Packet Level Wireless Channel Model for OFDM System Using SHLPNs

2015 ◽  
pp. 79-97
Author(s):  
Lei Lei ◽  
Chuang Lin ◽  
Zhangdui Zhong
Keyword(s):  
Channel Model ◽  
Wireless Channel ◽  
Ofdm System ◽  
Wireless Channel Model

scholarly journals Projection wavelet weighted twin support vector regression for OFDM system channel estimation

2020 ◽  
Author(s):  
Lidong Wang ◽  
Yimei Ma ◽  
Xudong Chang ◽  
Chuang Gao ◽  
Qiang Qu ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Support Vector Regression ◽  
Orthogonal Frequency Division Multiplexing ◽  
Channel Model ◽  
Wireless Channel ◽  
Estimation Methods ◽  
Support Vector ◽  
Ofdm System ◽  
Twin Support Vector Regression ◽  
Empirical Risk

Abstract In this paper, an efficient projection wavelet weighted twin support vector regression (PWWTSVR) based orthogonal frequency division multiplexing system (OFDM) system channel estimation algorithm is proposed. Most Channel estimation algorithms for OFDM systems are based on the linear assumption of channel model. In the proposed algorithm, the OFDM system channel is consumed to be nonlinear and fading in both time and frequency domains. The PWWTSVR utilizes pilot signals to estimate response of nonlinear wireless channel, which is the main work area of SVR. Projection axis in optimal objective function of PWWRSVR is sought to minimize the variance of the projected points due to the utilization of a priori information of training data. Different from traditional support vector regression algorithm, training samples in different positions in the proposed PWWTSVR model are given different penalty weights determined by the wavelet transform. The weights are applied to both the quadratic empirical risk term and the first-degree empirical risk term to reduce the influence of outliers. The final regressor can avoid the overfitting problem to a certain extent and yield great generalization ability for channel estimation. The results of numerical experiments show that the propose algorithm has better performance compared to the conventional pilot-aided channel estimation methods.

A General 3-D Non-Stationary 5G Wireless Channel Model

2018 ◽  
Vol 66 (7) ◽  
pp. 3065-3078 ◽  
Author(s):  
Shangbin Wu ◽  
Cheng-Xiang Wang ◽  
el-Hadi M. Aggoune ◽  
Mohammed M. Alwakeel ◽  
Xiaohu You
Keyword(s):  
Channel Model ◽  
Wireless Channel ◽  
Wireless Channel Model

Error Correction of Coding of Wireless Transmission Channel of Digital Images

2014 ◽  
Vol 536-537 ◽  
pp. 771-775
Author(s):  
Ming Kai Yue ◽  
Jia Hao Deng
Keyword(s):  
Error Correction ◽  
Channel Model ◽  
Simulation Analysis ◽  
Turbo Code ◽  
Signal To Noise Ratio ◽  
Wireless Channel ◽  
Wireless Transmission ◽  
Transmission Channel ◽  
Noise Interference ◽  
Wireless Channel Model

The wireless channel model, which was suitable with the complex environment of battlefield, was built by analyzing the digital image of wireless transmission channel, the transmission characteristics and the fading type. The error correction of coding for the compressed code stream of image was carried out specifically with Turbo code, and the Simulink simulation model was designed. The system simulation analysis was carried out for the performance parameters that affect the Turbo code and the BER performance of as-built wireless channel model. The results showed that the Turbo code is a kind of error correction one, which is anti-fading and strong interference among codes. It can not only reach higher peak signal to noise ratio, but also transmit more steadily and more reliably in the changeable channel environment under noise interference. Furthermore, the turbo can be applied for code correction and controlling.

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