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Kalman Filter-Trained Recurrent Neural Equalizers for Time-Varying Channels
(Institute of Electrical and Electronics Engineers, 2005-03)
Kalman Filter-Trained Recurrent Neural Equalizers for Time-Varying Channels
(Institute of Electrical and Electronics Engineers, 2005-03)
Recurrent neural networks (RNNs) have been successfully applied to communications channel equalization because of their modeling capability for nonlinear dynamic systems. Major
problems of gradient-descent learning techniques ...
Modified Kalman Filters for Channel Estimation in Orthogonal Space-Time Coded Systems
(Ieee-inst Electrical Electronics Engineers IncPiscatawayEUA, 2012)
Low-Complexity Channel Prediction Using Approximated Recursive DCT
(Institute of Electrical and Electronics Engineers, 2011-07-14)
We present a novel channel estimator/predictor for OFDM systems over time-varying channels using a recursive formulation of a basis expansion model (BEM) based on an approximated discrete cosine transform (DCT). We derive ...
Time-varying channel estimation using two-dimensional channel orthogonalization and superimposed training
(2012)
In this correspondence, a method is presented for estimating double-selective channels using superimposed training (ST). The estimator is based on a subspace projection of the time-varying channel onto a set of two dimensional ...
Intercarrier Interference in OFDM: A deterministic model for transmissions in mobile environments with imperfect synchronization
(IEEE, 2008)
Intercarrier Interference (ICI) is an impairment well known to degrade performance of Orthogonal Frequency Division Multiplexing (OFDM) transmissions. It arises from carrier frequency offsets (CFO), from the Doppler spread ...
The use of FDTD for the analysis of magnetoplasma channel waveguides
(Ieee-inst Electrical Electronics Engineers IncNew YorkEUA, 1998)
Energy-efficient channel estimation
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
We investigate the energy-efficient channel estimation in wireless networks, where one pilot is inserted for every several data slots to estimate the channel coefficients. Both the channel state information estimation error ...
Robustness over time-varying channels in DNN-HMM ASR based human-robot interaction
(2017)
This paper addresses the problem of time-varying channels in speech-recognition-based human-robot interaction using Locally-Normalized Filter-Bank features (LNFB), and training strategies that compensate for microphone ...