Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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Subject: search.filters.subject.Channel estimationWoS Q: search.filters.wosQuartile.Q4

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Now showing 1 - 2 of 2
  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Iterative Channel Estimation for Higher Order Modulated Stbc-Ofdm Systems With Reduced Complexity
    (Korean Society of Internet Information, 2016) Baştürk, İlhan; Özbek, Berna
    In this paper, a frequency domain Expectation-Maximization (EM)-based channel estimation algorithm for Space Time Block Coded-Orthogonal Frequency Division Multiplexing (STBC-OFDM) systems is investigated to support higher data rate applications in wireless communications. The computational complexity of the frequency domain EM-based channel estimation is increased when higher order constellations are used because of the ascending size of the search set space. Thus, a search set reduction algorithm is proposed to decrease the complexity without sacrificing the system performance. The performance results of the proposed algorithm is obtained in terms of Bit Error Rate (BER) and Mean Square Error (MSE) for 16QAM and 64QAM modulation schemes.
  • Article
    Taylor Series Approximation of Semi-Blind Blue Channel Estimates With Applications To Dtv
    (Taylor and Francis Ltd., 2008) Pladdy, Christopher; Özen, Serdar; Nerayanuru, Sreenivasa M.; Ding, Peilu; Fimoff, Mark J.; Zoltowski, Michael
    We present a low-complexity method for approximating the semi-blind best linear unbiased estimate (BLUE) of a channel impulse response (CIR) vector for a communication system, which utilizes a periodically transmitted training sequence. The BLUE, for h, for the general linear model, y = Ah + w + n, where w is correlated noise (dependent on the CIR, h) and the vector n is an Additive White Gaussian Noise (AWGN) process, which is uncorrelated with w is given by h = (ATC(h)-1A)-1ATC(h)-1y. In the present work, we propose a Taylor series approximation for the function F(h) = (ATC(h)-1A)-1ATC(h)-1y. We describe the full Taylor formula for this function and describe algorithms using, first-, second-, and third-order approximations, respectively. The algorithms give better performance than correlation channel estimates and previous approximations used, at only a slight increase in complexity. Our algorithm is derived and works within the framework imposed by the ATSC 8-VSB DTV transmission system, but will generalize to any communication system utilizing a training sequence embedded within data.