malaysia obtained using stratiform convective- synthetic storm technique. International Journal of Engineering & Technology 7, 22–25.CrossRefGoogle Scholar
Chebil, J and Rahman, TA (1999) Development of 1 min rain rate contour maps for microwave applications in Malaysia Peninsula. Electronics Letters 35, 1772–1774.CrossRefGoogle Scholar
Capsoni, C and Luini, L (2008) 1-min rain rate statistics predictions from 1-hour rain rate statistics measurements. IEEE Transactions on Antennas and Propagation 56, 815–824.CrossRefGoogle Scholar
Capsoni, C and Luini, L (2013) The SC EXCELL model for the prediction of monthly rain attenuation statistics. In 7th European Conference on Antennas and Propagation (EuCAP), 1382–1385.Google Scholar
Shrestha, S and Choi, DY (2017) Rain attenuation over terrestrial microwave links in South Korea. IET Microwaves Antennas & Propagation 11, 1031–1039.CrossRefGoogle Scholar
Lu, CS, Zhao, ZW, Wu, ZS, Lin, LK, Thiennviboon, P, Zhang, X and Lv, ZF (2018) A new rain attenuation prediction model for the earth-space links. IEEE Transactions on Antennas and Propagation 66, 5432–5442.CrossRefGoogle Scholar
ITU-R P.837-7 (2017) Characteristics of precipitation for propagation modelling. Recommendation ITU-R.Google Scholar
Goldberg, DE (1989) Genetic Algorithms in Search, Optimization & Machine Learning. Boston, MA: Addison-Wesley.Google Scholar
Chebil, J and Rahman, TA (1999) Rain rate statistical conversion for the prediction of rain attenuation in Malaysia. Electronics Letters 35, 1019–1021.CrossRefGoogle Scholar
ITU-R P.530-17. (2017) Propagation data and prediction methods required for the design of terrestrial line-of-sight systems. Recommendation ITU-R, 1–24.Google Scholar
ITU-R P.838-3. (2005) Specific attenuation model for rain for use in prediction methods, 1–8.Google Scholar
Jong, SL, Riva, C, D'Amico, M, Lam, HY, Yunus, MM and Din, J (2018) Performance of synthetic storm technique in estimating fade dynamics in equatorial Malaysia. International Journal of Satellite Communications and Networking 36, 416–426.CrossRefGoogle Scholar
ITU-R P.311-17. (2017) Acquisition, Presentation and Analysis of Data in Studies of Radiowave Propagation. Recommendation ITU-R.Google Scholar
ITU-R. (2016) Fascicle on testing variables used for the selection of prediction methods, 1–6.Google Scholar
Lam, HY, Luini, L, Din, J, Alhilali, MJ, Jong, SL and Cuervo, F (2017). Impact of rain attenuation on 5G millimeter wave communication systems in equatorial Malaysia investigated through disdrometer data. In 2017 11th European Conference on Antennas and Propagation, EUCAP 2017, 1793–1797.CrossRefGoogle Scholar
Capsoni, C and Luini, L (2009) A physically based method for the conversion of rainfall statistics from long to short integration time. IEEE Transactions on Antennas and Propagation 57, 3692–3696.CrossRefGoogle Scholar
Rappaport, TS, Sun, S, Mayzus, R, Zhao, H, Azar, Y, Wang, K and Gutierrez, F (2013) Millimeter wave mobile communications for 5G cellular: it will work!. IEEE Access 1, 335–349.CrossRefGoogle Scholar