Quantization-Noise Suppression for Uplink eCPRI Assisted by Wireless-Channel Estimation Feedback

2018 ◽  
Author(s):  
Longsheng Li ◽  
Meihua Bi ◽  
Xin Miao ◽  
Yan Fu ◽  
Mingxia Zhang ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Noise Suppression ◽  
Wireless Channel ◽  
Quantization Noise

scholarly journals Enhanced Wireless Channel Estimation Through Parametric Optimization of Hybrid Ray Launching-Collaborative Filtering Technique

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 83070-83080
Author(s):  
Fran Casino ◽  
Peio Lopez-Iturri ◽  
Erik Aguirre ◽  
Leyre Azpilicueta ◽  
Francisco Falcone ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Collaborative Filtering ◽  
Parametric Optimization ◽  
Wireless Channel ◽  
Filtering Technique ◽  
Ray Launching

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.

scholarly journals A Novel Noise Suppression Channel Estimation Method Based on Adaptive Weighted Averaging for OFDM Systems

Symmetry ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 997 ◽  
Author(s):  
Zhang ◽  
Zhou ◽  
Wang
Keyword(s):  
Fourier Transform ◽  
Channel Estimation ◽  
Fast Fourier Transform ◽  
Orthogonal Frequency Division Multiplexing ◽  
Noise Suppression ◽  
Estimation Method ◽  
Weighted Averaging ◽  
Doppler Spread ◽  
Estimation Methods ◽  
Ofdm Systems

Orthogonal frequency division multiplexing (OFDM) systems have inherent symmetric properties, such as coding and decoding, constellation mapping and demapping, inverse fast Fourier transform (IFFT) and fast Fourier transform (FFT) operations corresponding to multi-carrier modulation and demodulation, and channel estimation is a necessary module to resist channel fading in the OFDM system. However, the noise in the channel will significantly affect the accuracy of channel estimation, which further affects the recovery quality of the final received signals. Therefore, this paper proposes an efficient noise suppression channel estimation method for OFDM systems based on adaptive weighted averaging. The basic idea of the proposed method is averaging the last few channel coefficients obtained from coarse estimation to suppress the noise effect, while the average frame number is adaptively adjusted by combining Doppler spread and signal-to-noise ratio (SNR) information. Meanwhile, to better combat the negative effect brought by Doppler spread and inter-carrier interference (ICI), the proposed method introduces a weighting factor to correct the weighted value of each frame in the averaging process. Simulation results show that the proposed channel estimation method is effective and provides better performance compared with other conventional channel estimation methods.

scholarly journals Iterative Channel Estimation for the Chinese Digital Television Terrestrial Broadcasting Systems with the Multiple-Antenna Receivers

2012 ◽  
Vol 6-7 ◽  
pp. 439-444
Author(s):  
Zi Wei Zheng
Keyword(s):  
Fourier Transform ◽  
Channel Estimation ◽  
Fast Fourier Transform ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multipath Fading ◽  
Wireless Channel ◽  
Digital Television ◽  
Frequency Division Multiplexing ◽  
Multiple Antenna ◽  
Frequency Division

Orthogonal frequency division multiplexing is an effective against multipath fading and high data throughput wireless channel transmission technology. Assistance with the inverse fast Fourier transform and fast Fourier transform operation, orthogonal frequency division multiplexing modulation and demodulation operations of the system convenient and convenient hardware implementation, orthogonal frequency division multiplexing, so in the modern digital television terrestrial broadcasting the system is widely used to support high performance bandwidth-efficient multimedia services. Broadband multi-carrier orthogonal frequency division multiplexing with multi-antenna and multi-antenna receiving system, to increase the diversity gain and improve the capacity of the system in different multipath fading channel. Accurate channel estimation in a simple channel equalization and decoding of broadband multi-carrier orthogonal frequency division multiple-antenna receiver and channel estimation accuracy and multiplexing system is very important, is the key to the performance of the overall broadband multi-carrier orthogonal frequency division multiplexing system in the multi-antenna receiver bit error rate. In this paper, iterative channel estimation to plan for digital terrestrial television broadcasting broadband multi-carrier orthogonal frequency division multiple antenna receiver multiplexing system proposal.

scholarly journals Channel Estimation in DCT-Based OFDM

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Yulin Wang ◽  
Gengxin Zhang ◽  
Zhidong Xie ◽  
Jing Hu
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multipath Fading ◽  
Wireless Channel ◽  
Least Square ◽  
System Throughput ◽  
Multipath Fading Channel ◽  
Channel Response ◽  
Coherent Demodulation ◽  
And Performance

This paper derives the channel estimation of a discrete cosine transform- (DCT-) based orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective multipath fading channel. Channel estimation has been proved to improve system throughput and performance by allowing for coherent demodulation. Pilot-aided methods are traditionally used to learn the channel response. Least square (LS) and mean square error estimators (MMSE) are investigated. We also study a compressed sensing (CS) based channel estimation, which takes the sparse property of wireless channel into account. Simulation results have shown that the CS based channel estimation is expected to have better performance than LS. However MMSE can achieve optimal performance because of prior knowledge of the channel statistic.

scholarly journals Adaptive Power Allocation and Splitting with Imperfect Channel Estimation in Energy Harvesting Based Self-Organizing Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Kisong Lee ◽  
JeongGil Ko
Keyword(s):  
Energy Transfer ◽  
Energy Harvesting ◽  
Channel Estimation ◽  
Power Allocation ◽  
Wireless Channel ◽  
Network Systems ◽  
Adaptive Power ◽  
Continuous Power ◽  
Self Organizing Networks ◽  
Self Organizing

As miniature-sized embedded computing platforms are ubiquitously deployed to our everyday environments, the issue of managing their power usage becomes important, especially when they are used in energy harvesting based self-organizing networks. One way to provide these devices with continuous power is to utilize RF-based energy transfer. Previous research in RF-based information and energy transfer builds up on the assumption that perfect channel estimation is easily achievable. However, as our preliminary experiments and many previous literature in wireless network systems show, making perfect estimations of the wireless channel is extremely challenging due to their quality fluctuations. To better reflect reality, in this work, we introduce an adaptive power allocation and splitting (APAS) scheme which takes imperfect channel estimations into consideration. Our evaluation results show that the proposed APAS scheme achieves near-optimal performances for transferring energy and data over a single RF transmission.

scholarly journals Wireless channel estimation in OFDM systems based on collaborative filtering techniques

2019 ◽  
Vol 70 (3) ◽  
pp. 244-252
Author(s):  
Velimir Švedek ◽  
Adrian Satja Kurdija ◽  
Željko Ilić
Keyword(s):  
Channel Estimation ◽  
Collaborative Filtering ◽  
Orthogonal Frequency Division Multiplexing ◽  
Predictive Accuracy ◽  
Spline Interpolation ◽  
Estimation Algorithm ◽  
Wireless Channel ◽  
Estimation Methods ◽  
Ofdm Systems ◽  
Interpolation Methods

Abstract In this paper, a new channel estimation algorithm in Orthogonal Frequency Division Multiplexing (OFDM) systems is proposed. The proposed algorithm is suitable for cases with low density of pilot sub-carriers, where standard interpolation methods (linear, second order and cubic spline interpolation) are inaccurate. The algorithm improves the interpolation methods by employing memory based collaborative filtering (CF) techniques which are less sensitive to the number and location of the pilot subcarriers. CF algorithms are usually used in the context of recommender systems (e-commerce) for predictions of the unknown user-item ratings based on known values of similar users. The advantage of CF is the ability to e ciently produce quality predictions with highly sparse data. Computer simulations are used to verify the proposed channel estimation algorithm and demonstrate that the proposed algorithm improves predictive accuracy metrics, such as Root Mean Squared Error (RMSE), compared to usual estimation methods.

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