A novel blind channel estimation method based on a simple coding scheme for a 2 by 2 multiple input multiple output (MIMO) system is described. The proposed algorithm is easy to implement in comparison with conventional blind estimation algorithms, as it is able to recover the channel matrix without performing singular value decomposition (SVD) or eigenvalue decomposition (EVD). The block codin...

This paper focuses on blind channel estimation in Alamouti coded systems with one receiving antenna working in indoor scenarios where the flat fading assumption is reasonable. A comparative study of several channel estimation techniques in both simulated and realistic scenarios is presented. The tested methods exploit the orthogonality property of the Alamouti coded channel matrix, and are base...

This paper proposes a efficient blind sampling frequency offset (SFO) estimation technique for an orthogonal frequency division multiplexing (OFDM) based power line communication (PLC) system. The main drawback of the conventional estimators is their limited estimation range and their high sensitivity to effect of SFO. To remedy these, this paper proposes two-step correlation scheme that exploi...

A blind adaptive scheme is proposed for joint maximum likelihood (ML) channel estimation and data detection of single-input multiple-output (SIMO) systems. The joint ML optimization over channel and data is decomposed into an iterative optimization loop. An efficient global optimization algorithm called the repeated weighted boosting search is employed at the upper level to identify optimally t...

Probability theory and statistics are two main tools in signal and image processing. Bayesian inference has a privileged place in developing methods for inverse problems arising in signal and image processing which can be applied in real world applications. In this tutorial presentation, first I will breifly present the Bayesian estimation approach in signal and image processing. Then, I will s...

We provide a maximum likelihood formulation for the blind estimation of massive mmWave MIMO channels while taking into account their underlying sparse structure. The main advantage of this approach is the fact that the overhead due to pilot sequences can be reduced dramatically especially when operating at low SNR per antenna. Thereby, the sparsity in the angular domain is exploited as a key pr...

Fast and reliable channel estimation is very important for wireless communication transmission. This paper addresses blind channel estimation for OFDM systems. A novel One-Cycle blind channel estimation algorithm based on cyclostationarity properties of OFDM signal is proposed in this paper, the new algorithm is formed from using the two related z-transform values of delay parameter. Furthermor...

—For a time-hopping (TH) pulse position modulation (PPM) based ultra-wideband (UWB) multiantenna system, we propose four coherent space-time (ST) diversity schemes, corresponding to which the correlation template signals with blind channel estimation are also presented. First of all, the issue of channel identifiability based on first-order statistics is addressed, aspired by the singleantenna...

Independent Component Analysis (ICA) is a statistical signal processing technique whose main applications are blind source separation, blind deconvolution, and feature extraction. Estimation of ICA is usually performed by optimizing a 'contrast' function based on higher-order cumulants. In this paper, it is shown how almost any error function can be used to construct a contrast function to perf...

In this paper we present a generic approach for the problem of the blind estimation of the parameters of linear and convolutional error correcting codes. In a non-cooperative context, an adversary has only access to the noised transmission he has intercepted. The intercepter has no knowledge about the parameters used by the legal users. So, before having acess to the information he has first to...