OFDM Multiple Antennas Cognitive Radio Relay Synchronization CDMA Channel Estimation Spectrum Sharing Interference Cancellation Full duplex Spectrum Sensing Neural Networks Resource Allocation Stochastic Geometry Equalizer Bi-Directional Feedback Femtocell Heterogeneous Networks Energy Harvesting Device-to-Device (D2D) Cell Search Spectral efficiency NOMA FBMC interference management Dynamic TDD Cross-link interference SINR mismatch problem HetNet Idle cells Ultra-dense small cell networks achievable sum rate outage probability multi-spectral full-duplex relay selection diversity bursty traffic model mode selection Handoff CP-OFDM non-orthogonal multiple access self-interference cancellation Singular Vale Decomposition interference mitigation full-duplex cellular interference coordination Cognitive relay networks Time spreading beamforming Link adaptation Heterogeneous channel estimation capability coexistence MU-MIMO full-spreading NOMA GFDM Bi-directional full-duplex OQAM sensing duration Correlated MIMO Simultaneous Sensing and Transmission transmission capacity (TC) Two-way communications in-band full-duplex system automatic repeat request (ARQ) UWB flexible duplex TS-W-OFDM Windowing time-frequency efficiency eigen decomposition pilot signal 5G networks prototype filter Aggregate interference Long Term Evolution-Advanced interference to noise ratio resource size control link reliability mixed numerology Vehicle-to-vehicle communication LTE-based V2V Coexistence scenarios Resource management Filtered OFDM Cooperative systems Complexity tabu-search Deep learning Reliability Vehicle-to-Vehicle C-V2V HST Mobility Preamble 5G Grant-free Transmission Asynchronous Transmission Railway MLP massive connectivity
Status : Published 
Date : 1998-11 
Title : Nonlinear Blind Equalization Schemes Using Complex-valued Multilayer Feedforward Neural Networks 
Authors : Cheolwoo You and Daesik Hong 
Journal : IEEE Transactions on Neural Networks 
Abstract : Among the useful blind equalization algorithms, stochastic-gradient iterative equalization schemes are based on minimizing a nonconvex and nonlinear cost function. However, as they use a linear FIR filter with a convex decision region, their residual estimation error is high. In the paper, four nonlinear blind equalization schemes that employ a complex-valued multilayer perceptron instead of the linear filter are proposed and their learning algorithms are derived. After the important properties that a suitable complex-valued activation function must possess are discussed, a new complex-valued activation function is developed for the proposed schemes to deal with QAM signals of any constellation sizes. It has been further proven that by the nonlinear transformation of the proposed function, the correlation coefficient between the real and imaginary parts of input data decreases when they are jointly Gaussian random variables. Last, the effectiveness of the proposed schemes is verified in terms of initial convergence speed and MSE in the steady state. In particular, even without carrier phase tracking procedure, the proposed schemes correct an arbitrary phase rotation caused by channel distortion 
URL : http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=728394 

Cheolwoo You; Daesik Hong; , "Nonlinear blind equalization schemes using complex-valued multilayer feedforward neural networks," Neural Networks, IEEE Transactions on , vol.9, no.6, pp.1442-1455, Nov 1998
doi: 10.1109/72.728394
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=728394&isnumber=15696

List of Articles
No.
Status Datesort
3 [IEEE Trans. Neural Netw.] KyunByoung Ko, Sooyong Choi, Changeon Kang and Daesik Hong, "RBF Multiuser Detector With Channel Estimation Capability in a Synchronous MC-CDMA System", IEEE Trans. Neural Networks, Nov 2001 Published  2001-11 
» [IEEE Trans. Neural Netw.] Cheolwoo You and Daesik Hong, "Nonlinear Blind Equalization Schemes Using Complex-valued Multilayer Feedforward Neural Networks", IEEE Trans. Neural Networks, Nov 1998 Published  1998-11 
1 [IEEE Trans. Neural Netw.] Daesik Hong and Okan K. Ersoy, "Parallel, Self-Organizing Hierarchical Neural Networks", IEEE Trans. Neural Net., June 1990 Published  1990-06