OFDM
Relay
Cognitive Radio
Multiple Antennas
Resource Allocation
Full Duplex
Spectrum Sensing
Synchronization
Spectrum Sharing
Channel Estimation
Interference Cancellation
Stochastic Geometry
Energy Harvesting
Feedback
Bi-directional
Heterogeneous Networks
Equalization
HetNet
relay networks
FBMC
Ultra Low Power
SC-FDMA
TVWS
Duplex
Reliability
CDMA
MIMO
interference
channel capacity
in-band full-duplex system
interference suppression
5G
C-V2V
reinforcement learning
RSRP weighting
non-orthogonal multiple access (NOMA)
health care
5G mobile communication
indoor positioning
Vehicle-to-vehicle communication
estimated position overlapping
Resource sharing
Power allocation
multi-access edge computing
control overhead
hybrid
Rat-dependent positioning
NR positioning
smart factory
UFMC
Handoff
Femtocell
QAM
CoMP
power uncertainty
- Computation offloading
amplify and forward communication
Zigbee
body area networks
resource block management
frame structure
WVAN
inter user interference
GFDM
mode selection
antenna arrays
partial overlap
LTE-based V2V
resource selection
maximum likelihood method
Communication range
Number of training blocks
Vehicular communication
Uplink SCMA system
Dynamic TDD
QR Factorization
Metaheuristics
FS-NOMA
cross-link interference
user fairness
Multi-user Receiver
Mode 3
V2X
P-NOMA
dynamic HetNet
spectrum partitioning
DQN
D-TDD
CLI
massive connectivity
and 5G networks.
OTDOA
estimated position updating
distributed mode
non-orthogonal multiple access
Spatial capacity
LTE-TDD
—Device-to-device (D2D)
Location-based
overloading
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Cheolwoo You and Daesik Hong, "Neural Convolutional Decoders in the Satellite Channel", ICNN, Dec. 1995
[ICNN]
조회 61772
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
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