OFDM Relay Cognitive Radio Multiple Antennas Resource Allocation Full Duplex Spectrum Sensing Synchronization Spectrum Sharing Interference Cancellation Channel Estimation Feedback Heterogeneous Networks Bi-directional Energy Harvesting Stochastic Geometry HetNet relay networks FBMC Equalization channel capacity TVWS CDMA interference in-band full-duplex system Duplex MIMO Ultra Low Power C-V2V 5G Reliability SC-FDMA interference suppression D-TDD CLI indoor positioning reinforcement learning RSRP weighting - Computation offloading smart factory Cell-free multi-access edge computing estimated position overlapping —Device-to-device (D2D) estimated position updating mMIMO control overhead hybrid NR positioning Femtocell Rat-dependent positioning frame structure Zigbee body area networks channel estimation error Handoff CoMP User grouping power uncertainty ultra-dense small cell network mode selection antenna arrays 5G mobile communication UFMC resource block management inter user interference WVAN health care partial overlap GFDM Dynamic TDD Multi-user Receiver Number of training blocks Uplink SCMA system V2X Vehicular communication cross-link interference LTE-TDD FS-NOMA Location-based user fairness Mode 3 QR Factorization Metaheuristics P-NOMA non-orthogonal multiple access dynamic HetNet spectrum partitioning and 5G networks. massive connectivity non-orthogonal multiple access (NOMA) overloading DQN OTDOA distributed mode Communication range resource selection maximum likelihood method Resource sharing Power allocation packet delay
Status : Presented 
Date : 1996-06 
Title : Adaptive Equalization Using the Complex Backpropagation Algorithm 
Authors : Cheolwoo You and Daesik Hong 
Conference : International Conference on Neural Networks 
Abstract : For decreasing intersymbol interference (ISI) due to band-limited channels in digital communication, the uses of equalization techniques are necessary. Among adaptive equalization techniques, because of their ease of implementation and nonlinear capabilities, the neural networks have been used as an alternative for effectively dealing with the channel distortion, especially the nonlinear distortion. The complex backpropagation (BP) neural networks are proposed as nonlinear adaptive equalizers that can deal with both QAM and PSK signals of any constellation size (e.g. 32-QAM, 64-QAM and MPSK), and the complex BP algorithm for the new node activation functions having multi-output values and multi-saturation regions is presented. We also show that the proposed complex BPN provides, compared with the linear equalizer using the least mean squares (LMS) algorithm, an interesting improvement concerning bit error rate (BER) when channel distortions are nonlinear 
URL : http://ieeexplore.ieee.org/xpl/articleDe...ber=549232 

 Cheolwoo You; Daesik Hong; , "Adaptive equalization using the complex backpropagation algorithm ,"Neural Networks, 1996., IEEE International Conference on , vol.4, no., pp.2136-2141 vol.4, 3-6 Jun 1996

doi: 10.1109/ICNN.1996.549232
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=549232&isnumber=11369
List of Articles
No.
Status Datesort
3 [ICNN] Sunghwan Ong, Sooyong Choi, Cheolwoo You and Daesik Hong, "A decision feedback recurrent neural equalizer for digital communication", ICNN, June 1997 Presented  1997-06 
» [ICNN] Cheolwoo You and Daesik Hong, "Adaptive Equalization Using the Complex Backpropagation Algorithm", ICNN, June 1996 Presented  1996-06 
1 [ICNN] Cheolwoo You and Daesik Hong, "Neural Convolutional Decoders in the Satellite Channel", ICNN, Dec. 1995 Presented  1995-12