Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Conference Object Yazılım Tabanlı Radyolarda Karşılıklı Kanal Özelliğinin İncelenmesi(Institute of Electrical and Electronics Engineers Inc., 2016) Uslu, Merve; Tuğrel, Halim Bahadır; Karabulut Kurt, Güneş; Özbek, BernaKablosuz haberleşme sistemlerinde, kanal kestirimi çok önemli bir yer tutmaktadır. Bu çalışmada A ve B, iki haberleşme düğümü olduğu varsayıldığında, A düğümünden B düğümüne olan kanal için elde edilen kanal katsayıları ile, B düğümünden A düğümüne olan kanal için elde edilen kanal katsayılarının benzerliği incelenmiştir. Karşılıklı kanal özelliğinden dolayı bu kanalların birbirine benzer çıkmaları beklenmektedir. Bu çalışmada, laboratuvar ortamında yazılım tabanlı radyo kitleri kullanılarak karşılıklı kanal özelliği test ortamında test edilmiş, bu iki kanal katsayılarının genlik ve faz ortalama değerleri karşılaştırılmıştır.Conference Object Citation - WoS: 1Citation - Scopus: 3Iterative Em-Based Channel Estimation for Stbc-Ofdm(Institute of Electrical and Electronics Engineers Inc., 2009) Baştürk, İlhan; Özbek, BernaIn this paper, an iterative EM based channel estimation algorithm is studied for STBC-OFDM systems. Compared to the time domain EM based channel estimation algorithm which needs matrix inversion, a frequency domain EM based channel estimation algorithm is proposed by estimating the channel coefficients for each subcarrier. The proposed channel estimation algorithm decreased the complexity without sacrificing the performance. The time domain and proposed frequency domain EM based channel estimation algorithms are compared in terms of bit error rate (BER), mean square error (MSE) and the number of iterations used in the EM algorithm.Conference Object Citation - WoS: 2Citation - Scopus: 2Taylor Series Approximation of Semi-Blind Best Linear Unbiased Channel Estimates for the General Linear Model(Institute of Electrical and Electronics Engineers Inc., 2004) Pladdy, Christopher; Nerayanuru, Sreenivasa M.; Fimoff, Mark; Özen, Serdar; Zoltowski, MichaelWe present a low complexity approximate method for semi-blind best linear unbiased estimation (BLUE) of a channel impulse response vector (CIR) for a communication system, which utilizes a periodically transmitted training sequence, within a continuous stream of information symbols. The algorithm achieves slightly degraded results at a much lower complexity than directly computing the BLUE CIR estimate. In addition, the inverse matrix required to invert the weighted normal equations to solve the general least squares problem may be pre-computed and stored at the receiver. The BLUE estimate is obtained by solving the general linear model, y = Ah + w + n, for h, where w is correlated noise and the vector n is an AWGN process, which is uncorrelated with w. The Gauss - Markoff theorem gives the solution h = (A TC(h) -1A) -1A TC(h) -1y. In the present work we propose a Taylor series approximation for the function F(h) = (A TC(h) -1A) -1A TC(h) -1y where, F:R L → R L for each fixed vector of received symbols, y, and each fixed convolution matrix of known transmitted training symbols, A. We describe the full Taylor formula for this function, F(h) = F(h id) + ∑|α|≥|(h - h id) α(∂/∂h) αF(h id) and describe algorithms using, respectively, first, second and third order approximations. The algorithms give better performance than correlation channel estimates and previous approximations used, [15], at only a slight increase in complexity. The linearization procedure used is similar to that used in the linearization to obtain the extended Kaiman filter, and the higher order approximations are similar to those used in obtaining higher order Kaiman filter approximations,