Paper
10 August 2004 Approximate best linear unbiased channel estimation for multi-antenna frequency selective channels with applications to digital TV systems
Serdar Ozen, Christopher Pladdy, Sreenivasa M. Nerayanuru, Mark J. Fimoff, Michael D. Zoltowski
Author Affiliations +
Abstract
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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Serdar Ozen, Christopher Pladdy, Sreenivasa M. Nerayanuru, Mark J. Fimoff, and Michael D. Zoltowski "Approximate best linear unbiased channel estimation for multi-antenna frequency selective channels with applications to digital TV systems", Proc. SPIE 5440, Digital Wireless Communications VI, (10 August 2004); https://doi.org/10.1117/12.543164
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KEYWORDS
Antennas

Receivers

Telecommunications

Signal to noise ratio

Error analysis

Data communications

Composites

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