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 : 1995-12 
Title : Neural Convolutional Decoders in the Satellite Channel 
Authors : Cheolwoo You and Daesik Hong 
Conference : International Conference on Neural Networks 
Abstract : The neural convolutional decoders (NCD) have been used as an alternative for decoding convolutional codes. The motivation of the NCD is to reduce the hardware complexity of the conventional convolutional decoders and maintain the performance. Simulations are performed under the satellite channel that has the nonlinear distortion. We restrict our attention to the case of coherent QPSK modulation. In this case, the neural networks can learn the nonlinear distortion of the satellite channel including the filtering effects and the nonlinear effects of the traveling-wave tube (TWT) amplifiers. The result shows that the performance of the NCD with a simple structure is almost equal to that of the soft decision Viterbi decoder for the systematic code with 32-bit paths which need 128-bit memory storage. And, the performance difference between the NCD for the systematic code and the soft decision Viterbi decoder for the nonsystematic code is about 1.0 dB and nearly identical to that caused by the dissimilarity of the error-correcting ability in two codes. It is concluded that the NCD would perform as well as the soft decision Viterbi decoder for the nonsystematic code 
URL : http://ieeexplore.ieee.org/xpl/articleDe...ber=488142 

Cheolwoo You; Daesik Hong; , "Neural convolutional decoders in the satellite channel," Neural Networks, 1995. Proceedings., IEEE International Conference on , vol.1, no., pp.443-448 vol.1, Nov/Dec 1995
doi: 10.1109/ICNN.1995.488142
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=488142&isnumber=10431

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 
2 [ICNN] Cheolwoo You and Daesik Hong, "Adaptive Equalization Using the Complex Backpropagation Algorithm", ICNN, June 1996 Presented  1996-06 
» [ICNN] Cheolwoo You and Daesik Hong, "Neural Convolutional Decoders in the Satellite Channel", ICNN, Dec. 1995 Presented  1995-12