scholarly journals A Non-Stationary IMT-Advanced MIMO Channel Model for High-Mobility Wireless Communication Systems

2017 ◽  
Vol 16 (4) ◽  
pp. 2057-2068 ◽  
Author(s):  
Ammar Ghazal ◽  
Yi Yuan ◽  
Cheng-Xiang Wang ◽  
Yan Zhang ◽  
Qi Yao ◽  
...  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kai Zhang ◽  
Fangqi Zhang ◽  
Guoxin Zheng ◽  
Lei Cang

With the rapid development of high-mobility wireless communication systems, e.g., high-speed train (HST) and metro wireless communication systems, more and more attention has been paid to the wireless communication technology in tunnel-like scenarios. In this paper, we propose a three-dimensional (3D) nonstationary multiple-input multiple-output (MIMO) channel model with high-mobility wireless communication systems using leaky coaxial cable (LCX) inside a rectangular tunnel over the 1.8 GHz band. Taking into account single-bounce scattering under line-of-sight (LoS) and non-line-of-sight (NLoS) propagations condition, the analytical expressions of the channel impulse response (CIR) and temporal correlation function (T-CF) are derived. In the proposed channel model, it is assumed that a large number of scatterers are randomly distributed on the sidewall of the tunnel and the roof of the tunnel. We analyze the impact of various model parameters, including LCX spacing, time separation, movement velocity of Rx, and K-factor, on the T-CF of the MIMO channel model. For HST, the results of some further studies on the maximum speed of 360 km/h are given. By comparing the T-CF between the dipole MIMO system and the LCX-MIMO system, we can see that the performance of the LCX-MIMO system is better than that of the dipole MIMO system.


2019 ◽  
Vol 12 (1) ◽  
pp. 25-30
Author(s):  
Awwab Q. Jumaah

In wireless communication systems, the channel estimation problem has been played an essential challenge to accurately retrieve the channel state information (CSI) such that reliable communication & wide coverage can be provided. Due to the improvement and rapid growth of communication systems and in order to maintain a reliable data transmission, estimation of CSI has become necessary. This in turn results, precise receiver demodulation, accurate decoding, and equalization processes. This paper gives a survey on a fading phenomena and a comprehensive review of the recent works that have already been done and studied related to the problem of estimating channel parameters in wireless communication systems. Varieties of best channel estimation techniques that have been recently evolved are explored. Comparison between them in terms of computational cost, simplicity and appropriateness conditions is also discussed. This paper also provides a basic introduction of wireless channel model, SIMO and MIMO channel.


2015 ◽  
Vol 781 ◽  
pp. 89-92 ◽  
Author(s):  
Atikom Suppayasarn ◽  
Sarun Duangsuwan ◽  
Sathaporn Promwong

This paper studies an indoor multipath interference cancellation using the MMSE-CMA estimator for the unlicensed at 2.45 GHz of wireless communication systems. The proposed of the MMSE-CMA estimator can mitigate a superposition of the multipath interference at the receiver. As the result, the magnitudes of the channel characterization in the time domain are shown between the measured and estimated channel as a difference of number of iterations. Furthermore, we also confirm the multipath interference cancellation with the eye diagrams.


2020 ◽  
Vol 6 (2) ◽  
pp. 211-222 ◽  
Author(s):  
Jie Huang ◽  
Cheng-Xiang Wang ◽  
Lu Bai ◽  
Jian Sun ◽  
Yang Yang ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Kan Zheng ◽  
Suling Ou ◽  
Xuefeng Yin

The exponential traffic growth of wireless communication networks gives rise to both the insufficient network capacity and excessive carbon emissions. Massive multiple-input multiple-output (MIMO) can improve the spectrum efficiency (SE) together with the energy efficiency (EE) and has been regarded as a promising technique for the next generation wireless communication networks. Channel model reflects the propagation characteristics of signals in radio environments and is very essential for evaluating the performances of wireless communication systems. The purpose of this paper is to investigate the state of the art in channel models of massive MIMO. First, the antenna array configurations are presented and classified, which directly affect the channel models and system performance. Then, measurement results are given in order to reflect the main properties of massive MIMO channels. Based on these properties, the channel models of massive MIMO are studied with different antenna array configurations, which can be used for both theoretical analysis and practical evaluation.


2021 ◽  
pp. 228-235
Author(s):  
Sarun Duangsuwan ◽  

A challenge swarm unmanned aerial vehicles (swarm UAVs)-based wireless communication systems have been focused on channel modeling in various environments. In this paper, we present the characterized path loss air-to-air (A2A) channel modeling-based measurement and prediction model. The channel model was considered using A2A Two-Ray (A2AT-R) extended path loss modeling. The prediction model was considered using an artificial neural network (ANN) algorithm to train the measured dataset. To evaluate the measurement result, path loss models between the A2AT-R model and the prediction model are shown. We show that the prediction model using ANN is optimal to train the measured data for the A2A channel model. To discuss the result, the parametric prediction errors such as mean absolute error (MAE), root mean square error (RMSE), and R-square (R2), are performed.


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