scholarly journals Site-specific millimeter-wave compressive channel estimation algorithms with hybrid MIMO architectures

2021 ◽  
Vol 2 (4) ◽  
pp. 9-26
Author(s):  
Sai Subramanyam Thoota ◽  
Dolores Garcia Marti ◽  
�zlem Tugfe Demir ◽  
Rakesh Mundlamuri ◽  
Joan Palacios ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Orthogonal Frequency Division Multiplexing ◽  
Wireless Channel ◽  
Data Driven ◽  
Site Specific ◽  
Digital Architecture ◽  
Estimation Algorithms ◽  
Model Based ◽  
Wide Range

In this paper, we present and compare three novel model-cum-data-driven channel estimation procedures in a millimeter-wave Multi-Input Multi-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) wireless communication system. The transceivers employ a hybrid analog-digital architecture. We adapt techniques from a wide range of signal processing methods, such as detection and estimation theories, compressed sensing, and Bayesian inference, to learn the unknown virtual beamspace domain dictionary, as well as the delay-and-beamspace sparse channel. We train the model-based algorithms with a site-specific training dataset generated using a realistic ray tracing-based wireless channel simulation tool. We assess the performance of the proposed channel estimation algorithms with the same site's test data. We benchmark the performance of our novel procedures in terms of normalized mean squared error against an existing fast greedy method and empirically show that model-based approaches combined with data-driven customization unanimously outperform the state-of-the-art techniques by a large margin. The proposed algorithms were selected as the top three solutions in the "ML5G-PHY Channel Estimation Global Challenge 2020" organized by the International Telecommunication Union.

scholarly journals Model-based compressed sensing algorithms for MIMO- OFDM channel estimation

2018 ◽  
Vol 7 (2.4) ◽  
pp. 5
Author(s):  
P N. Jayanthi ◽  
S Ravishankar
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Orthogonal Frequency Division Multiplexing ◽  
Wireless Channel ◽  
Least Square ◽  
Modulation Scheme ◽  
Mean Square ◽  
Least Mean Square ◽  
Model Based ◽  
Mimo Ofdm

High data rates on the wireless channel can be achieved by combining orthogonal frequency division multiplexing (OFDM) with multiple input multiple output (MIMO) communication modulation scheme. MIMO-OFDM system impulse response of the channel is approximately sparse. Sparse channelestimation can be done using Compressive Sensing (CS) techniques. In this paper, a low complexity model based CoSaMp Compressive Sensing (CS) algorithm with conventional tools namely Least Square (LS) and Least Mean Square (LMS) are used for MIMO-OFDM channel estimation. Simulation results show amodel based CoSaMP for MIMO-OFDM channel estimation with LMS tool the Normalized Mean Square Error(NMSE)reduced by 34%with very reduced complexity.

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 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 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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