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In this paper we propose low-complexity algorithms for estimating flat, time-varying and spatially correlated MIMO channels. The proposed estimators employ Kalman filters to track the channel in orthogonal space-time block coded systems. After developing a state-space model for spatially correlated MIMO channels, we show that the proposed estimators can be simplified by using the orthogonality inherent...
In this paper, we propose a semi-blind state-space based receiver that jointly performs channel estimation and data detection in MIMO systems subject to fast frequency-selective fading. To accomplish these two tasks, we first define state equations representing the dynamics of channel and transmitted signals. Then, we obtain the state vector by concatenating the transmitted signals and the channel...
This paper introduces a turbo-fuzzy equalizer (TFEQ) to cope with the inter-symbol interference effects and impulsive noise occurrences in bandlimited digital communication channels, such as the indoor and outdoor power line circuits. We exploit a close relationship between the fuzzy and Bayesian equalizers to derive an adaptive nonsingleton turbo-fuzzy equalization technique. Generally speaking,...
Crosstalk is one of the main limiting factors in the data rates achievable by digital subscriber line (DSL) systems, and several algorithms have been proposed to mitigate this impairment. In this paper, we compare the capacity of binders under different crosstalk-mitigating techniques. When computing capacity, we also compare two different power constraints: either on the total power in the binder...
Turbo equalization is a receiver scheme intended to combat the detrimental effects of intersymbol interference (ISI) in digital transmissions protected by error-control codes (ECC). Traditionally, these equalizers are implemented with the optimal MAP (maximum a posteriori probability), or Bayesian algorithm. Thus, considering the close relationship between the fuzzy and Bayesian equalizers, this paper...
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