Two-stage Channel Frequency Response Estimation in OFDM Systems

Oleksandr Myronchuk, Oleksandr Shpylka, Serhii Zhuk

Abstract

This paper proposes two-stage channel frequency response estimation algorithm in communication systems with OFDM technology. Algorithm is based on Kalman filter. Pilots from current and previous OFDM symbols are used for channel estimation. At the first stage data is processed in time and frequency directions. Pilots from the current OFDM symbol are filtered and at the position, where the pilots from the previous OFDM symbols should be placed, predictions are made. Predictions are based on the pilots and channel correlation characteristics. The data processing carried out on both sides relative to the array of processed data in frequency direction and on one side at processing in time direction. The results of processing are optimally combined at the second stage. The autoregressive process was used as a channel model. The analysis of the developed algorithm carried out on a model example by statistical modeling. Modeling showed that application of designed algorithm allows reducing the standard deviation of the estimation error of channel frequency response. The efficiency of designed algorithm studied using Rayleigh channel with Doppler spectrum described by Jakes model. The autocorrelation characteristics of the channel were considered as known. Modeling showed a decrease in the probability of a bit error during reception using the proposed algorithm. It is also shown that an increase in the order of the autoregressive model reduces the error in estimating the frequency response of the communication channel.



Keywords


OFDM; wireless channel; channel frequency response; channel estimation; autoregressive process; Kalman filter

Full Text:

PDF


References


Rohling, H. (Ed.). (2011). OFDM. Signals and Communication Technology. doi: 10.1007/978-3-642-17496-4

Shpylka, A. A., & Zhuk, S. Y. (2010). Joint interpolation of data and parameter filtration of a multibeam communications channel. Radioelectronics and Communications Systems, 53(1), 20–24. doi: 10.3103/s0735272710010048

Chiueh, T.-D., Tsai, P.-Y., & Lai, I.-W. (2012). Baseband Receiver Design for Wireless MIMO-OFDM Communications (2nd ed.). Singapore: John Wiley & Sons.

Shen, Y., & Martinez, E. (2006). Channel estimation in ofdm systems. Retrieved from https://pdfs.semanticscholar.org/bb01/a1cf553eeb6d9101b77d0ebe92fb44172347.pdf?_ga=2.176146658.1983668023.1582973234-1042230176.1581878685

Van de Beek, J.-J., Edfors, O., Sandell, M., Wilson, S. K., & Borjesson, P. O. (n. d.). On channel estimation in OFDM systems. 1995 IEEE 45th Vehicular Technology Conference. Countdown to the Wireless Twenty-First Century. doi: 10.1109/vetec.1995.504981

Fazel, K., & Kaiser, S. (2009). Multi-carrier and spread spectrum systems: from OFDM and MC-CDMA to LTE and WiMAX (2nd ed.). Hoboken: John Wiley & Sons.

Myronchuk, A. Y., Shpylka, O. O., & Zhuk, S. Y. (2019). Channel frequency response estimation method based on pilot’s filtration and extrapolation. Visnyk NTUU KPI Seriia – Radiotekhnika Radioaparatobuduvannia, 78, 36–42. doi: 10.20535/radap.2019.78.36-42

Ki-Young Han, Sang-Wook Lee, Jun-Seok Lim, & Koeng-Mo Sung. (2004). Channel estimation for OFDM with fast fading channels by modified Kalman filter. IEEE Transactions on Consumer Electronics, 50(2), 443–449. doi: 10.1109/tce.2004.1309406

Huang, M., Chen, X., Xiao, L., Zhou, S., & Wang, J. (2007). Kalman-filter-based channel estimation for orthogonal frequency-division multiplexing systems in timevarying channels. IET Communications, 1(4), 795–801.

Wei Chen, & Ruifeng Zhang. (n.d.). Kalman-filter channel estimator for OFDM systems in time and frequency-selective fading environment. 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing. doi: 10.1109/icassp.2004.1326842

Vishnevyy, S. V., & Zhuk, S. Y. (2011). Two-stage mutual causal filtration and segmentation of heterogeneous images. Radioelectronics and Communications Systems, 54(1), 37–44. doi: 10.3103/s0735272711010067

Favorskaya, M., & Jain, L. (2020). Computer Vision in Advanced Control Systems-5: Advanced Decisions in Technical and Medical Applications. Cham: Springer International Publishing.

Jakes, W. C. (Ed). (1994). Microwave Mobile Communications. New York: IEEE Press.


Article Metrics

Metrics Loading ...

Metrics powered by PLOS ALM

Refbacks

  • There are currently no refbacks.




Copyright (c) 2020 Oleksandr Myronchuk, Oleksandr Shpylka, Serhii Zhuk

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.