mm-Dalga Kanallarındaki Yol Kaybı Modelleri Üzerine Kısa Bir Derleme

Yıl 2021, Sayı: 29, 264 - 272, 01.12.2021

Nermin Hamdan , Begüm Korunur Engiz

https://doi.org/10.31590/ejosat.1022696

Öz

Yüksek bant genişliğine ve buna bağlı olarak yüksek hızlı veri iletişimine olanak tanıması nedeniyle milimetre dalga (mm-dalga) haberleşmesinin 5. Nesil (5G) haberleşme sistemlerinde kullanılması planlanmaktadır. Yol kaybı, mm-dalga haberleşmesinde sistem başarımını etkileyen en önemli faktörlerden biridir. Bu nedenle etkin ve güvenilir mm-dalga haberleşme sistemini oluşturmak, yüksek veri hızları elde etmek için yol kaybı dikkate alınmalıdır. mm-dalga haberleşme kanalının yayılım özelliklerinin ve yol kaybı modellerinin doğru bir biçimde belirlenmesi 5G sistemleri için oldukça önemlidir. 5G sistemlerininde, yol kaybını yüksek doğruluk ve hassasiyetle tahmin etmek için literatürde birçok yöntem önerilmiştir. Bu derleme çalışmasında araştırmacılara, 5G mm-dalga haberleşme sistemlerinde yol kaybı hakkında bilgi sağlamak hedeflenmiştir. 2018-2021 yılları arasında yapılmış, makine öğrenmesi, derin öğrenme, sinir ağları ve yayılım ölçümü yaklaşımına dayanan birçok çalışma sunulmuş, CI, ABG veya FI gibi temel yol kaybı modellerini, 5G’de üç boyutlu ışın izleme yöntemlerini inceleyen çalışmalar açık ve anlaşılır bir biçimde özetlenmiştir.

Anahtar Kelimeler

mm-dalga, 5. Nesil, Yol kaybı modelleri, Yayılım ölçümleri

A Brief Review of Path Loss Models for mmWave Channels

Öz

It is planned to use millimeter wave (mm-wave) communication in 5th Generation (5G) communication systems, as it allows high bandwidth and accordingly high speed data communication. Path loss is one of the most important factors affecting system performance in mm-wave communication. Therefore, path loss must be taken into account in order to create an efficient and reliable mm-wave communication system and to obtain high data rates. It is very important for 5G systems to accurately determine the propagation characteristics and path loss models of the mm-wave communication channel. Many methods have been proposed in the literature to predict path loss with high accuracy and precision in 5G systems. In this review, it is aimed to provide researchers a clear knowledge about path loss in 5G mm-wave communication systems. Papers published between 2018-2021 which based on machine learning, deep learning, neural networks and propagation measurement approach were presented, and the main results of researches related to main path loss models Close-in (CI), and Alpha, Beta, Gamma (ABG) or Floating Intercept (FI) and papers that discussed 3-D ray tracing method were summarized in clear and precise manner.

Anahtar Kelimeler

mmWave, 5G, Path loss models, Propagation measurements

Kaynakça

• Adachi, F. (2002, October). Evolution towards broadband wireless systems. In The 5th International Symposium on Wireless Personal Multimedia Communications (Vol. 1, pp. 19-26). IEEE.
• Osseiran, A., Boccardi, F., Braun, V., Kusume, K., Marsch, P., Maternia, M., et al. (2014). Scenarios for 5G mobile and wireless communications: the vision of the METIS project. IEEE communications magazine, 52(5), 26-35.
• Narekar, N. P., & Bhalerao, D. M. (2015, April). A survey on obstacles for 5G communication. In 2015 International Conference on Communications and Signal Processing (ICCSP) (pp. 0831-0835). IEEE.
• Mitra, R. N., & Agrawal, D. P. (2015). 5G mobile technology: A survey. ICT express, 1(3), 132-137.
• Niu, Y., Li, Y., Jin, D., Su, L., & Vasilakos, A. V. (2015). A survey of millimeter wave communications (mmWave) for 5G: opportunities and challenges. Wireless networks, 21(8), 2657-2676.
• Uwaechia, A. N., & Mahyuddin, N. M. (2020). A comprehensive survey on millimeter wave communications for fifth-generation wireless networks: Feasibility and challenges. IEEE Access, 8, 62367-62414.
• Al-Saman, A., Cheffena, M., Elijah, O., Al-Gumaei, Y. A., Abdul Rahim, S. K., & Al-Hadhrami, T. (2021). Survey of millimeter-wave propagation measurements and models in indoor environments. Electronics, 10(14), 1653.
• Rappaport, T. S., Xing, Y., MacCartney, G. R., Molisch, A. F., Mellios, E., & Zhang, J. (2017). Overview of millimeter wave communications for fifth-generation (5G) wireless networks—With a focus on propagation models. IEEE Transactions on antennas and propagation, 65(12), 6213-6230.
• Sun, S., Rappaport, T. S., Rangan, S., Thomas, T. A., Ghosh, A., Kovacs, I. Z., et al. (2016, May). Propagation path loss models for 5G urban micro-and macro-cellular scenarios. In 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring) (pp. 1-6). IEEE.
• Zhang, Y., Wen, J., Yang, G., He, Z., & Wang, J. (2019). Path loss prediction based on machine learning: Principle, method, and data expansion. Applied Sciences, 9(9), 1908.
• Thrane, J., Zibar, D., & Christiansen, H. L. (2020). Model-aided deep learning method for path loss prediction in mobile communication systems at 2.6 GHz. Ieee Access, 8, 7925-7936.
• Cheng, H., Ma, S., & Lee, H. (2020). CNN-based mmWave path loss modeling for fixed wireless access in suburban scenarios. IEEE Antennas and Wireless Propagation Letters, 19(10), 1694-1698.
• Sotiroudis, S. P., Sarigiannidis, P., Goudos, S. K., & Siakavara, K. (2021). Fusing diverse input modalities for path loss prediction: A deep learning approach. IEEE Access, 9, 30441-30451.
• Nguyen, C., & Cheema, A. A. (2021). A Deep Neural Network-Based Multi-Frequency Path Loss Prediction Model from 0.8 GHz to 70 GHz. Sensors, 21(15), 5100.
• Juang, R. T. (2021). Explainable Deep-Learning-Based Path Loss Prediction from Path Profiles in Urban Environments. Applied Sciences, 11(15), 6690.
• Cheng, H., Ma, S., Lee, H., & Cho, M. (2021). Millimeter Wave Path Loss Modeling for 5G Communications Using Deep Learning With Dilated Convolution and Attention. IEEE Access, 9, 62867-62879.
• Sun, S., MacCartney, G. R., & Rappaport, T. S. (2017, May). A novel millimeter-wave channel simulator and applications for 5G wireless communications. In 2017 IEEE International Conference on Communications (ICC) (pp. 1-7). IEEE.
• Hasan, R., Mowla, M. M., Rashid, M. A., Hosain, M. K., & Ahmad, I. (2019, February). A statistical analysis of channel modeling for 5g mmwave communications. In 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) (pp. 1-6). IEEE.
• Lodro, M. M., Majeed, N., Khuwaja, A. A., Sodhro, A. H., & Greedy, S. (2018, March). Statistical channel modelling of 5G mmWave MIMO wireless communication. In 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) (pp. 1-5). IEEE.
• Fiandrino, C., Assasa, H., Casari, P., & Widmer, J. (2019). Scaling millimeter-wave networks to dense deployments and dynamic environments. Proceedings of the IEEE, 107(4), 732-745.
• Lin, Z., Du, X., Chen, H. H., Ai, B., Chen, Z., & Wu, D. (2019). Millimeter-wave propagation modeling and measurements for 5G mobile networks. IEEE Wireless Communications, 26(1), 72-77.
• Saba, N., Mela, L., Sheikh, M. U., Ruttik, K., Salo, J., & Jäntti, R. (2021, April). Measurements at 5G Commercial 26 GHz Frequency with Above and on Rooftop Level Antenna Masts in Urban Environment. In 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) (pp. 1-5). IEEE.
• Pimienta-del-Valle, D., Mendo, L., Riera, J. M., & Garcia-del-Pino, P. (2020). Indoor LOS Propagation Measurements and Modeling at 26, 32, and 39 GHz Millimeter-Wave Frequency Bands. Electronics, 9(11), 1867.
• Pimienta-del-Valle, D., Hernández-Sáenz, S., Sáiz-Coronado, P., Mendo, L., Garcia-del-Pino, P., & Riera, J. M. (2019, March). Indoor path loss measurements at the 5G millimeter-wave bands of 26 and 39 GHz. In 2019 13th European Conference on Antennas and Propagation (EuCAP) (pp. 1-5). IEEE.
• Al-Samman, A. M., Rahman, T. A., Azmi, M. H., & Hindia, M. N. (2016). Large-scale path loss models and time dispersion in an outdoor line-of-sight environment for 5G wireless communications. AEU-International Journal of Electronics and Communications, 70(11), 1515-1521.
• Al-Samman, A. M., Rahman, T. A., Azmi, M. H., Sharaf, A., Yamada, Y., & Alhammadi, A. (2018, March). Path loss model in indoor environment at 40 GHz for 5G wireless network. In 2018 IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA) (pp. 7-12). IEEE.
• Al-Samman, A. M., Azmi, M. H., Al-Gumaei, Y. A., Al-Hadhrami, T., Fazea, Y., & Al-Mqdashi, A. (2020). Millimeter wave propagation measurements and characteristics for 5G system. Applied Sciences, 10(1), 335.
• Liu, J., Matolak, D. W., Mohsen, M., & Chen, J. (2019, September). Path loss modeling and ray-tracing verification for 5/31/90 GHz indoor channels. In 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall) (pp. 1-6). IEEE.
• Qamar, F., Siddiqui, M. H. S., Hindia, M. N., Dimyati, K., Abd Rahman, T., & Talip, M. S. A. (2018, November). Propagation Channel Measurement at 38 GHz for 5G mm-wave communication Network. In 2018 IEEE student conference on research and development (SCOReD) (pp. 1-6). IEEE.
• Oyie, N. O., & Afullo, T. J. O. (2018, August). An Empirical Approach to Omnidirectional Path Loss and Line-of-sight Probability Models at 18 GHz for 5G Networks. In 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama) (pp. 129-136). IEEE.
• Al-Samman, A. M., Rahman, T. A., Azmi, M. H., & Al-Gailani, S. A. (2018). Millimeter-wave propagation measurements and models at 28 GHz and 38 GHz in a dining room for 5G wireless networks. Measurement, 130, 71-81.
• Hindia, M. N., Al-Samman, A. M., Rahman, T. A., & Yazdani, T. M. (2018). Outdoor large-scale path loss characterization in an urban environment at 26, 28, 36, and 38 GHz. Physical Communication, 27, 150-160.
• Qamar, F., Hindia, M. N., Abd Rahman, T., Hassan, R., Dimyati, K., & Nguyen, Q. N. (2021). Propagation characterization and analysis for 5G mmWave through field experiments. CMC-COMPUTERS MATERIALS & CONTINUA, 68(2), 2249-2264.
• Al-Samman, A. M., Abd Rahman, T., HINDIA, M. N., & Nasir, J. (2018). Path loss model for indoor emergency stairwell environment at millimeter wave band for 5G network. Turkish Journal of Electrical Engineering & Computer Sciences, 26(6), 3024-3032.
• Aldhaibani, A. O., Rahman, T. A., & Alwarafy, A. (2020). Radio-propagation measurements and modeling in indoor stairwells at millimeter-wave bands. Physical Communication, 38, 100955.
• Shen, Y., Shao, Y., Xi, L., Zhang, H., & Zhang, J. (2021). Millimeter-Wave Propagation Measurement and Modeling in Indoor Corridor and Stairwell at 26 and 38 GHz. IEEE Access, 9, 87792-87805.
• Nagatomo, S., & Omiya, M. (2021, January). Prediction of 28 GHz Propagation Characteristics in an Indoor Office Environment Based on Large-scale Computer Simulations. In 2020 International Symposium on Antennas and Propagation (ISAP) (pp. 311-312). IEEE.
• Li, S., Liu, Y., Lin, L., Sun, D., Yang, S., & Sun, X. (2018, March). Simulation and modeling of millimeter-wave channel at 60 GHz in indoor environment for 5G wireless communication system. In 2018 IEEE International Conference on Computational Electromagnetics (ICCEM) (pp. 1-3). IEEE.
• Al-Saman, A., Mohamed, M., & Cheffena, M. (2020). Radio propagation measurements in the indoor stairwell environment at 3.5 and 28 GHz for 5G wireless networks. International Journal of Antennas and Propagation, 2020.
• Oyie, N. O., & Afullo, T. J. (2018). Measurements and analysis of large-scale path loss model at 14 and 22 GHz in indoor corridor. IEEE Access, 6, 17205-17214.
• Oyie, N. O., & Afullo, T. J. O. (2018, August). A Comparative Study of Dual-Slope Path Loss Model in Various Indoor Environments at 14 to 22 GHz. In 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama) (pp. 121-128). IEEE.
• Al-Samman, A. M., Abd Rahman, T., & Azmi, M. H. (2018). Indoor corridor wideband radio propagation measurements and channel models for 5g millimeter wave wireless communications at 19 GHz, 28 GHz, and 38 GHz bands. Wireless Communications and Mobile Computing, 2018.
• Qamar, F., Hindia, M. H. D., Dimyati, K., Noordin, K. A., Majed, M. B., Abd Rahman, T., & Amiri, I. S. (2019). Investigation of future 5G-IoT millimeter-wave network performance at 38 GHz for urban microcell outdoor environment. Electronics, 8(5), 495.
• Rubio, L., Torres, R. P., Rodrigo Peñarrocha, V. M., Pérez, J. R., Fernández, H., Molina-Garcia-Pardo, J. M., & Reig, J. (2019). Contribution to the channel path loss and time-dispersion characterization in an office environment at 26 GHz. Electronics, 8(11), 1261.
• Al-Samman, A. M., Al-Hadhrami, T., Daho, A., Hindia, M. H. D., Azmi, M. H., Dimyati, K., & Alazab, M. (2019). Comparative study of indoor propagation model below and above 6 GHz for 5G wireless networks. Electronics, 8(1), 44.
• Majed, M. B., Rahman, T. A., Aziz, O. A., Hindia, M. N., & Hanafi, E. (2018). Channel characterization and path loss modeling in indoor environment at 4.5, 28, and 38 GHz for 5G cellular networks. International Journal of Antennas and Propagation, 2018.
• Hossain, F., Geok, T. K., Rahman, T. A., Hindia, M. N., Dimyati, K., Ahmed, S., ... & Abd Rahman, N. Z. (2019). An efficient 3-D ray tracing method: prediction of indoor radio propagation at 28 GHz in 5G network. Electronics, 8(3), 286.
• Kamboh, U. R., Ullah, U., Khalid, S., Raza, U., Chakraborty, C., & Al-Turjman, F. (2021). Path loss modelling at 60 GHz mmWave based on cognitive 3D ray tracing algorithm in 5G. Peer-to-Peer Networking and Applications, 1-17.
• Sousa, M., Alves, A., Vieira, P., Queluz, M. P., & Rodrigues, A. (2021). Analysis and Optimization of 5G Coverage Predictions Using a Beamforming Antenna Model and Real Drive Test Measurements. IEEE Access, 9, 101787-101808.
• Xu, T., Pan, Z., Zhang, H., Zou, Q., & Bao, C. (2021, June). Modeling and Analysis of Millimeter Wave 5G Cellular Networks Based on 3-D Spatial Model. In Journal of Physics: Conference Series (Vol. 1944, No. 1, p. 012025). IOP Publishing.