Application of a Neural Network for Estimating the Frequency Response of a Multipath Channel in Communication Systems with OFDM Technology
DOI:
https://doi.org/10.31649/1997-9266-2021-157-4-99-104Keywords:
OFDM, digital communication, wireless channel, multipath signal propagation, channel frequency response, channel estimation, neural networkAbstract
In the context of the development of modern technologies, the key role is assigned to the exchange of information. Digital communication systems are at the heart of information technology. To meet the needs of a modern person the requirements for communication systems are constantly increasing. Large information flows require high data rates. At the same time an important task is to reduce the number of errors that occur during data transmission. In OFDM systems, this is achieved by increasing the accuracy of estimating the frequency response of the communication channel. In this paper a neural network of direct propagation is used to estimate the values of the frequency response of the communication channel in OFDM systems. The neural network was designed for conditions when the pilot signals in the OFDM symbol structure are arranged in a combined pattern. Under such conditions the neural network receives noisy values of the frequency response on the pilot subcarriers as input information. Its task is to filter these values from noise and interpolate the values of the frequency response to the data subcarriers. The designed neural network has 32 incoming neurons, 128 outgoing neurons and 2 hidden layers of 8 neurons each. The structure of this neural network was designed with such an approach that the vector of the frequency response of the channel is estimated sequentially by 128 samples with their further combining. The neural network was trained on communication channels with given correlation properties by applying the error backpropagation method. The analysis of the efficiency of the network was carried out by means of statistical modeling using a model example in the Matlab computer-aided design system. The results of estimating the values of the frequency response using a neural network are compared with the results that are given by known methods. The analysis of the efficiency of the neural network showed that it is capable of providing a gain of up to 2 dB in comparison with the method of two-stage estimation of the frequency response estimation for a given model example. The neural network is inferior in the estimation accuracy to the minimum mean square error method, however, it has a lower implementation complexity compared to it.
References
Hermann Rohling, OFDM Concepts of Future Communication Systems, Springer, 2011. https://doi.org/10.1007/978-3-642-17496-42 .
S. I. Piltyay, A. V. Bulashenko, and I. V. Demchenko, “Wireless sensor network connectivity in heterogeneous 5G mobile systems, ” IEEE International Conference on Problems of Infocommunications. Science and Technology, Kharkiv, Ukraine, October 2020, pp. 625-630. http://doi.org/10.1109/PICST51311.2020.9468073 .
S. Piltyay, et al., “Numerical performance of FEM and FDTD Methods for the simulation of waveguide polarizers,” Visnyk NTUU KPI Seriia — Radiotekhnika Radioaparatobuduvannia, vol. 84, pp. 11-21. March 2021. https://doi.org/10.20535/RADAP.2021.84.11-21.
A. V. Bulashenko, S. I. Piltyay, and I. V. Demchenko, “Wave matrix technique for waveguide iris polarizers simulation. Numerical results,” Journal of Nano- and Electronic Physics, vol. 13, no. 3, pp. 03023-1-03023-5, 2021. https://doi.org/10.21272/jnep.3(3).03023 .
S. I. Piltyay, et al., “High performance waveguide polarizer for satellite information systems,” Visnyk Cherkaskogo derzhavnogo tekhnolohichnogo universytetu, no. 4. pp. 14-26, 2020. https://doi.org/10.24025/2306-4412.4.2020.217129.
В. В. Котляров, О. Ю. Мирончук, и О. О. Шпилька, «Математичний опис та формалізація типів спотворень у цифровому каналі зв’язку з OFDM-сигналами,» Вісник НТУУ "КПІ". Серія – Радіотехніка, Радіоапаратобудування, № 66, с. 10-18, 2016. https://doi.org/10.20535/RADAP.2016.66.10-18.
John G. Proakis, Digital Communications, 5th ed., McGraw-Hill Higher Education 2008.
А. А. Шпилька, и С. Я. Жук, «Совместная интерполяция данных и фильтрация параметров многолучевого канала связи,» Известия вузов. Радиоэлектроника, тl. 53, № 1, с. 26-30, 2010. https://doi.org/10.20535/s0021347010010048 .
А. А. Шпилька, и С. Я. Жук, «Совместное оценивание данных и параметров многолучевого канала связи. Современные проблемы радиотехники и телекомуникаций (РТ-2009),» материалы 5-й Междунар. молодежной науч.-техн. конф. Севастопольский нац. технический ун-т, 20-25 апреля 2009 г. Севастополь: Вебер, 2009, 351 с.
J.-J. van de Beek, O. Edfors, M. Sandell, S. Wilson, and P. Borjesson, “On channel estimation in OFDM systems,” іn IEEE 45th Vehicular Technology Conference. Countdown to the Wireless Twenty-First Century, Chicago, 1995, vol. 2, pp. 815-819. https://doi.org/10.1109/VETEC.1995.504981 .
O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. Brjesson, “OFDM channel estimation by singular value decomposition,” IEEE Trans. On Communications, 1998, July, vol. 46, no. 7, pp. 931-939. https://doi.org/10.1109/VETEC.1996.501446 .
Srishtansh Pathak, and Himanshu Sharma, “Channel Estimation in OFDM Systems,” International Journal of Advanced Research in Computer Science and Software Engineering, vol. 3, Issue 3, March 2013.
Tzi-Dar Chiueh, Pei-Yun Tsai, and I-Wei Lai, Baseband Receiver Design for Wireless MIMO-OFDM Communications Second Edition, John Wiley & Sons Singapore Pte. Ltd. 2012.
Y. Shen, and E. Martinez, “Channel estimation in ofdm systems” in Frescale Semiconductor Application Note, 2006.
А. Ю. Мирончук, O. O. Шпилька, и С. Я. Жук, «Метод оценивания частотной характеристики канала а OFDM системах на основе фильтрации и экстраполяции пилот-сигналов,» Вісник НТУУ«КПІ». Серія – Радіотехніка, Радіоапаратобудування, № 78, с. 36-42, 2019. https://doi.org/10.20535/RADAP.2019.78.36-42 .
А. Ю. Мирончук, А. А. Шпилька, и С. Я. Жук, «Метод двухэтапного совместного оценивания информационных символов и частотной характеристики канала в системах связи с OFDM,» Известия вузов, Радиоэлектроника, vol. 63, no. 8, pp. 497-508, 2020, https://doi.org/10.20535/S002134702008004X .
O. Myronchuk, O. Shpylka, and S. Zhuk, “Algorithm of channel frequency response estimation in orthogonal frequency division multiplexing systems based on Kalman filter,” in IEEE 15th Int. Conf. on Advanced Trends in Radioelectronics, Telecommunications and omputer Engineering. Lviv-Slavske, 2020. https://doi.org/.1109/TCSET49122.2020.235385 .
О. Ю. Мирончук, и О. О. Шпилька, «Модель Джейкса для спектральної густини потужності і Допплерівського спектру процесу завмирання,» на Міжнародній науково-технічній конференції «Радіотехнічні поля, сигнали, апарати та системи», Київ, 28-24 листопада 2019 р., НТУУ «КПІ ім. І. Сікорського», 2019.
M. M. A. Moustafa and S. H. A. El-Ramly, “Channel estimation and equalization using backpropagation neural networks in OFDM systems,” in 2009 IFIP International Conference on Wireless and Optical Communications Networks, 2009, pp. 1-4. https://doi.org/ 10.1109/WOCN.2009.5010528 .
Ş. Şimşir, and N. Taşpınar, “Channel estimation using neural network in Orthogonal Frequency Division Multiplexing-Interleave Division Multiple Access (OFDM-IDMA) system,” in 2014 International Telecommunications Symposium (ITS), 2014, pp. 1-5. https://doi.org/ 10.1109/ITS.2014.6947977 .
CH. Cheng, YH. Huang, and HC. Chen, “Channel estimation in OFDM systems using neural network technology combined with a genetic algorithm,” Soft Comput., 20, 4139-4148, 2016. https://doi.org/10.1007/s00500-015-1749-7 .
D. D. Strukov, and O. Y. Myronchuk, “Application of neural networks for solving interpolation tasks,” Polit. Callanges of science today. International relations : abstracts of XXI International conference of higher education students and young scientists, National aviation university, Kyiv, 2021. pp. 18-19.
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