OFDM Multiple Antennas Cognitive Radio Relay Synchronization CDMA Channel Estimation Spectrum Sharing Interference Cancellation Spectrum Sensing Full duplex Neural Networks Resource Allocation Stochastic Geometry Equalizer Bi-Directional Feedback Heterogeneous Networks Energy Harvesting Femtocell Device-to-Device (D2D) Idle cells FBMC Ultra-dense small cell networks Cell Search Spectral efficiency SINR mismatch problem Cross-link interference HetNet Dynamic TDD self-interference cancellation full-duplex relay in-band full-duplex system automatic repeat request (ARQ) transmission capacity (TC) full-duplex cellular Two-way communications sensing duration selection diversity GFDM interference mitigation Correlated MIMO mode selection multi-spectral outage probability achievable sum rate Cognitive relay networks Vehicular and wireless technologies bursty traffic model UL grant free NOMA Asynchronized system Reliability Latency Cellular networks LTE-TDD Iterative decoder Bi-directional full-duplex OQAM UWB MU-MIMO coexistence Link adaptation beamforming Simultaneous Sensing and Transmission CP-OFDM Long Term Evolution-Advanced Aggregate interference singular value decomposition MIMO 5G networks time-frequency efficiency K-S statistics Time spreading Windowing Vehicle-to-vehicle communication LTE-based V2V interference coordination prototype filter pilot signal TS-W-OFDM eigen decomposition link reliability interference to noise ratio tabu-search resource size control C-V2V Coexistence scenarios interference management Resource management mixed numerology Vehicle-to-Vehicle massive connectivity Complexity non-orthogonal multiple access full-spreading NOMA Filtered OFDM Singular Vale Decomposition 5G flexible duplex Cooperative systems
Status : Published 
Date : 1997-11 
Title : Rapid Acquisition Using A Neural Network in DS/SS Communication System 
Authors : Sangmok Lee, Cheolwoo You and Daesik Hong 
Journal : Neurocomputing 
Abstract : In direct-sequence spread-spectrum (DS/SS) systems, an improved acquisitionsystem aided by aneuralnetwork (RANN) enables the rapid and exact synch-process between the locally generated despreading signal and the received spreading signal. Simulation results show that RANN is more efficient than the conventional system (RASE). 
URL : http://www.sciencedirect.com/science/art...1297000295 

Sangmok Lee, Cheolwoo You, Daesik Hong, Rapid acquisition using a neural network in DS/SS communication systems, Neurocomputing, Volume 17, Issues 3–4, November 1997, Pages 135-140, ISSN 0925-2312, 10.1016/S0925-2312(97)00029-5.
Keywords: DS/SS system; Acquisition; Neural networks; RASE

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» [Neuro Computing] Sangmok Lee, Cheolwoo You and Daesik Hong, "Rapid Acquisition Using A Neural Network in DS/SS Communication System", Neurocomputing, Nov 1997 Published  1997-11