Detection of Nonlinearly Distorted M-ary QAM Signals Using Self-Organizing Map
スポンサーリンク
概要
- 論文の詳細を見る
Detection of nonlinearly distorted signals is an essential problem in telecommunications. Recently, neural network combined conventional equalizer has been used to improve the performance especially in compensating for nonlinear distortions. In this paper, the self-organizing map (SOM) combined with the conventional symbol-by-symbol detector is used as an adaptive detector after the output of the decision feedback equalizer (DFE), which updates the decision levels to follow up the nonlinear distortions. In the proposed scheme, we use the box distance to define the neighborhood of the winning neuron of the SOM algorithm. The error performance has been investigated in both 16 QAM and 64 QAM systems with nonlinear distortions. Simulation results have shown that the system performance is remarkably improved by using SOM detector compared with the conventional DFE scheme.
- 社団法人電子情報通信学会の論文
- 2001-08-01
著者
-
LU Jianming
Graduate School of Science and Technology, Chiba University
-
YAHAGI Takashi
Graduate School of Science and Technology, Chiba University
-
Lu Jianming
Graduate School Of Science And Technology Chiba University
-
Yahagi T
Graduate School Of Science And Technology Chiba University
-
Lin H
Mobile Terminals Core Technology Development Division Nec Corporation
-
Wang Xiaoqiu
Graduate School Of Science And Technology Chiba University
-
LIN Hua
The authors are with the Graduate School of Science and Technology, Chiba University
-
WANG Xiaoqiu
The authors are with the Graduate School of Science and Technology, Chiba University
-
LU Jianming
The authors are with the Graduate School of Science and Technology, Chiba University
-
YAHAGI Takashi
The authors are with the Graduate School of Science and Technology, Chiba University
-
Yahagi Takashi
The Authors Are With The Graduate School Of Science And Technology Chiba University
関連論文
- Nonlinear Time Series Prediction Using Wavelet Network with Kalman Filter Based Algorithm
- Texture Classification for Liver Tissues from Ultrasonic B-Scan Images Using Testified PNN(Pattern Recognition)
- Independent Component Analysis for Image Recovery Using SOM-Based Noise Detection(Digital Signal Processing)
- Convolutive Nonlinear Separation with Unsupervised Neural Network
- A Novel Neural Detector Based on Self-Organizing Map for Frequency-Selective Rayleigh Fading Channel(Digital Signal Processing)
- A Compensating Method Based on SOM for Nonlinear Distortion in 16-QAM-OFDM System(Nonlinear Problems)
- Combining Recurrent Neural Networks with Self-Organizing Map for Channel Equalization
- A Design Method of Block Interleaver for Turbo Codes Based on Low Correlation Coefficient
- An Improved Bit Allocation Method in DMT System
- Channel Equalization Using Recurrent Neural Networks with Real-Time Recurrent Learning
- A New Algorithm to Rectify the Frequency Bias in Periodic Signal Measurement
- Analysis of a Neural Detector Based on Self-Organizing Map in a 16 QAM System
- SB-11-2 An Improved Loading Algorithm for DMT Technology
- A Stop Criterion for Turbo Code to Reduce Decoding Iterations
- Detection of Nonlinearly Distorted M-ary QAM Signals Using Self-Organizing Map
- Multi-Input Single-Output Nonlinear Adaptive Digital Filters Using Recurrent Neural Networks
- A Novel Stop Criterion for Turbo Decoding
- On the Capacity of Twisted-Wire Pair under AWGN and FEXT Noise Environment
- Design of Class DE Inverter with Second Order Constant K Band-Pass Filter(Nonlinear Circuits,Nonlinear Theory and its Applications)
- Post-Processing for Restoring Edges and Removing Artifacts of Low Bit Rates Wavelet-Based Image
- Nonlinear Blind Source Separation Method for X-Ray Image Separation(Selected Papers from the 18th Workshop on Circuits and Systems in Karuizawa)
- Investigation of Class E Amplifier with Nonlinear Capacitance for Any Output Q and Finite DC-Feed Inductance(Selected Papers from the 18th Workshop on Circuits and Systems in Karuizawa)
- Novel Design Procedure for MOSFET Class E Oscillator(Nonlinear Theory and its Applications)
- B-5-195 A SOM Compensator for TWTA in 16-QAM-OFDM System
- A Design Method for Blind Equalizers Using Multilayer Perceptrons
- An Adaptive Decision Feedback Equalizer Using Radial Basis Function (適応信号処理特集号)
- Channel Equalization Using Complex-Valued Recurrent Neural Networks (適応信号処理特集号)
- A-1-43 A Method of Robust Model Matching Control in the Presence of Disturbances
- A Fast Block Matching Algorithm Based on Motion Vector Correlation and Integral Projections
- Application of Fast Biorthogonal Spline Wavelet Transform in Automatic Inspection
- An Efficient Algorithm for Detecting Singularity in Signals Using Wavelet Transform(Degital Signal Processing)
- D-11-14 A Stable Algorithm for the Inverse Generalized Radon Transform
- A Method for Adaptive Control of Nonminimum Phase Continuous-Time Systems Based on Pole-Zero Placement
- A New Method for the Self-Tuning Control of Nonminimum Phase Discrete-Time Systems in the Presence of Disturbances
- On Self-Tuning Control of Nonminimum Phase Discrete-Time Stochastic Systems
- A New Method for Self-Tuning Control of Nonminimum Phase Continuous-Time Systems Based on Pole-Zero Placement
- Model Reference Adaptive Control for MIMO Nonminimum Phase Discrete-Time Systems Using Approximate Inverse Systems
- A-7 A Method of Model Reference Adaptive Control for Multivariable Nonminimum Phase Discrete-Time Systems
- A Method of Robust Model Reference Adaptive Control for Diserete-Time Systems in the Presence of Unmodeled Dynamics
- A Method of Model Matching Control for Continuous-Time Systemes in the Presence of Arbitrarily Bounded Disturbances
- Application of Neural Networks to MRAC for the Nonlinear Magnetic Levitation System
- A Method of Simple Adaptive Control for Nonlinear Systems Using Neural Networks(Systems and Control)
- Chattering Free Sliding Mode Control in Magnetic Levitation System
- Simple Adaptive Control for MIMO Nonlinear Continuous-Time Systems Using Neural Networks
- SAC for Nonlinear Systems Using Elman Recurrent Neural Networks(Special Section on Digital Signal Processing)
- A Method of Model Reference Adaptive Control for MIMO Nonlinear Systems Using Neural Networks
- 3D Face Recognition Using Parallel Pyramid Neural Networks
- A Method of 3D Face Recognition Based on Contour Maps
- Perfect Tracking Control of Nonminimum Phase Systems in Magnetic Levitation System(Systems and Control)
- A Design Method of Parallel Fast RLS Second-Order Adaptive Volterra Filter(Nonlinear Problems)
- A Method for Parallel Adaptive Volterra Filter Using RLS Algorithm
- Design of Noise Canceller Using Parallel Recursive Least-Squares Adaptive Volterra Filter (Special Issue on Nonlinear Circuits and Signal Processing)
- Invited Paper Adaptive Noise Cancellation and Adaptive Control for Nonlinear Systems Using Neural Networks
- Scalable Authentication and Nonrepudiation Technique for JPEG2000 Images Using JPSEC Protection Tools(Image Media Quality)
- Design of Class DE Amplifier with Nonlinear Shunt Capacitances for Any Output Q
- A control method for nonlinear systems using simple adaptive control with multiple neural networks
- Ultrasonographic Diagnosis of Cirrhosis Based on Preprocessing Using DCT
- Estimation of ARMAX Systems and Strictly Positive Real Condition
- Quantitative Diagnosis on Magnetic Resonance Images of Chronic Liver Disease Using Neural Networks (Special Section on Nonlinear Theory and Its Applications)
- Neural Network Approach to Characterization of Cirrhotic Parenchymal Echo Patterns (Special Section of Papers Selected from the 7th Digital Signal Processing Symymposium
- Maximum Likelihood Estimation of Autoregressive Systems Degraded by Colored Noise
- Identification of Two-Dimensional Autoregressive Systems from Observations Containing Noise
- A Method of Noise Removal for Color Degraded Images Using Neural Networks
- B-8-11 DMT Modulation Technology in ADSL System
- A New Transformed Input-Domain ANFIS for Highly Nonlinear System Modeling and Prediction
- Image Compression by New Sub-Image Block Classification Techniques Using Neural Networks