OFDM
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Multiple Antennas
Resource Allocation
Full Duplex
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Synchronization
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Channel Estimation
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Stochastic Geometry
HetNet
relay networks
FBMC
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channel capacity
TVWS
CDMA
interference
in-band full-duplex system
Duplex
MIMO
Ultra Low Power
C-V2V
5G
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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
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Sunghwan Ong, Sooyong Choi, Cheolwoo You and Daesik Hong, "A decision feedback recurrent neural equalizer for digital communication", ICNN, June 1997
[ICNN]
조회 68372
Status : | Presented |
---|---|
Date : | 1997-06 |
Title : | A decision feedback recurrent neural equalizer for digital communication |
Authors : | Sunghwan Ong, Sooyong Choi, Cheolwoo You and Daesik Hong |
Conference : | International Conference on Neural Networks |
Abstract : | In this paper, we introduce an adaptive Decision Feedback Recurrent Neural Equalizer (DFRNE) whose small size and high performance makes it suitable for high-speed channel equalization. By evaluating its performance through computer simulations for various channels, the DFRNE has comparable performance with traditional equalizers when the channel interferences are mild. And it outperforms them when the channel’s transfer function has spectral nulls or when severe nonlinear distortion is present. In addition, the DFRiVE, being essentially an IIR filter, is shown to outperform multi-layer perceptron equalizers in linear and non-linear channel equalization cases. |
URL : | http://ieeexplore.ieee.org/xpl/articleDe...ber=611653 |
Sunghwan Ong; Sooyong Choi; Cheolwoo You; Daesik Hong; , "A decision feedback recurrent neural equalizer for digital communication," Neural Networks,1997., International Conference on , vol.1, no., pp.142-147 vol.1, 9-12 Jun 1997
doi: 10.1109/ICNN.1997.611653
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=611653&isnumber=13361
doi: 10.1109/ICNN.1997.611653
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=611653&isnumber=13361
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