This paper studies a networked state estimation problem for a spatially large linear system with a distributed array of sensors, each of which offers partial state measurements. A lossy communication network is used to transmit the sensor measurements to a central estimator where the minimum mean square error (MMSE) state estimate is computed. Under aMarkovian packet lossmodel, we provide neces...

This paper addresses time-domain channel estimation for pilot-symbol-aided orthogonal frequency division multiplexing (OFDM) systems. By using a cyclic sinc-function matrix uniquely determined by Nc transmitted subcarriers, the performance of our proposed scheme approaches perfect channel state information (CSI), within a maximum of 0.4 dB degradation, regardless of the delay spread of the chan...

Estimation of the clean speech short-time magnitude spectrum (MS) is key for enhancement and separation. Moreover, an automatic recognition (ASR) system that employs a front-end relies on MS estimation to remain robust. Training targets deep learning approaches fall into three categories: computational auditory scene analysis (CASA), MS, minimum mean square error (MMSE) estimator training targe...

This paper proposes a novel recursive method to jointly estimate the Rayleigh fading channel and the transmitted symbols for current wireless communications systems. Starting from the well-known Jakes’ model for the wireless fading channel, an autoregressive (AR) representation is produced by the means of Levinson–Durbin algorithm. This allows for a state-space approach to the channel estimatio...

The problem of estimating propagation delays of the orthogonal modulated signals in asynchronous DS-CDMA system over fading channels is treated in this paper. The system under study resembles the uplink of an IS-95 system. The channel is assumed to be a time-varing flat Rayleigh-fading channel. The shortcoming of the sliding correlator as the standard method of code acquisition is examined and ...

A time-difference-of-arrival-based partial discharge (PD) location system that utilises prior knowledge of substation layout is presented. We propose a new time delay estimator employs onset detection techniques and demonstrate, through experimental results, it at least 2.8 times more accurate than other conventional estimators. Using substation’s layout, we develop minimum mean-square-error (M...

This paper considers a single-cell massive MIMO (multiple-input multiple-output) system with dual-polarized antennas at both the base station and users. We study channel model that includes key practical aspects arise when utilizing dual-polarization: cross-polar discrimination (XPD) correlations (XPC) transmitter receiver. derive achievable uplink downlink spectral efficiencies (SE) without su...

In this paper, we devise a highly efficient machine learning-based channel estimation for orthogonal frequency division multiplexing (OFDM) systems, in which the training of estimator is performed online. A simple learning module employed proposed estimator. The process thus much faster and required data reduced significantly. Besides, construction approach utilizing least square (LS) results s...

In this paper we revisit the minimum mean square error (MMSE) pilot-aided channel estimation for broadband orthogonal frequency division multiplexing (OFDM) systems. The careful design of OFDM symbol leads to the proposal of a simplified time-domain (TD) MMSE estimator. By exploring the Fourier properties of the symbol, the investigated method eliminates the need to use direct or inverse discre...