Signal to noise ratio (SNR) indicated notable efficacy in this paper that obtained by using the LS algorithm, in particular channels with variation in time.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:Orthogonal frequency division multiplex (OFDM) is one of the best approaches to overcome frequency selectivity of channels.
📊
Key Findings & Data:To improve channel estimation achievement a LS algorithm is developed, so we obtain Bit Error Rate (BER) performance of channel.
💡
Conclusion & Impact:Signal to noise ratio (SNR) indicated notable efficacy in this paper that obtained by using the LS algorithm, in particular channels with variation in time.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Channel Estimation · LSE · MIMO System
Abstract
Orthogonal frequency division multiplex (OFDM) is one of the best approaches to overcome frequency selectivity of channels. In multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, we purposed channel estimation with least squares (LS) estimation method in this paper. To improve channel estimation achievement a LS algorithm is developed, so we obtain Bit Error Rate (BER) performance of channel. Mean Square Error (MSE) of LS estimation calculated and depicted with figures. Signal to noise ratio (SNR) indicated notable efficacy in this paper that obtained by using the LS algorithm, in particular channels with variation in time.
Bölcskei, H., Gesbert, D., Paulraj, A. J., (2002). On the capacity of OFDMbased spatial multiplexing systems. IEEE Trans. Commun., 50, 225–234
Cavers, J.K., (1991). An analysis of pilot symbol assisted modulation for Rayleigh fading channels. IEEE Trans. Veh. Technol., 40, 686–693
Chang, M.X. Su, Y.T., (2002). Performance analysis of equalized OFDM system in Rayleigh fading. IEEE Trans. Wireless Commun., 1, 721–732
Cheon, H., Hong, D., (2002). Effect of channel estimation error in OFDMbased WLAN. IEEE Commun. Lett., 6, 190–192
Deneire, L., Vandenameele, P., Van der Perre, L., Gyselinckx, B., Engels, M., (2001). A low complexity ML channel estimator for OFDM. Proc. IEEE Int. Conf. Commun., Helsinki, Finland, 11–14
Edfords, O., Sandell, M., Van de Beek, J.J., Wilson, S.K., Borjesson, P.O., (1998). OFDM channel estimation by singular value decomposition. IEEE Trans. Commun., 46, 931–939
Van de Beek, J.J., Edfors, O., Sandell, M., Wilson, S. K., Brjesson, P. O., (1995). On channel estimation in OFDM systems. Proc. IEEE Vehic. Technol. Conf., 2, 815–819
Jeon, W. G., Paik, K. H., Cho, Y. S., (2000). An efficient channel estimation technique for OFDM systems with transmitter diversity. Proc. IEEE Int. Symp. Pers., Indoor Mobile, 2, 1246–1250
Li, Y., Seshadri, N., Ariyavisitakul, S., (1999). Channel estimation for OFDM systems with transmitter diversity in mobile wireless channels. IEEE J. Select. Areas Commun., 17, 461–471
Li, Y.G., Cimini, L.J., Sollenberger, N.R., (1998). Robust channel estimation for OFDM systems with rapid dispersive fading channels. IEEE Trans. Commun., 46, 902–915
Ohno, S., Giannakis, G. B., (2001). Optimal training and redundant precoding for block transmissions with applications to wireless OFDM. Proc. IEEE ICASSP, Salt Lake City, UT, 2389–2392
Veeranarayanareddy, C., Prabhakar, K., (2015). A Novel BER Analytical Performance of DWT based ofdm using various channel over dft based OFDM. International journal of engineering and computer science 4(9), 14313
Le Floch, B., Alard, M., Berrou, C., (1995). Coded orthogonal frequency division multiplex. Proc. IEEE, 83(6), 982–996
Beek, J.J., (1998). Channel Estimation in OFDM Systems. Lulea University of Technology,1402-1544
Van de Beek, J.J., (1998). Synchronization and Channel Estimation in OFDM Systems. Lulea University of Technology, Division of Signal Processing. 051015202530352.533.544.555.566.57Number of NFFTPower of Channel (