A Novel Four Single-Sideband M-QAM Modulation Scheme Using a Shadow Equalizer for MIMO System Toward 5G Communications. [PDF]
Sensors (Basel), 2019 Alhasani MM, Nguyen QN, Ohta GI, Sato T.
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Blind Fractionally Spaced Channel Equalization for Shallow Water PPM Digital Communications Links. [PDF]
Sensors (Basel), 2019 Scarano G, Petroni A, Biagi M, Cusani R.
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Copper damascene process-based high-performance thin-film lithium tantalate modulators. [PDF]
Nat CommunLin M +10 more
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Design of AFDM Waveform Encryption for LEO Satellite Networks. [PDF]
Sensors (Basel)Yuan M, Lin H, Ma C, Ma P, Yu M, Tang X.
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Adaptive Damping Log-Domain Message-Passing Algorithm for FTN-OTFS in V2X Communications. [PDF]
Sensors (Basel)Xu H, Zhang C, Wu Q, Ng BK, Lam CT.
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Implementation of the deep learning method for signal detection in massive-MIMO-NOMA systems. [PDF]
HeliyonKumar A +3 more
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MMSE decision-feedback equalizers and coding. I. Equalization results
IEEE Transactions on Communications, 1995The minimum mean-squared-error decision-feedback equalizer (MMSE-DFE) has properties that suggest that it is a canonical equalization structure for systems that combine equalization with coded modulation. The structure and performance of the MMSE-DFE are succinctly derived using linear-estimation-theoretic principles in this first part of this two-part
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Blind MMSE Equalizer for Nonlinear SIMO Systems
2021 18th International Multi-Conference on Systems, Signals & Devices (SSD), 2021This work presents a novel minimum mean squared error (MMSE) equalizer for blind signal estimation of a nonlinear single input multiple outputs (SIMO) system. The zero and $\tau$ delay MMSE equalizer parameters are blindly estimated using the property that they belong to both the signal subspace and the kernel of a properly truncated data covariance ...
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On the Performance of the Mismatched MMSE and the LS Linear Equalizers
IEEE Transactions on Signal Processing, 2007We consider two widely referenced trained finite-length linear equalizers, namely, the mismatched minimum mean square error (MMSE) equalizer and the least-squares (LS) equalizer. Using matrix perturbation theory, we express both of them as perturbations of the ideal MMSE equalizer and we derive insightful analytical expressions for their excess mean ...
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