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, "Adaptive Equalization Using the Complex Backpropagation Algorithm", ICNN, June 1996
[ICNN]
조회 62019
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.1996.549232URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=549232&isnumber=11369
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