scholarly journals Optimization of Iterative Channel State Estimation Algorithms in SCMA System

2018 ◽  
pp. 23-34
Author(s):  
V. P. Klimentyev ◽  
A. B. Sergienko
Keyword(s):  
Channel Estimation ◽  
State Estimation ◽  
Spectral Efficiency ◽  
Signal To Noise Ratio ◽  
Iterative Algorithms ◽  
Channel State ◽  
Computational Costs ◽  
Channel State Estimation ◽  
Low Snr ◽  
Estimation Algorithms

Optimization of iterative algorithms for channel state estimation in a sparse coding multiple-access system (SCMA) is performed to reduce computational costs of the receiver. It is shown that when a signal-to-noise ratio (SNR) does not exceed 10 dB, one iteration of the algorithm is sufficient, and an increase in the number of iterations does not lead to an increase in spectral efficiency. Simulation demonstrates a possibility of a reasonable choice of the total number of decoder iterations and their distribution between different stages of the channel estimation. For an uncoded system, iterative re-estimation of the channel is proposed, as well as ways to reduce computational costs during its calculation. In the coded system, at a low SNR the achieved spectral efficiency values are approximately similar to those with pilot-only channel estimation. The article provides recommendations for the placement of data symbols and pilot signals in re-source blocks to increase the system spectral efficiency.

scholarly journals An Improved Channel Estimation Algorithm Based on WD-DDA in OFDM System

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Dan Wang ◽  
Zhiqiang Mei ◽  
Jiamin Liang ◽  
Jinzhi Liu
Keyword(s):  
Channel Estimation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
Transform Domain ◽  
Ofdm System ◽  
Low Snr ◽  
Estimation Algorithms ◽  
Residual Noise ◽  
First Time

Channel estimation is the key technology to ensure reliable transmission in orthogonal frequency division multiplexing (OFDM) system. In order to improve the accuracy of the channel estimation algorithm in a low signal-to-noise ratio (SNR) channel environment, in this paper, we proposed an improved channel estimation algorithm based on the transform domain. The improved algorithm with wavelet denoising (WD) and distance decision analysis (DDA) to perform secondary denoising on the channel estimation algorithm based on the transform domain is proposed. First, after the least-squares (LS) algorithm, WD is used to denoise for the first time, then the DDA is used to further suppress the residual noise in the transform domain, and the important channel taps are screened out. Simulation results show that the proposed algorithm can improve the detection performance of existing channel estimation algorithms based on transform domain in low SNR.

scholarly journals Optimal adaptive diversity watermarking with channel state estimation

2001 ◽  
Author(s):  
Sviatoslav V. Voloshynovskiy ◽  
Frederic Deguillaume ◽  
Shelby Pereira ◽  
Thierry Pun
Keyword(s):  
State Estimation ◽  
Channel State ◽  
Channel State Estimation ◽  
Adaptive Diversity

scholarly journals Hierarchical Data Decision Aided 2-Source BPSK H-MAC Channel Phase Estimator with Feed-Back Gradient Solver for WPNC Networks and Its Equivalent Model

Information ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 40 ◽  
Author(s):  
Jan Sykora
Keyword(s):  
State Estimation ◽  
Indicator Function ◽  
Equivalent Model ◽  
Hierarchical Data ◽  
Decode And Forward ◽  
Channel State ◽  
Physical Layer Network Coding ◽  
Channel State Estimation ◽  
Stable Domain ◽  
Individual Source

This paper focuses on the channel state estimation (CSE) problem in parametrized Hierarchical MAC (H-MAC) stage in Wireless Physical Layer Network Coding (WPNC) networks with Hierarchical Decode and Forward (HDF) relay strategy. We derive a non-pilot based H-MAC channel phase estimator for 2 BPSK alphabet sources. The CSE is aided only by the knowledge of H-data decisions. At HDF relay, there is no information on individual source symbols available. The estimator is obtained by a marginalization over the hierarchical dispersion. The estimator uses a gradient additive update solver and the indicator function (gradient) is derived in exact closed form and in approximations for low and high SNR. We analyze the properties of the equivalent solver model, particularly the equivalent gradient detector characteristics and its main stable domain properties, and also the detector gain and equivalent noise properties under a variety of channel parameterization scenarios.

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