ESTIMATION METHODS OF A CHANNEL WITH SPATIAL MODULATION BASED ON CORRELATION

2021 ◽  
pp. 106-110
Author(s):  
О.Н. Чирков
Keyword(s):  
Channel Estimation ◽  
Communication Channel ◽  
Energy Savings ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Spatial Modulation ◽  
Mimo Channel ◽  
Estimation Methods ◽  
Signal Ratio ◽  
Single Stream

Рассматриваются методы оценки канала связи с пространственной модуляцией. Данный вид модуляции представляет собой методику однопотоковой передачи данных с несколькими входами и несколькими выходами (MIMO), при которой одновременно активируется только одна передающая антенна. Пространственная модуляция позволяет добиться полного исключения межканальных помех, а также демонстрирует большую экономию энергии в радиочастотной цепи. Однако, в отличие от многопоточных систем MIMO, оценка канала для пространственной модуляции становится проблемой, поскольку канал MIMO не может быть оценен на одном этапе передачи по единственному потоку. На основании этого факта была предложена новая схема оценки канала, которая использует корреляцию каналов и совместно оценивает каналы для разных передающих антенн. Предложенный метод обеспечивает тот же период оценки, что и многопоточные схемы MIMO. Исследовано изменение количества передаваемых пилот-сигналов при пространственной модуляции как для традиционных, так и для новых методов оценки канала связи. Уравновешивая точность и объем данных, можно достичь оптимального отношения пилот-сигналов для максимальной пропускной способности канала. Результаты моделирования показывают, что новый подход оценки превосходит традиционный метод с гораздо более низким оптимальным коэффициентом количества пилотов The article considers methods for estimating a communication channel with spatial modulation. This type of modulation is a single-stream multiple-input multiple-output (MIMO) technique in which only one transmit antenna is activated at a time. Spatial modulation allows for complete elimination of inter-channel interference, and also demonstrates great energy savings in the RF circuit. However, unlike multi-stream MIMO systems, channel estimation for spatial modulation becomes a problem because a MIMO channel cannot be estimated in a single transmission step on a single stream. Based on this fact, I proposed a new channel estimation scheme that uses channel correlation and jointly estimates channels for different transmit antennas. The proposed method provides the same evaluation period as multithreaded MIMO schemes. The change in the number of transmitted pilot-signals with spatial modulation is investigated for both traditional and new methods of estimation of the communication channel. By balancing accuracy and data volume, an optimal pilot signal ratio can be achieved for maximum channel throughput. Simulation results show that the new scoring approach outperforms the traditional method with a much lower optimal pilot count ratio

scholarly journals GAMP-SBL-based channel estimation for millimeter-wave MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Jianfeng Shao ◽  
Xianpeng Wang ◽  
Xiang Lan ◽  
Zhiguang Han ◽  
Ting Su
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Mimo Systems ◽  
Learning Algorithm ◽  
Mimo System ◽  
Estimation Algorithm ◽  
Mimo Channel ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Signal Recovery

AbstractBased on the finite scattering characters of the millimeter-wave multiple-input multiple-output (MIMO) channel, the mmWave channel estimation problem can be considered as a sparse signal recovery problem. However, most traditional channel estimation methods depend on grid search, which may lead to considerable precision loss. To improve the channel estimation accuracy, we propose a high-precision two-stage millimeter-wave MIMO system channel estimation algorithm. Since the traditional expectation–maximization-based sparse Bayesian learning algorithm can be applied to handle this problem, it spends lots of time to calculate the E-step which needs to compute the inversion of a high-dimensional matrix. To avoid the high computation of matrix inversion, we combine damp generalized approximate message passing with the E-step in SBL. We then improve a refined algorithm to handle the dictionary matrix mismatching problem in sparse representation. Numerical simulations show that the estimation time of the proposed algorithm is greatly reduced compared with the traditional SBL algorithm and better estimation performance is obtained at the same time.

scholarly journals Improvement of Complexity and Performance of Least Square Based Channel Estimation in MIMO System

2016 ◽  
Vol 1 ◽  
pp. 11
Author(s):  
Anand Kumar Sah ◽  
Arun Kumar Timalsina
Keyword(s):  
Channel Estimation ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Estimation Method ◽  
Vital Role ◽  
Least Square ◽  
Mimo Channel ◽  
Fourth Generation ◽  
Simulation Results

<p>Multiple-input multiple-output (MIMO) systems play a vital role in fourth generation wireless systems to provide advanced data rate. In this paper, a better performance and reduced complexity channel estimation method is proposed for MIMO systems based on matrix factorization. This technique is applied on training based least squares (LS) channel estimation using STBC for performance improvement. Simulation results indicate that the proposed method not only alleviates the performance of MIMO channel estimation but also significantly reduces the complexity caused by matrix inversion. The performance evaluations are validated through computer simulations using MATLAB in terms of bit error rate (BER) for modified LS with LS and MMSE channel estimation techniques. Simulation results show that the BER performance and complexity of the proposed method clearly outperforms the conventional LS channel estimation method.</p><p><em>Journal of Advanced College of Engineering and Management, Vol. 1, 2015</em>, pp. 11-24</p>

scholarly journals GAMP-SBL Based Channel Estimation for Millimeter-Wave MIMO Systems

2021 ◽  
Author(s):  
Jianfeng Shao ◽  
Xianpeng Wang ◽  
Xiang Lan ◽  
Zhiguang Han ◽  
Ting Su
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Message Passing ◽  
Mimo Systems ◽  
Mimo System ◽  
Estimation Algorithm ◽  
Mimo Channel ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Signal Recovery

Abstract Based on the finite scattering characters of the millimeter-wave multiple-input multiple-output (mmWave MIMO) channel, the mmWave channel estimation problem can be considered as a sparse signal recovery problem. However, most traditional channel estimation methods depend on grid search, which may lead to considerable precision loss. To improve the channel estimation accuracy, we propose a high-precision two-stage millimeter-wave MIMO system channel estimation algorithm. Since the traditional expectation-maximization based sparse Bayesian learning (EM-SBL) algorithm can be applied to handle this problem, however, it spends lots of time to calculate the E-step which needs to compute the inversion of a high dimensional matrix. To avoid the high computation of matrix inversion, we combine damp generalized approximate message passing (DGAMP) with the E-step in SBL. We then improve a refined algorithm to handle the dictionary matrix mismatching problem in sparse representation. Numerical simulations show that the estimation time of the proposed algorithm is greatly reduced compared with the traditional SBL algorithm and better estimation performance is obtained at the same time.

scholarly journals Optimization of Training Signal Transmission for Estimating MIMO Channel under Antenna Mutual Coupling Conditions

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Xia Liu ◽  
Marek E. Bialkowski
Keyword(s):  
Channel Estimation ◽  
Mutual Coupling ◽  
Minimum Mean Square Error ◽  
Signal Transmission ◽  
Multiple Input Multiple Output ◽  
Least Square ◽  
Mimo Channel ◽  
Estimation Methods ◽  
Estimation Errors ◽  
Training Signal

This paper reports investigations on the effect of antenna mutual coupling on performance of training-based Multiple-Input Multiple-Output (MIMO) channel estimation. The influence of mutual coupling is assessed for two training-based channel estimation methods, Scaled Least Square (SLS) and Minimum Mean Square Error (MMSE). It is shown that the accuracy of MIMO channel estimation is governed by the sum of eigenvalues of channel correlation matrix which in turn is influenced by the mutual coupling in transmitting and receiving array antennas. A water-filling-based procedure is proposed to optimize the training signal transmission to minimize the MIMO channel estimation errors.

scholarly journals Research of the Channel Estimation in Wireless Communication Systems

2019 ◽  
Vol 25 ◽  
pp. 01002 ◽  
Author(s):  
Lili Zhao ◽  
Peng Zhang ◽  
Qicai Dong ◽  
Xiangyang Huang ◽  
Jianhua Zhao ◽  
...  
Keyword(s):  
Wireless Communication ◽  
Channel Estimation ◽  
Communication Technology ◽  
Communication Systems ◽  
Communication Channel ◽  
Data Transfer ◽  
Estimation Methods ◽  
Wireless Communication Systems ◽  
Data Transfer Rate

Wireless communication technology has been developed rapidly after entering the 21st century. Data transfer rate increased significantly as well as the bandwidth became wider and wider from 2G to 4G in wireless communication systems. Channel estimation is an import part of any communication systems; its accuracy determines the quality of the whole communication. Channel estimation methods of typical wireless communication systems such as UWB, 2G and 3G have been researched.

scholarly journals Optical spatial modulation design

2020 ◽  
Vol 378 (2169) ◽  
pp. 20190195 ◽  
Author(s):  
T. Cogalan ◽  
H. Haas ◽  
E. Panayirci
Keyword(s):  
Mimo Systems ◽  
Direct Detection ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Pulse Amplitude ◽  
Visible Light Communication ◽  
Performance Model ◽  
Spatial Modulation ◽  
Error Performance ◽  
Led Array

Visible light communication (VLC) systems are inherently signal-to-noise ratio (SNR) limited due to link budget constraints. One favourable method to overcome this limitation is to focus on the pre-log factors of the channel capacity. Multiple-input multiple-output (MIMO) techniques are therefore a promising avenue of research. However, inter-channel interference in MIMO limits the achievable capacity. Spatial modulation (SM) avoids this limitation. Furthermore, the performance of MIMO systems in VLC is limited by the similarities among spatial channels. This limitation becomes particularly severe in intensity modulation/direct detection (IM/DD) systems because of the lack of phase information. The motivation of this paper is to propose a system that results in a multi-channel transmission system that enables reliable multi-user optical MIMO SM transmission without the need for a precoder, power allocation algorithm or additional optics at the receiver. A general bit error performance model for the SM system is developed for an arbitrary number of light-emitting diodes (LEDs) in conjunction with pulse amplitude modulation. Based on this model, an LED array structure is designed to result in spatially separated multiple channels by manipulating the transmitter geometry. This article is part of the theme issue ‘Optical wireless communication’.

A New Method for MIMO-OFDM Channel Estimation Based on Discrete Wavelet Transform

2012 ◽  
Vol 182-183 ◽  
pp. 2066-2070
Author(s):  
Hui Shi ◽  
Ren Wang Song ◽  
Gang Fei Wang
Keyword(s):  
Wavelet Transform ◽  
Channel Estimation ◽  
Discrete Wavelet Transform ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Input Multiple Output ◽  
Mimo Channel ◽  
Discrete Wavelet ◽  
Input Multiple Output ◽  
Estimation Scheme ◽  
Mimo Ofdm

This paper puts forward a suitable channel estimation scheme for multiple input multiple output and orthogonal frequency division multiplexing system (MIMO-OFDM) based on discrete wavelet transform. According to the least-squares standard (LS), this plan uses pilot to estimate the unit impulse response of MIMO channel firstly, then does wavelet denoising in changing domain, in order to reduce the frequency spectrum leakage and improve the estimation precision. At the same time, this method does not need to know channel information in advance, and can follow up the changes of channel on time with good error rate performance.

scholarly journals Channel Covariance Identification in FDD Massive MIMO Systems

Proceedings ◽  
2018 ◽  
Vol 2 (18) ◽  
pp. 1176 ◽  
Author(s):  
José González-Coma ◽  
Pedro Suárez-Casal ◽  
Paula Castro ◽  
Luis Castedo
Keyword(s):  
Channel Estimation ◽  
Covariance Matrix ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Estimation Methods ◽  
Training Sequences

Channel estimation for Massive MIMO systems has drawn a lot of attention in the last years. A number of estimation methods rely on the knowledge of the channel covariance matrix to operate. However, this covariance is not known in practice, and it should be acquired. In this work, we investigate different techniques for covariance identification under the assumption of very short training sequences.

scholarly journals Superimposed Training-Based Channel Estimation for MIMO Relay Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaoyan Xu ◽  
Jianjun Wu ◽  
Shubo Ren ◽  
Lingyang Song ◽  
Haige Xiang
Keyword(s):  
Channel Estimation ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Relay Network ◽  
Mimo Channel ◽  
Amplify And Forward ◽  
Error Performance ◽  
Superimposed Training ◽  
Training Strategy ◽  
The Individual

We introduce the superimposed training strategy into the multiple-input multiple-output (MIMO) amplify-and-forward (AF) one-way relay network (OWRN) to perform the individual channel estimation at the destination. Through the superposition of a group of additional training vectors at the relay subject to power allocation, the separated estimates of the source-relay and relay-destination channels can be obtained directly at the destination, and the accordance with the two-hop AF strategy can be guaranteed at the same time. The closed-form Bayesian Cramér-Rao lower bound (CRLB) is derived for the estimation of two sets of flat-fading MIMO channel under random channel parameters and further exploited to design the optimal training vectors. A specific suboptimal channel estimation algorithm is applied in the MIMO AF OWRN using the optimal training sequences, and the normalized mean square error performance for the estimation is provided to verify the Bayesian CRLB results.

scholarly journals Channel Estimation for Frequency Division Duplexing Multi-user Massive MIMO Systems via Tensor Compressive Sensing

2017 ◽  
Vol 67 (6) ◽  
pp. 668
Author(s):  
Qingzhu Wang ◽  
Mengying Wei ◽  
Yihai Zhu
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Three Dimensional ◽  
Data Representation ◽  
Frequency Division ◽  
Frequency Division Duplexing

<p class="p1">To make full use of space multiplexing gains for the multi-user massive multiple-input multiple-output, accurate channel state information at the transmitter (CSIT) is required. However, the large number of users and antennas make CSIT a higher-order data representation. Tensor-based compressive sensing (TCS) is a promising method that is suitable for high-dimensional data processing; it can reduce training pilot and feedback overhead during channel estimation. In this paper, we consider the channel estimation in frequency division duplexing (FDD) multi-user massive MIMO system. A novel estimation framework for three dimensional CSIT is presented, in which the modes include the number of transmitting antennas, receiving antennas, and users. The TCS technique is employed to complete the reconstruction of three dimensional CSIT. The simulation results are given to demonstrate that the proposed estimation approach outperforms existing algorithms.</p>

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