Proceedings ArticleDOI
A neural network based channel estimation scheme for OFDM system
Kalpesh Hiray,K. Vinoth Babu +1 more
- pp 0438-0441
TLDR
A multi layered perceptron (MLP) based neural network (NN) which is trained with back propagation (BP) algorithm to estimate the channel characteristics of OFDM system and demonstrates that proposed schemes offers superior performance over the conventional LMS scheme under noisy environment.Abstract:
Recent wireless standards prefer orthogonal frequency division multiplexing (OFDM) along with multiple input multiple output (MIMO) to offer high spectral efficiency services for any time anywhere environment. The full advantages of MIMO-OFDM is accessible only when there exist perfect channel information. Improper channel estimation leads to poor quality. In this work, we have developed a multi layered perceptron (MLP) based neural network (NN) which is trained with back propagation (BP) algorithm to estimate the channel characteristics of OFDM system. Monte-Carlo simulations are used to evaluate the performance of the proposed scheme with the conventional Least Mean Square (LMS) algorithm. The simulation results demonstrate that proposed schemes offers superior performance over the conventional LMS scheme under noisy environment.read more
Citations
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Journal ArticleDOI
Massive MIMO Systems for 5G and Beyond Networks-Overview, Recent Trends, Challenges, and Future Research Direction.
Robin Chataut,Robert Akl +1 more
TL;DR: This paper presents a comprehensive overview of the key enabling technologies required for 5G and 6G networks, highlighting the massive MIMO systems and discusses all the fundamental challenges related to pilot contamination, channel estimation, precoding, user scheduling, energy efficiency, and signal detection.
Journal ArticleDOI
Deep Neural Networks for Channel Estimation in Underwater Acoustic OFDM Systems
TL;DR: Two types of channel estimators based on deep neural networks (DNNs) are proposed with a novel training strategy for UWA-OFDM systems, which are superior to the MMSE algorithm and achieve better performance using 16QAM than 32QAM, 64QAM.
Journal ArticleDOI
Adaptive Modulation and Coding Using Neural Network Based SNR Estimation
TL;DR: The proposed Adaptive Modulation and Coding (AMC) scheme enabled by Artificial Neural Network (ANN) aided Signal-to-Noise power Ratio (SNR) estimation is robust especially in high mobility environment since the PSD appearance is hardly influenced by the Doppler shift.
Journal ArticleDOI
Secure Cooperative Transmission With Imperfect Channel State Information Based on BPNN
TL;DR: Back propagation neural network (BPNN) is employed for a high accuracy channel estimation to simulate a realistic security communication scenario and the numerical results show that the channel estimation errors result in a decrease in secrecy rate, but the BPNN channel estimator still can guarantee secure transmission that verifies the feasibility of the application of physical layer security.
Posted Content
A Markovian Model-Driven Deep Learning Framework for Massive MIMO CSI Feedback
TL;DR: Leveraging a Markovian model, a deep convolutional neural network (CNN)-based framework called MarkovNet is developed to efficiently encode CSI feedback to improve accuracy and efficiency and explores important physical insights including spherical normalization of input data and deep learning network optimizations in feedback compression.
References
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Journal ArticleDOI
Training feedforward networks with the Marquardt algorithm
TL;DR: The Marquardt algorithm for nonlinear least squares is presented and is incorporated into the backpropagation algorithm for training feedforward neural networks and is found to be much more efficient than either of the other techniques when the network contains no more than a few hundred weights.
Book
Neural network design
TL;DR: This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules, as well as methods for training them and their applications to practical problems.
Book
Statistical Digital Signal Processing and Modeling
TL;DR: The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering.
Book
MIMO-OFDM Wireless Communications with MATLAB
TL;DR: In this article, the authors provide a comprehensive introduction to the theory and practice of wireless channel modeling, OFDM, and MIMO, using MATLAB programs to simulate the various techniques on a wireless network.
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