OFDM Multiple Antennas Cognitive Radio Relay CDMA Synchronization Channel Estimation Spectrum Sharing Interference Cancellation Neural Networks Spectrum Sensing Full duplex Resource Allocation Stochastic Geometry Equalizer Feedback Bi-Directional Energy Harvesting Femtocell Heterogeneous Networks Device-to-Device (D2D) Cell Search FBMC HetNet Idle cells Ultra-dense small cell networks Spectral efficiency SINR mismatch problem automatic repeat request (ARQ) in-band full-duplex system Two-way communications transmission capacity (TC) Correlated MIMO sensing duration self-interference cancellation Simultaneous Sensing and Transmission full-duplex cellular multi-spectral beamforming UWB achievable sum rate outage probability Cognitive relay networks selection diversity full-duplex relay Latency Vehicular and wireless technologies Asynchronized system Cross-link interference Cellular networks coexistence Channel estimation error Ultra-dense small cell Shortened TTI UL grant free NOMA mode selection Bi-directional full-duplex OQAM Link adaptation Iterative decoder LTE-TDD Dynamic TDD bursty traffic model Filtered OFDM MIMO singular value decomposition Time spreading K-S statistics interference coordination Vehicle-to-vehicle communication eigen decomposition 5G networks GFDM MU-MIMO TS-W-OFDM prototype filter pilot signal Windowing time-frequency efficiency Long Term Evolution-Advanced Aggregate interference LTE-based V2V Resource management Coexistence scenarios resource size control interference to noise ratio interference management mixed numerology Reliability Cooperative systems link reliability C-V2V non-orthogonal multiple access full-spreading NOMA massive connectivity Complexity CP-OFDM Vehicle-to-Vehicle Singular Vale Decomposition tabu-search
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

List of Articles
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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