Numerical examples are shown to demonstrate the performance of the proposed algorithm. Compared with training-based MIMO relay channel estimation approaches, our algorithm has a better bandwidth efficiency as no bandwidth is wasted for sending the training sequences. When no knowledge is available about the degradations present on the original image, blind restoration methods can only be considered. Channel estimation In document Advanced Blind Signal Processing for MIMO Communications (-36) The performance of coherent MIMO communication systems, in which it can be safely as- sumed that channel state information (CSI) being known at the receiver, severely rely upon the quality of CSI available at the receiver Yan05. In particular, we propose a first-order Z-domain precoding technique for the blind estimation of the relay-destination channel matrix, while an algorithm based on the constant modulus and mutual information properties is developed to estimate the source-relay channel matrix. Hyperspectral images acquired by remote sensing systems are generally degraded by noise and can be sometimes more severely degraded by blur. Extensive simulation results demonstrate the effectiveness of the proposed semi-blind cascaded channel estimation algorithm. In this paper, we integrate two blind source separation (BSS) methods to estimate the individual channel state information (CSI) for the source-relay and relay-destination links of three-node two-hop multiple-input multiple-output (MIMO) relay systems. Meanwhile, we present an analytical framework to characterize the theoretical performance bound of the proposed approach in the large-system limit via the replica method developed in statistical physics. IEEE Workshop on Statistical Signal Processing The first stage is based on the classical Viterbi Viterbi approach with the estimation of the mean. Based on the fact that it is hard to distinguish late reverberation from noise in noisy scenarios, this paper proposes a noise-robust blind reverberation time estimation algorithm based on noise-aware timefrequency masking.
SSP 2014 : IEEE Workshop on Statistical Signal Processing Proceedings This paper presents a general blind channel estimation algorithm for multicarrier transmission. Blind T 60 estimation in noisy and large reverberation enclosures is still a challenging problem. IEEE Workshop on Statistical Signal Processing (2014 : Gold Coast, Qld.) conventional blind estimation algorithms, as it is able to recover the channel matrix without performing sin- gular value decomposition (SVD) or eigenvalue. Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia Corresponding author: Abstract. Blind estimation of MIMO relay channels Chiong,CWR, Rong,Y and Xiang,Y 2014, Blind estimation of MIMO relay channels, in SSP 2014 : IEEE Workshop on Statistical Signal Processing Proceedings, IEEE Computer Society, Piscataway, N.
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