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A Neural Network MLSE Receiver Based on Natural Gradient Descent: Application to Satellite Communications

Mohamed Ibnkahla, Jun Yuan
2004 EURASIP Journal on Advances in Signal Processing  
The satellite channel model is composed of a nonlinear traveling wave tube (TWT) amplifier followed by a multipath propagation channel.  ...  The receiver is composed of a neural network channel estimator (NNCE) and a Viterbi detector. The natural gradient (NG) descent is used for training.  ...  The filter-memoryless neural network structure has been shown to outperform fully connected complex-valued multilayer neural network with memory when applied to satellite channel identification (see, e.g  ... 
doi:10.1155/s1110865704405010 fatcat:axamsid5q5ew3nb6ytyd5tjmuy

A neural network MLSE receiver based on natural gradient descent: application to satellite communications

M. Ibnkahla, J. Yuan
2003 Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings.  
The satellite channel model is composed of a nonlinear traveling wave tube (TWT) amplifier followed by a multipath propagation channel.  ...  The receiver is composed of a neural network channel estimator (NNCE) and a Viterbi detector. The natural gradient (NG) descent is used for training.  ...  The filter-memoryless neural network structure has been shown to outperform fully connected complex-valued multilayer neural network with memory when applied to satellite channel identification (see, e.g  ... 
doi:10.1109/isspa.2003.1224633 dblp:conf/isspa/IbnkahlaY03 fatcat:qtcb4csb2nf4zbjlgstvpgvbuq

Statistical analysis of a two-layer backpropagation algorithm used for modeling nonlinear memoryless channels: the single neuron case

N.J. Bershad, M. Ibnkahla, F. Castanie
1997 IEEE Transactions on Signal Processing  
Neural networks have been used for modeling the nonlinear characteristics of memoryless nonlinear channels using backpropagation (BP) learning with experimental training data.  ...  In order to better understand this neural network application, this paper studies the transient and convergence properties of a simplified two-layer neural network that uses the BP algorithm and is trained  ...  INTRODUCTION S EVERAL NONLINEAR channels (e.g., satellite communication channels) [1] are equipped with memoryless nonlinear devices such as traveling-wave tube (TWT) amplifiers. 1 These devices exhibit  ... 
doi:10.1109/78.558493 fatcat:l3dbucqwsbf4tdm6r5fy4xwtaa

Neural network equalization for frequency selective nonlinear MIMO channels

Oussama B. Belkacem, Rafik Zayani, Mohamed L. Ammari, Ridha Bouallegue, Daniel Roviras
2012 2012 IEEE Symposium on Computers and Communications (ISCC)  
The Levenberg-Marquardt algorithm (LM) is used for neural network training, which has proven [1] to exhibit a very good performance with lower computation complexity and faster convergence than other algorithms  ...  These proposed methods are compared in term of Symbol Error Rate (SER) running under nonlinear frequency selective channel.  ...  In [1] , authors proposed an adaptive predistortion techniques based on a feed-forward Neural Network (NN) to linearize power amplifiers such as those used in satellite communications.  ... 
doi:10.1109/iscc.2012.6249262 dblp:conf/iscc/BelkacemZABR12 fatcat:w7rwevolg5amdizmciv2osctsy

Complex-bilinear recurrent neural network for equalization of a digital satellite channel

Dong-Chul Park, Tae-Kyun Jung Jeong
2002 IEEE Transactions on Neural Networks  
Equalization of satellite communication using complex-bilinear recurrent neural network (C-BLRNN) is proposed in this paper.  ...  C-BLRNN is then applied to equalization of a digital satellite communication channel for M-PSK and QAM, which has severe nonlinearity with memory due to traveling wave tube amplifier (TWTA).  ...  Wood for their help in preparing this manuscript. The author extends the thanks to the anonymous reviewers for their careful reviews and constructive comments.  ... 
doi:10.1109/tnn.2002.1000135 pmid:18244467 fatcat:tdqc5hb5uzdllian2ss5sh35km

Adaptive decision feedback equalization for digital satellite channels using multilayer neural networks

Po-Rong Chang, Bor-Chin Wang
1995 IEEE Journal on Selected Areas in Communications  
Digital satellite communication systems are frequently operated over nonlinear channels with memory.  ...  In fact, the satellite communication links are equipped with traveling wave tube (TWT) amplifiers at or near saturation for better efficiency.  ...  However, for MPSK satellite communication, the channel models and the information bearing signals are complexvalued.  ... 
doi:10.1109/49.345876 fatcat:3urlxtu5ffglhhpuf4thfhvf74

Robust Digital Signal Recovery for LEO Satellite Communications Subject to High SNR Variation and Transmitter Memory Effects

Qingyue Chen, Yufeng Zhang, Feridoon Jalili, Zhugang Wang, Yonghui Huang, Yubo Wang, Ying Liu, Gert Frolund Pedersen, Ming Shen
2021 IEEE Access  
LEO satellite networks.  ...  Moreover, unlike existing deep neural network-based DSR techniques (DNN-DSR), which failed to effectively take into account the memory effects of radio-frequency power amplifiers (RF-PAs) in the model  ...  in sixth-generation (6G) communication networks [4] .  ... 
doi:10.1109/access.2021.3117517 fatcat:gjnzuauh5je2nkblcmodsmnx2i

Page 7259 of Mathematical Reviews Vol. , Issue 99j [page]

1999 Mathematical Reviews  
Summary: “This paper proposes a neural network (NN) approach for modeling nonlinear channels with memory.  ...  network modeling and identification of nonlinear channels with memory: algorithms, applications, and analytic models.  ... 

Equalization of the Non-Linear Satellite Communication Channel with an Echo State Network

M. Bauduin, A. Smerieri, S. Massar, F. Horlin
2015 2015 IEEE 81st Vehicular Technology Conference (VTC Spring)  
Index Terms-Satellite Communications, Non-linear communication channel, Equalization, Volterra, Echo State Network authors, the ESN has never been compared to state-of-the-art equalizers for non-linear  ...  The Echo State Network (ESN), an algorithm coming from the field of artificial neural networks, has also been proposed for this task but has never been compared to state-of-the-art equalizers for non-linear  ...  The problem of the equalization of a satellite non-linear channel has been investigated for both the Volterra equalizer and ESN equalizer.  ... 
doi:10.1109/vtcspring.2015.7145827 dblp:conf/vtc/BauduinSMH15 fatcat:mzufe5vtjngcpndc3wmozbhbvy

Predistorsion Of Non-Linear Satellite Channels Using Neural Network: Architecture, Algorithm And Implementation

Fabien Langlet, Hasan Abdulkader, D. Roviras
2002 Zenodo  
Publication in the conference proceedings of EUSIPCO, Toulouse, France, 2002  ...  Global simulation In this simulation, we present the down link linearization, for a memoryless SSPA, by predistortion. All the mixed implementation predistorter imperfections are modeled.  ...  MLP Neural Network structure Update of the 1st layer synaptic weights and biases: Fig. 5 . 5 Fig. 5. MSE evolution with ordinary and natural gradient 4. IMPLEMENTATION Fig. 6 . 6 Fig. 6.  ... 
doi:10.5281/zenodo.53593 fatcat:q2ccykzzgvghzff4avnj42hq7a

Nonlinear System Identification Using Neural Networks Trained with Natural Gradient Descent

Mohamed Ibnkahla
2003 EURASIP Journal on Advances in Signal Processing  
We use natural gradient (NG) learning neural networks (NNs) for modeling and identifying nonlinear systems with memory.  ...  The NN model is composed of a linear adaptive filter Q followed by a two-layer memoryless nonlinear NN.  ...  This nonlinear system structure has been used in many applications, for example, in satellite communications where the uplink channel is composed of a linear filter followed by a traveling wave tube (TWT  ... 
doi:10.1155/s1110865703306079 fatcat:6hhfrh6unrefdllbj4zk3m4gly

A Novel Efficient Cluster-Based MLSE Equalizer for Satellite Communication Channels with-QAM Signaling

Eleftherios Kofidis, Vassilis Dalakas, Yannis Kopsinis, Sergios Theodoridis
2006 EURASIP Journal on Advances in Signal Processing  
In satellites, nonlinear amplifiers used near saturation severely distort the transmitted signal and cause difficulties in its reception.  ...  Nevertheless, the nonlinearities introduced by memoryless bandpass amplifiers preserve the symmetries of the M-ary quadrature amplitude modulation (M-QAM) constellation.  ...  Relevant works commonly resort to nonlinear equalizers based on neural network (NN) structures [5, 9] or on Volterra series [10] [11] [12] .  ... 
doi:10.1155/asp/2006/34343 fatcat:wqugugxz5fdkhk6v4nleu7gkki

Complex-valued neural networks with adaptive spline activation function for digital-radio-links nonlinear equalization

A. Uncini, L. Vecci, P. Campolucci, F. Piazza
1999 IEEE Transactions on Signal Processing  
Several experimental results using a realistic channel model are reported that prove the effectiveness of the proposed network on equalizing a digital satellite radio link in the presence of noise, nonlinearities  ...  In particular, this work addresses the problem of nonlinear channel equalization.  ...  ACKNOWLEDGMENT The authors wish to acknowledge the anonymous reviewers for their useful suggestions and comments that yielded to an improved version of this manuscript.  ... 
doi:10.1109/78.740133 fatcat:zfvwctgfwnazxh52xgcb7ea7wy

Source separation in post-nonlinear mixtures

A. Taleb, C. Jutten
1999 IEEE Transactions on Signal Processing  
These mixtures constituted by a linear instantaneous mixture (linear memoryless channel) followed by an unknown and invertible memoryless nonlinear distortion, are realistic models in many situations and  ...  Index Terms-Entropy, neural networks, nonlinear mixtures, source separation, unsupervised adaptive algorithms.  ...  For instance, systems with memoryless nonlinearities can be encountered in sensor arrays [27] , in digital satellite and microwave communications [30] , and in some biological models [21] . B.  ... 
doi:10.1109/78.790661 fatcat:6h4rrnn6uvfsbpkumc72djiire

MIMO Volterra Modeling for Nonlinear Communication Channels

Carlos Alexandre R. Fernandes, João Cesar M. Mota, Gérad Favier
2010 Learning and Nonlinear Models  
An overview of the modeling of nonlinear communication channels using MIMO Volterra models is presented in this paper.  ...  Finally, some applications of such models for communication systems are briefly discussed.  ...  SISO Volterra communication channels The main Volterra models for SISO communication channels are introduced in this section, as well as some of their properties.  ... 
doi:10.21528/lnlm-vol8-no2-art1 fatcat:djjk2bqnpzdxjmdqzgy7rrlopy
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