Performance Evaluation of Channel Estimation Methods in OFDM Systems
محورهای موضوعی : Majlesi Journal of Telecommunication Devices
1 - Düziçi Vocacinal High School, Osmaniye Korkut Ata University, Osmaniye, 80000, Turkey
2 - Department of Electrical and Electronics Engineering, Osmaniye Korkut Ata University, Osmaniye, 80000, Turkey
کلید واژه: en, Minimum Mean-Square Error (MMSE), Multi input multi output (MIMO), Least Square (LS), Orthogonal frequency division multiplexing(OFDM),
چکیده مقاله :
In the communication sector, a large amount of data needs to be transmitted very quickly with an increasing user demand. To accommodate these demands, single carrier systems leave their place to multiple carrier systems. The transmission of large amounts of data at high speed requires high-quality radio access over multi-way damped channels. The amplitudes of the signals reaching the receiver at different times and paths are caused by fluctuations in the signal strength, this is called damping effect. The received signal is weaker than the transmitted signal due to the average transmission loss and damping. The adverse effects such as the damping effect on the communication channel greatly affect the performance of the wireless communication and prevent to reach high transmission speeds. In addition to multipath demodulation, multipath propagation also extends the time required for the transmitted signal to reach the receiver. In wireless communication systems, the best way to mitigate the damping effect on the channel is to take advantage of diversification techniques. OFDM, one of the multi-carrier systems, provides efficient channel capacity enhancement. In this study, the performances of least squares (LS) and minimum mean square error (MMSE) estimation methods, which are channel estimation methods, required to remove the interchannel interference in the OFDM technique are investigated by computer simulations. In interchannel interference in the OFDM technique is analyzed with LS and MMS estimation methods and results are compared with respect to Signal to Noise Ratio aspect. The results are promising.
[1]. YALÇIN, E.Y.M.M., Kablosuz İletişim Sistemlerinde Zaman-Frekans Yaklaşımı ile Kanal Modelleme ve Kestirimi. Doktora Tezi, Şubat,2011. İstanbul Üniversitesi Fen Bilimleri Enstitüsü: p. 114.
[2]. Manzoor, S., A.S. Bamuhaisoon, and A.N. Alifa. Channel estimation for MIMO-OFDM systems. in 2015 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW). 2015.
[3]. S. Ganesh, R., J. J, and I. P Akhila, Channel estimation analysis in MIMO-OFDM wireless systems. 2011 International Conference on Signal Processing, Communication, Computing and Networking Technologies. p. 399-403, 2011.
[4]. SR Aryal, H.D., Channel Estimation in MIMO-OFDM System. Nepal Journal of Science and Technology, 2013. 14(Channel Estimation in MIMO-OFDM System ): p. 6.
[5]. Seyman, M.N. and N. Taspinar, Radial Basis Function Neural Networks for Channel Estimation in MIMO-OFDM Systems. Arabian Journal for Science and Engineering, 2013. 38(8): p. 2173-2178.
[6]. Li, Y.G., J.H. Winters, and N.R. Sollenberger, MIMO-OFDM for wireless communications: signal detection with enhanced channel estimation. IEEE Transactions on Communications, 2002. 50(9): p. 1471-1477.
[7]. Khan, A.M., V. Jeoti, and M.A. Zakariya, Pilot Based Pre FFT Signal to Noise Ratio Estimation for OFDM Systems in Rayleigh-Fading Channel. Advanced Computer and Communication Engineering Technology, 2015. 315: p. 171-182.
[8]. Manzoor, S., A.S. Bamuhaisoon, and A.N. Alifa, Channel Estimation for MIMO-OFDM Systems. 2015 5th National Symposium on Information Technology: Towards New Smart World (Nsitnsw), 2015.
[9]. Khlifi, A. and R. Bouallegue, A Very Low Complexity LMMSE Channel Estimation Technique for OFDM Systems. 2015 Ieee 81st Vehicular Technology Conference (Vtc Spring), 2015.
