scholarly journals Construction of analytical wireless MIMO channel model based on full correlation matrix approximation

2020 ◽  
pp. 52-61
Author(s):  
Alexander Kalachikov ◽  
◽  
Nikolay Shelkunov ◽  
Keyword(s):  
Covariance Matrix ◽  
Correlation Matrix ◽  
Channel Model ◽  
Channel Modeling ◽  
Mimo Channel ◽  
Matrix Approximation ◽  
Channel Correlation ◽  
Correlation Matrices ◽  
Sample Covariance ◽  
Good Agreement

This paper addresses the experimental wireless MIMO channel modeling and validation based on channel sounding data using the approximation of the full channel correlation matrix. Measurement were carried out in indoor laboratory environment at central frequency 2.3 GHz. An analytical MIMO channel model is presented based on optimal approximation of channel covariance matrix. Approximation of a full channel covariance matrix is based on the optimal Kronecker product series expansion of the sample covariance matrix. The channel correlation matrices calculated from the measured channel coefficients were decomposed using Van Loan and Pitsanis approximation algorithm. Experimental validation of such model is presented. The accuracy of the MIMO channel modeling was evaluated by the correlation matrix distance and by calculating of CDF of channel capacity. The results show that these models have good agreement with the MIMO channel measured data. Also two popular analytical MIMO channel models – Kronecker and Weichselberger models are evaluated and compared with the presented channel model.

scholarly journals Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Gao Xi jun ◽  
Chen Zi li ◽  
Hu Yong Jiang
Keyword(s):  
Correlation Matrix ◽  
Channel Model ◽  
Three Dimensional ◽  
Matrix Decomposition ◽  
Mimo Channel ◽  
Characteristic Analysis ◽  
Channel Correlation ◽  
Channel Matrix ◽  
Time Frequency ◽  
Model Channel

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

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 Standard Propagation Channel Models for MIMO Communication Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-36
Author(s):  
Agbotiname Lucky Imoize ◽  
Augustus Ehiremen Ibhaze ◽  
Aderemi A. Atayero ◽  
K. V. N. Kavitha
Keyword(s):  
Wireless Communication ◽  
Communication Systems ◽  
Channel Model ◽  
Channel Modeling ◽  
Lessons Learned ◽  
Physical Models ◽  
Mimo Channel ◽  
Physical Parameters ◽  
Channel Models ◽  
Mimo Communication

The field of wireless communication networks has witnessed a dramatic change over the last decade due to sophisticated technologies deployed to satisfy various demands peculiar to different data-intensive wireless applications. Consequently, this has led to the aggressive use of the available propagation channels to fulfill the minimum quality of service (QoS) requirement. A major barometer used to gauge the performance of a wireless communication system is the spectral efficiency (SE) of its communication channels. A key technology used to improve SE substantially is the multiple input multiple output (MIMO) technique. This article presents a detailed survey of MIMO channel models in wireless communication systems. First, we present the general MIMO channel model and identified three major MIMO channel models, viz., the physical, analytical, and standardized models. The physical models describe the MIMO channel using physical parameters. The analytical models show the statistical features of the MIMO channel with respect to the measured data. The standardized models provide a unified framework for modern radio propagation architecture, advanced signal processing, and cutting-edge multiple access techniques. Additionally, we examined the strengths and limitations of the existing channel models and discussed model design, development, parameterization, implementation, and validation. Finally, we present the recent 3GPP-based 3D channel model, the transitioning from 2D to 3D channel modeling, discuss open issues, and highlight vital lessons learned for future research exploration in MIMO communication systems.

scholarly journals 3D Cluster-Based Ray Tracing Technique for Massive MIMO Channel Modeling

2021 ◽  
Vol 10 (1) ◽  
pp. 36-45
Author(s):  
M. M. Tamaddondar ◽  
N. Noori
Keyword(s):  
Ray Tracing ◽  
Channel Model ◽  
Model Simulation ◽  
Multiple Input Multiple Output ◽  
Channel Modeling ◽  
Mimo Channel ◽  
Mimo Channels ◽  
Physical Channel ◽  
Execution Speed ◽  
Physical Clusters

In this paper, a novel 3 dimensional (3D) approach is proposed for precise modeling of massive multiple input multiple output (M-MIMO) channels in millimeter wave (mmW) frequencies. This model is based on both deterministic and statistic computations to extract characteristics of the propagation channel. In order to increase algorithm execution speed, the physical channel is divided into two regions. The first region refers to those parts of the channel which can be mapped with simple planes such as walls, ramps and etc. The second region is usually complex which is defined by considering the channel with physical clusters. These physical clusters yield multipath components (MPCs) with similar angles of arrival (AoA) and time delay. The ray-tracing algorithm is utilized to find ray paths from transmitter (Tx) to receiver (Rx). Some characteristics of MPCs in each cluster are defined according to some appropriate statistical distribution. The non-stationary property of M-MIMO along the antenna array axis is considered in the algorithm. Due to the correspondence between the propagation environment and scatters, the accuracy of the model is highly increased. To evaluate the proposed channel model, simulation results are compared with some measurements reported in the literature.

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