© The Institution of Engineering and Technology
In this study, the estimation of fast-fading long term evolution (LTE) downlink channels in high-speed applications of LTE advanced is investigated by the authors. A robust channel estimation and interpolation algorithm is essential in order to adequately track the fast time-varying channel response. In this contribution, the multipath fast-fading channel is modelled as a discrete, tapped-delay and finite impulse response filter. Using support vector machine regression (SVR), they develop an extended algorithm to jointly estimate the complex-valued channel frequency response in time and frequency domains, in the presence of fading and non-linear noise from the transmission of known pilot symbols. Furthermore, the channel estimates at the known pilot symbols are interpolated to the unknown data symbols by using the non-linear SVR approach exploiting kernel features. This study integrates both channel estimation at pilot symbols and interpolation at data symbol into the complex SVR interpolation method. The bit error rate and mean square error performances of the authors’ fast-fading channel estimation scheme is demonstrated via simulation for LTE downlink with 64-QAM modulation and 500 km/h velocity under non-linearities.
References
-
-
1)
-
1. Garcia, M.J.F.-G., Rojo-Alvarez, J.L., Atienza, F.A., Martinez-Ramon, M.: ‘Support vector machines for robust channel estimation in OFDM’, IEEE Signal Process. Lett., 2006, 13, (7), pp. 397–400 (doi: 10.1109/LSP.2006.871862).
-
2)
-
9. 3rd Generation Partnership Project: ‘Technical specification group radio access network; evolved universal terrestrial radio access (UTRA): physical channels and modulation layer’, TS 36.211, 2009, V8.8.0, pp. 50–58.
-
3)
-
15. Kim, J., Park, J., Hong, D.: ‘Performance analysis of channel estimation in OFDM systems’. Proc. IEEE 60th Vehicular Technology Conf., 2004, vol. 7, pp. 4864–4866.
-
4)
-
7. Hsieh, M.-H., Wei, C.-H.: ‘Channel estimation for OFDM systems based on comb-type pilot arrangement in frequency selective fading channels’, IEEE Trans. Consum. Electron., 1998, 44, (1), pp. 217–225 (doi: 10.1109/30.663750).
-
5)
-
14. Li, Y.: ‘Pilot-symbol-aided channel estimation for OFDM in wireless systems’. Proc. IEEE 49th Vehicular Technology Conf., July 1999, vol. 2, pp. 1131–1135.
-
6)
-
1. Li, T., Fan, P., Xiong, K., et al: ‘QoS-distinguished achievable rate region for high speed railway wireless communications’. IEEE Wireless Communications and Networking Conf. (WCNC), 2015, pp. 2044–2049.
-
7)
-
4. Dai, X., Zhang, W., Xu, J., et al: ‘Kalman interpolation filter for channel estimation of LTE downlink in highmobility environments’, EURASIP J. Wirel. Commun. Netw., 2012, 2012, (1), pp. 1–14 (doi: 10.1186/1687-1499-2012-232).
-
8)
-
11. Rumney, M.: ‘LTE and the evolution to 4G wireless: design and measurement challenges’ (Agilent Technologies, Inc., John Wiley Sons, Ltd, 2013, 2nd edn.).
-
9)
-
2. 3rd Generation Partnership Project: ‘Technical specification group radio access network; evolved universal terrestrial radio access (UTRA): base station (BS) radio transmission and reception’, TS 36.104, 2009, V8.7.0, pp. 22–33.
-
10)
-
16. Morosi, S., Argentini, F., Biagini, M., et al: ‘Comparison of channel estimation algorithms for MIMO downlink LTE systems’. Proc. Ninth Int. Wireless Communications and Mobile Computing Conf., IWCMC, July 2013, pp. 953–958.
-
11)
-
8. Rojo-Álvarez, J.L., Figuera-Pozuelo, C., Martínez-Cruz, C.E., et al: ‘Nonuniform interpolation of noisy signals using support vector machines’, IEEE Trans. Signal Process., 2007, 55, (48), pp. 4116–4126 (doi: 10.1109/TSP.2007.896029).
-
12)
-
10. Ancora, A., Slock, D.T.M.: ‘Down-sampled Impulse Response Least-Squares Channel Estimation for LTE OFDMA’. Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing, ICASSP, April 2007, vol. 3, pp. III–293–III–296.
-
13)
-
18. Martínez Ramón, M., Xu, N., Christodoulou, C.G.: ‘Beamforming using support vector machines’, IEEE Antennas Wirel. Propag. J., 2005, 4, pp. 439–442 (doi: 10.1109/LAWP.2005.860196).
-
14)
-
20. 3rd Generation Partnership Project: ‘Technical specification group radio access network; evolved universal terrestrial radio access (UTRA: physical layer procedures’, TS 36.213, 2009, V8.8.0, pp. 23–31.
-
15)
-
17. Argentini, F., Biagini, M., Del Re, E., et al: ‘Time-frequency MSE analysis of linear channel estimation methods for the LTE downlink’, Trans. Emerg. Telecommun. Technol., 2015, 26, (4), pp. 704–717 (doi: 10.1002/ett.2840).
-
16)
-
13. Vapnik, V.: ‘The nature of statistical learning theory’ (Springer-Verlag, NY, 1995).
-
17)
-
19. 3rd Generation Partnership Project: ‘Technical specification group radio access network; physical layer aspects for evolved universal terrestrial radio access (UTRA)’, TR 25.814, 2006, V7.1.0, pp. 20–29.
-
18)
-
12. Sun, N., Ayabe, T., Nishizaki, T.: ‘Efficient spline interpolation curve modeling’. Proc. Third Int. Conf. on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP, November 2007, vol. 2, pp. 59–62.
-
19)
-
7. Charrada, A., Samet, A.: ‘Estimation of highly selective channels for OFDM system by complex least squares support vector machines’, Int. J. Electron. Commun. (AEÜ), 2012, 66, pp. 687–692 (doi: 10.1016/j.aeue.2011.12.011).
-
20)
-
3. 3rd Generation Partnership Project: ‘Technical specification group radio access network; evolved universal terrestrial radio access (UTRA): user equipment (UE) radio transmission and reception’, ARIB STD-T63-36.101, 2008, V8.4.0, pp. 22–33.
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