Outage Performances of 5G Channel Model Influenced by Barometric Pressure Effects in Yogyakarta

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Solichah Larasati
Serli Ridho Yuliani
Achmad Rizal Danisya


Abstract — The fifth-generation cellular technology (5G) is predicted to adopt a high-frequency channel, which could lead to a new challenge, namely, wave propagation attenuation. This attenuation is affected by natural conditions, such as barometric pressure, rain rate, humidity, and vegetation density. This paper proposes a 5G channel model under the barometric pressure effect to address the issue. The channel model is obtained from series computer simulations by operating frequency of 28 GHz and real-field parameters of Yogyakarta environments. The 5G channel model frameworks consist of two steps. First, generate the instantaneous Power Delay Profile (PDP) using NYU Wireless Simulator with real-field parameters of the environment. Second, the instantaneous PDP is then used to calculate the representative PDP. PDP differs from one country to another, especially on 5G technology, because of the high-frequency band, which is sensitive to nature. To observe the barometric pressure effect, we need to generate the instantaneous PDP with minimum and maximum barometric effects. PDP value used to calculate the outage probability of channel capacity (C) is smaller than the coding rate (R), indicating a failure of detection at the receiver based on the Shannon theory. Outage probability is obtained by the cumulative distribution function of the capacity evaluated against the coding rate. Outage probability results in both scenarios can reach a point of 10-4, for coding rate ½ needs 17.649883 dB, coding rate ¾ needs 20.020953 dB, and coding rate 1 needs 22 dB. This shows that barometric does not significantly influence the performance of the 5G communication system.


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How to Cite
S. Larasati, S. R. Yuliani, and A. R. Danisya, “Outage Performances of 5G Channel Model Influenced by Barometric Pressure Effects in Yogyakarta”, INFOTEL, vol. 12, no. 1, pp. 25-31, Apr. 2020.


[1] E. Wijanto, “Analysis of technology readiness for the implementation of fifth generation (5G) telecommunications technology,” vol. 06, no. 23, pp. 13, 2017.
[2] A. F. S. Admaja, “Kajian awal 5G Indonesia (5G Indonesia early preview),” Bul. Pos Dan Telekomun., vol. 13, no. 2, pp. 97, Dec. 2015, doi: 10.17933/bpostel.2015.130201.
[3] H. Mehta, D. Patel, B. Joshi, and H. Modi, “0G to 5G mobile technology: a survey,” vol. 1, no. 6, pp. 6, 2014.
[4] “IMT Vision – Framework and overall objectives of the future development of IMT for 2020 and beyond,” pp. 21.
[5] T. A. Nugraha and A. Hikmaturokhman, “Simulasi penggunaan frekuensi milimeter wave untuk akses komunikasi jaringan 5G Indoor,” pp. 7, 2017.
[6] K. Haneda et al., “5G 3GPP-like channel models for outdoor urban microcellular and macrocellular environments,” in 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring), Nanjing, 2016, pp. 1–7, doi: 10.1109/VTCSpring.2016.7503971
[7] GSMA, “Road-to-5G-introduction-and-migration_FINAL,” pp. 54, Apr. 2018.
[8] S. J. Dudzinsky, “Atmospheric effects on terrestrial millimeter-wave communications,” in 4th European Microwave Conference, 1974, Montreux, Switzerland, 1974, pp. 197–201, doi: 10.1109/EUMA.1974.332040
[9] A. Goldsmith, Wireless Communications. Stanford University, 2005.
[10] E. M. Alfaroby, N. M. Adriansyah, and K. Anwar, “Study on channel model for Indonesia 5G networks,” in 2018 International Conference on Signals and Systems (ICSigSys), Bali, 2018, pp. 125–130, doi: 10.1109/ICSIGSYS.2018.8372650
[11] A. Hikmaturokhman, M. Suryanegara and K. Ramli, "A comparative analysis of 5G channel model with varied frequency: a case study in Jakarta," 2019 7th International Conference on Smart Computing & Communications (ICSCC), Sarawak, Malaysia, Malaysia, 2019, pp. 1-5.
[12] A. University, ATT, BUPT, CMCC, Ericsson, Huawei, INTEL, K. Corporation, Nokia, N. DOCOMO, N. Y. University, Qualcomm, Samsung, U. of Bristol, and U. of Southern California, "5G channel model for bands up to 100 GHz, "Tech. Rep., 2016.
[13] V. Nurmela, A. Karttunen, A. Roivainen, L. Raschkowski, T. Imai, J. Jrvelinen, J. Medbo, J. Vihril, J. Meinil, K. Haneda, V. Hovinen, J. Ylitalo, N. Omaki, K. Kusume, P. Kysti, T. Jms, A. Hekkala, R. Weiler, and M. Peter, "METIS channel models," METIS, Tech. Rep., 2015.
[14] ETSI, "New ETSI group on millimetre wave transmission starts work," ETSI, Tech. Rep.,2015.
[15] NIST, "5G milimeter wave channel model," NIST, Tech. Rep.,2016.
[16] mmMagic, "The european 5G annual journal," 5GPPP, Tech. Rep., 2017.
[17] K. Anwar, E. Christy, and R. P. Astuti, “Indonesia 5G channel model under foliage effect [model kanal 5G Indonesia dengan pengaruh dedaunan],” Bul. Pos Dan Telekomun., vol. 17, no. 2, pp. 75, Dec. 2019, doi: 10.17933/bpostel.2019.170201.
[18] X. He, X. Zhou, K. Anwar, and T. Matsumoto, "Estimation of observation error probability in wireless sensor networks", IEEE Communications Letters, vol.17, no.6, pp. 1073-1076, June 2013.