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
Cheolwoo You and Daesik Hong, "Neural Convolutional Decoders in the Satellite Channel", ICNN, Dec. 1995
[ICNN]
조회 64119
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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