scholarly journals A Semiempirical MIMO Channel Model in Obstructed Viaduct Scenarios on High-Speed Railway

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Tao Zhou ◽  
Cheng Tao ◽  
Liu Liu ◽  
Zhenhui Tan
Keyword(s):  
High Speed ◽  
Channel Model ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Time Correlation ◽  
Time Correlation Function ◽  
Mimo Channel ◽  
High Speed Railway ◽  
Single Input Single Output ◽  
Single Output

A semiempirical multiple-input multiple-output (MIMO) channel model is proposed for high-speed railway (HSR) viaduct scenarios. The proposed MIMO model is based on the combination of realistic single-input single-output (SISO) channel measurement results and a theoretical geometry-based stochastic model (GBSM). Temporal fading characteristics involvingK-factor and Doppler power spectral density (PSD) are derived from the wideband measurement under an obstructed viaduct on Zhengzhou-Xi’an HSR in China. The GBSM composed of a one-ring model and an elliptical model is employed to describe the entire propagation environment. Environment-related parameters in the GBSM are determined by the measured temporal fading properties. And a close agreement is achieved between the model results and measured data. Finally, a deterministic simulation model is established to perform the analysis of the space-time correlation function, the space-Doppler PSD, and the channel capacity for the measured scenario. This model is more realistic and particularly beneficial for the performance evaluation of MIMO systems in HSR environments.

scholarly journals Block Method for SolvingState-Space Equations of Linear Continuous-Time Control Systems

2007 ◽  
Vol 4 (2) ◽  
pp. 318-329
Author(s):  
Baghdad Science Journal
Keyword(s):  
State Space ◽  
Continuous Time ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Method Comparison ◽  
The State ◽  
Block Method ◽  
Single Input Single Output ◽  
Single Output ◽  
Time Control

This paper presents a newly developed method with new algorithms to find the numerical solution of nth-order state-space equations (SSE) of linear continuous-time control system by using block method. The algorithms have been written in Matlab language. The state-space equation is the modern representation to the analysis of continuous-time system. It was treated numerically to the single-input-single-output (SISO) systems as well as multiple-input-multiple-output (MIMO) systems by using fourth-order-six-steps block method. We show that it is possible to find the output values of the state-space method using block method. Comparison between the numerical and exact results has been given for some numerical examples for solving different types of state-space equations using block method for conciliated the accuracy of the results of this method.

scholarly journals A Triply Selective MIMO Channel Simulator Using GPUs

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
R. Carrasco-Alvarez ◽  
R. Carreón-Villal ◽  
J. Vázquez Castillo ◽  
J. Ortegón Aguilar ◽  
O. Longoria-Gandara ◽  
...  
Keyword(s):  
Graphics Processing Units ◽  
Multiple Input Multiple Output ◽  
Direct Consequence ◽  
Mimo Channel ◽  
Computational Time ◽  
Space Correlation ◽  
Single Input Single Output ◽  
Single Output ◽  
Input Multiple Output ◽  
Channel Simulator

A methodology for implementing a triply selective multiple-input multiple-output (MIMO) simulator based on graphics processing units (GPUs) is presented. The resulting simulator is based on the implementation of multiple double-selective single-input single-output (SISO) channel generators, where the multiple inputs and the multiple received signals have been transformed in order to supply the corresponding space correlation of the channel under consideration. A direct consequence of this approach is the flexibility provided, which allows different propagation statistics to each SISO channel to be specified and thus more complex environments to be replicated. It is shown that under some specific constraints, the statistics of the triply selective MIMO simulator are the same as those reported in the state of art. Simulation results show the computational time improvement achieved, up to 650-fold for an 8 × 8 MIMO channel simulator when compared with sequential implementations. In addition to the computational improvement, the proposed simulator offers flexibility for testing a variety of scenarios in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) systems.

scholarly journals Deep Learning-based Cooperative Automatic Modulation Classification Method for MIMO Systems

2020 ◽  
Author(s):  
Yu Wang ◽  
Juan Wang ◽  
Jie Yang ◽  
Wei Zhang ◽  
Guan Gui
Keyword(s):  
Deep Learning ◽  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Decision Rules ◽  
Modulation Classification ◽  
Single Input Single Output ◽  
Automatic Modulation Classification ◽  
Single Output ◽  
Input Multiple Output

Automatic modulation classification (AMC) is one of the most essential algorithms to identify the modulation types for the non-cooperative communication systems. Recently, it has been demonstrated that deep learning (DL)-based AMC method effectively works in the single-input single-output (SISO) systems, but DL-based AMC method is scarcely explored in the multiple-input multiple-output (MIMO) systems. In this correspondence, we propose a convolutional neural network (CNN)-based cooperative AMC (Co-AMC) method for the MIMO systems, where the receiver equipped with multiple antennas cooperatively recognizes the modulation types. Specifically, each received antenna gives their recognition sub-results via the CNN, respectively. Then, the decision maker identifies the modulation types with the recognition sub-results and cooperative decision rules, such as direct voting (DV), weighty voting (WV), direct averaging (DA) and weighty averaging (WA). The simulation results demonstrate that the Co-AMC method, based on the CNN and WA, has the highest correct classification probability in the four cooperative decision rules. In addition, the CNN-based Co-AMC method also performs better than the high order cumulants (HOC)-based traditional AMC methods, which shows the effective feature extraction and powerful classification capabilities of the CNN.

Three-Dimension Kronecker Channel Modeling and Correlation Analysis

2015 ◽  
Vol 7 (4) ◽  
pp. 43-56 ◽  
Author(s):  
Jianzheng Li ◽  
Fei Li ◽  
Wei Ji ◽  
Yulong Zou ◽  
Chunguo Li
Keyword(s):  
Antenna Arrays ◽  
Channel Model ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Channel Modeling ◽  
Mimo Channel ◽  
Antenna Element ◽  
Three Dimension ◽  
3D Mimo ◽  
The Impact

In this paper a three-dimension (3D) multiple-input multiple-output (MIMO) channel model is derived by considering the elevation dimension and the azimuth dimension together. To get a more accurate performance analysis for 3D MIMO channel, both Tx and Rx correlation matrices are derived, respectively, in closed form, which consist of 3D Kronecker channel model. This novel 3D Kronecker channel model is developed for arbitrary antenna arrays with non-isotropic antenna patterns and also for any propagation environment of 3D MIMO systems. In order to quantify the performance of 3D MIMO systems, the capacity in multi-user cases is analyzed. Simulation results validate the proposed 3D Kronecker channel model and study the impact of elevation and azimuth angular spread and that of Rx antenna element spacing on the correlation. The proposed capacity analysis in multi-user cases for 3D MIMO systems is also verified by simulation.

scholarly journals Orbit Angular Momentum MIMO with Mode Selection for UAV-Assisted A2G Networks

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2289
Author(s):  
Tao Hu ◽  
Yang Wang ◽  
Bo Ma ◽  
Jie Zhang
Keyword(s):  
Angular Momentum ◽  
High Speed ◽  
Degrees Of Freedom ◽  
Channel Model ◽  
Mimo Systems ◽  
Mode Selection ◽  
Multiple Input Multiple Output ◽  
Base Stations ◽  
Spectrum Efficiency ◽  
Ms Scheme

As an emerging solution for line-of-sight (LOS) wireless communications, in air-to-ground (A2G) channels, the unmanned aerial vehicle (UAV), and allowing the dynamic and flexible network deployments enables the supplement or/and replacement of the terrestrial base stations (BSs). However, in conventional multiple-input-multiple-output (MIMO) systems, high-speed communications are significantly limited by channel crosstalks and spectrum scarcities. An orbit angular momentum (OAM) wireless network, allowing co-existence of multiple physical channels within the same frequency band, offers new degrees of freedom to address this dilemma. In this paper, we investigate the UAV-based A2G radio vortex wireless networks and study its channel model. Then we propose a branch and bound search-based mode selection (BBS-MS) scheme, which uses the spatial distribution characteristics of vortex beams to optimize the spectrum efficiency (SE). Theoretical derivations and numerical results demonstrate that our developed BBS-MS scheme can obtain the optimal performance, which outperforms conventional OAM-based MIMO systems. Also, it possesses a lower complexity compared with exhaustive searches.

scholarly journals Optimized Scheduling Technique of Null Subcarriers for Peak Power Control in 3GPP LTE Downlink

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Soobum Cho ◽  
Sang Kyu Park
Keyword(s):  
Power Efficiency ◽  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Average Power ◽  
Papr Reduction ◽  
Single Input Single Output ◽  
Single Output ◽  
Multiple Input ◽  
Input Multiple Output

Orthogonal frequency division multiple access (OFDMA) is a key multiple access technique for the long term evolution (LTE) downlink. However, high peak-to-average power ratio (PAPR) can cause the degradation of power efficiency. The well-known PAPR reduction technique, dummy sequence insertion (DSI), can be a realistic solution because of its structural simplicity. However, the large usage of subcarriers for the dummy sequences may decrease the transmitted data rate in the DSI scheme. In this paper, a novel DSI scheme is applied to the LTE system. Firstly, we obtain the null subcarriers in single-input single-output (SISO) and multiple-input multiple-output (MIMO) systems, respectively; then, optimized dummy sequences are inserted into the obtained null subcarrier. Simulation results show that Walsh-Hadamard transform (WHT) sequence is the best for the dummy sequence and the ratio of 16 to 20 for the WHT and randomly generated sequences has the maximum PAPR reduction performance. The number of near optimal iteration is derived to prevent exhausted iterations. It is also shown that there is no bit error rate (BER) degradation with the proposed technique in LTE downlink system.

scholarly journals Linear detectors and precoding methods for massive MIMO

2021 ◽  
Vol 42 (2) ◽  
pp. 209
Author(s):  
Jean Marcel Faria Tonin ◽  
Taufik Abrao
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mean Squared Error ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Wireless Channel ◽  
Single Input Single Output ◽  
Single Output ◽  
Minimum Mean Squared Error ◽  
Input Multiple Output

Detection in multiple-input-multiple-output (MIMO) wireless communication systems is a crucial procedure in receivers since the multiple access transmission schemes generate interference due to the simultaneous transmission along with the several antennas, unlike single-input-single-output (SISO) transmission schemes. Precoding is a technique in MIMO systems used to mitigate the effects of the channel over the received signal. Hence, it is possible to adjust continuously the transmitted information to reverse the effect of the wireless channel at the receiver side. In this work, linear sub-optimal detectors and precoders for massive MIMO (M-MIMO) systems are implemented, analyzed, and compared in terms of performance-complexity trade-off. It is also being considered numerical results in both channel scenarios: a) receiver and transmitter have perfect channel state information (CSI); b) complex channel coefficients are estimated with different levels of inaccuracy. Monte-Carlo simulations (MCS) reveal that linear zero-forcing (ZF) and minimum mean squared error (MMSE) massive MIMO detectors result in a certain robustness against multi-user interference when operating under low and medium system loading, L = K/M, thanks to the favourable propagation phenomenon arising in massive MIMO systems.

scholarly journals Deep Learning-based Cooperative Automatic Modulation Classification Method for MIMO Systems

2020 ◽  
Author(s):  
Yu Wang ◽  
Juan Wang ◽  
Jie Yang ◽  
Wei Zhang ◽  
Guan Gui
Keyword(s):  
Deep Learning ◽  
Communication Systems ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Decision Rules ◽  
Modulation Classification ◽  
Single Input Single Output ◽  
Automatic Modulation Classification ◽  
Single Output ◽  
Input Multiple Output

Automatic modulation classification (AMC) is one of the most essential algorithms to identify the modulation types for the non-cooperative communication systems. Recently, it has been demonstrated that deep learning (DL)-based AMC method effectively works in the single-input single-output (SISO) systems, but DL-based AMC method is scarcely explored in the multiple-input multiple-output (MIMO) systems. In this correspondence, we propose a convolutional neural network (CNN)-based cooperative AMC (Co-AMC) method for the MIMO systems, where the receiver equipped with multiple antennas cooperatively recognizes the modulation types. Specifically, each received antenna gives their recognition sub-results via the CNN, respectively. Then, the decision maker identifies the modulation types with the recognition sub-results and cooperative decision rules, such as direct voting (DV), weighty voting (WV), direct averaging (DA) and weighty averaging (WA). The simulation results demonstrate that the Co-AMC method, based on the CNN and WA, has the highest correct classification probability in the four cooperative decision rules. In addition, the CNN-based Co-AMC method also performs better than the high order cumulants (HOC)-based traditional AMC methods, which shows the effective feature extraction and powerful classification capabilities of the CNN.

scholarly journals Geometry-Based Stochastic Modeling for MIMO Channel in High-Speed Mobile Scenario

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Binghao Chen ◽  
Zhangdui Zhong
Keyword(s):  
High Speed ◽  
Measurement Data ◽  
Analytical Form ◽  
Time Correlation ◽  
Mimo Channel ◽  
Time Correlation Functions ◽  
Channel Models ◽  
High Speed Railway ◽  
Space Correlation ◽  
Channel Parameters

The geometry-based stochastic channel models are proposed in this paper for the terrain cutting, suburb, and urban scenarios in high-speed railway. First, the special scenarios in high-speed railway are described. And the channel models based on the geometry scenarios are introduced. Some channel parameters are based on measurement data. Then, the space-time correlation functions in analytical form are obtained in suburb and urban scenarios. Finally, the space correlation characteristics in three scenarios are compared.

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