Browsing by Author "Fimoff, Mark J."

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Approximate Best Linear Unbiased Channel Estimation for Frequency Selective Channels With Long Delay Spreads: Robustness To Timing and Carrier Offsets
(Institute of Electrical and Electronics Engineers Inc., 2005) Özen, Serdar; Özen, Serdar; Nerayanuru, Sreenivasa M.; Pladdy, Christopher; Fimoff, Mark J.; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
We provide an iterative and a non-iterative channel impulse response (CIR) estimation algorithm for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols. The iterative procedure calculates the (semi-blind) Best Linear Unbiased Estimate (BLUE) of the CIR. The non-iterative version is an approximation to the BLUE CIR estimate, denoted by a-BLUE, achieving almost similar performance, with much lower complexity. Indeed we show that, with reasonable assumptions, a-BLUE channel estimate can be obtained by using a stored copy of a pre-computed matrix in the receiver which enables the use of the initial CIR estimate by the subsequent equalizer tap weight calculator. Simulation results are provided to demonstrate the performance of the novel algorithms for 8-VSB ATSC Digital TV system. We also provide a simulation study of the robustness of the a-BLUE algorithm to timing and carrier phase offsets.
Approximate Best Linear Unbiased Channel Estimation for Multi-Antenna Frequency Selective Channels With Applications To Digital Tv Systems
(SPIE, 2004) Özen, Serdar; Özen, Serdar; Pladdy, Christopher; Nerayanuru, Sreenivasa M.; Fimoff, Mark J.; Zoltowski, Michael D.; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
We provide an iterative and a non-iterative channel impulse response (CIR) estimation algorithm for communication receivers with multiple-antenna. Our algorithm is best suited for communication systems which utilize a periodically transmitted training sequence within a continuous stream of information symbols, and the receivers for this particular system are expected work in a severe frequency selective multipath environment with long delay spreads relative to the length of the training sequence. The iterative procedure calculates the (semi-blind) Best Linear Unbiased Estimate (BLUE) of the CIR. The non-iterative version is an approximation to the BLUE CIR estimate, denoted by a-BLUE, achieving almost similar performance, with much lower complexity. Indeed we show that, with reasonable assumptions, a-BLUE channel estimate can be obtained by using a stored copy of a pre-computed matrix in the receiver which enables the use of the initial CIR estimate by the subsequent equalizer tap weight calculator. Simulation results are provided to demonstrate the performance of the novel algorithms for 8-VSB ATSC Digital TV system. We also provide a simulation study of the robustness of the a-BLUE algorithm to timing and carrier phase offsets.
Taylor Series Approximation of Semi-Blind Blue Channel Estimates With Applications To Dtv
(Taylor and Francis Ltd., 2008-01) Pladdy, Christopher; Özen, Serdar; Özen, Serdar; Nerayanuru, Sreenivasa M.; Ding, Peilu; Fimoff, Mark J.; Zoltowski, Michael; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
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.