System model for characterizing and reducing the mutual coupling in multiple-input multiple-output antennas

2011 ◽  
Vol 53 (3) ◽  
pp. 597-601 ◽  
Author(s):  
Yvan Duroc ◽  
Ali Imran Najam ◽  
Romain Siragusa
Keyword(s):  
Mutual Coupling ◽  
Multiple Input Multiple Output ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output

scholarly journals Mutual Coupling Reduction of DRA for MIMO Applications

2019 ◽  
Vol 8 (1) ◽  
pp. 75-81
Author(s):  
N. Al Shalaby ◽  
S. G. El-Sherbiny
Keyword(s):  
Mutual Coupling ◽  
Dielectric Material ◽  
Ground Plane ◽  
Multiple Input Multiple Output ◽  
Antenna System ◽  
Parasitic Element ◽  
Mimo Antenna ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Element Method

In this paper, A multiple input Multiple Output (MIMO) antenna using two Square Dielectric Resonators (SDRs) is introduced. The mutual coupling between the two SDRAs is reduced using two different methods; the first method is based on splitting a spiral slot in the ground plane, then filling the slot with dielectric material, "E.=2.2". The second method is based on inserting a copper parasitic element, having the same shape of the splitted Spiral, between the two SDRAs.  The effect of replacing the copper parasitic element with Carbon nanotubes (CNTs) parasitic element "SOC12 doped long-MWCNT BP" is also studied. The antenna system is designed to operate at 6 GHz. The analysis and simulations are carried out using finite element method (FEM). The defected ground plane method gives a maximum isolation of l8dB at element spacing of 30mm (0.6λo), whereas the parasitic element method gives a maximum isolation of 42.5dB at the same element spacing.

scholarly journals A Multiple-Input Multiple-Output Reservoir Computing System Subject to Optoelectronic Feedbacks and Mutual Coupling

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 231 ◽  
Author(s):  
Xiurong Bao ◽  
Qingchun Zhao ◽  
Hongxi Yin
Keyword(s):  
Mutual Coupling ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Computing System ◽  
Error Rates ◽  
Reservoir Computing ◽  
Multiple Input ◽  
Input Multiple Output ◽  
High Recognition Accuracy ◽  
Mean Square Errors

In this paper, a multiple-input multiple-output reservoir computing (RC) system is proposed, which is composed of multiple nonlinear nodes (Mach–Zehnder modulators) and multiple mutual-coupling loops of optoelectronic delay lines. Each input signal is added into every mutual-coupling loop to implement the simultaneous recognition of multiple route signals, which results in the signal processing speed improving and the number of routes increasing. As an example, the four-route input and four-route output RC is simultaneously realized by numerical simulations. The results show that this type of RC system can successfully recognize the four-route optical packet headers with 3-bit, 8-bit, 16-bit, and 32-bit, and four-route independent digital speeches. When the white noise is added to the signals such that the signal-to-noise ratio (SNR) of the optical packet headers and the digital speeches are 35 dB and 20 dB respectively, the normalized root mean square errors (NRMSEs) of the signal recognition are all close to 0.1. The word error rates (WERs) of the optical packet header recognition are 0%. The WER of the digital speech recognition is 1.6%. The eight-route input and eight-route output RC is also numerically simulated. The recognition of the eight-route 3-bit optical packet headers is implemented. The parallel processing of multiple-route signals and the high recognition accuracy are implemented by this proposed system.

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer ◽  
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

scholarly journals Root-MUSIC Based Angle Estimation for MIMO Radar with Unknown Mutual Coupling

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jianfeng Li ◽  
Xiaofei Zhang ◽  
Weiyang Chen
Keyword(s):  
Mutual Coupling ◽  
Estimation Error ◽  
Multiple Input Multiple Output ◽  
Doa Estimation ◽  
Mimo Radar ◽  
Angle Estimation ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Lower Complexity ◽  
Toeplitz Structure

Direction of arrival (DOA) estimation problem for multiple-input multiple-output (MIMO) radar with unknown mutual coupling is studied, and an algorithm for the DOA estimation based on root multiple signal classification (MUSIC) is proposed. Firstly, according to the Toeplitz structure of the mutual coupling matrix, output data of some specified sensors are selected to eliminate the influence of the mutual coupling. Then the reduced-dimension transformation is applied to make the computation burden lower as well as obtain a Vandermonde structure of the direction matrix. Finally, Root-MUSIC can be adopted for the angle estimation. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm and MUSIC-like algorithm. Furthermore, the proposed algorithm has lower complexity than them. The simulation results verify the effectiveness of the algorithm, and the theoretical estimation error of the algorithm is also derived.

scholarly journals Compact Wideband MIMO Diversity Antenna for Mobile Applications Using Multi-Layered Structure

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1307
Author(s):  
Omer Arabi ◽  
Chan Hwang See ◽  
Atta Ullah ◽  
Nazar Ali ◽  
Bo Liu ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Mutual Coupling ◽  
Multiple Input Multiple Output ◽  
Dielectric Constants ◽  
Impedance Bandwidth ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Diversity Antenna ◽  
Better Than ◽  
Envelope Correlation

A closely packed wideband multiple-input multiple-output (MIMO)/diversity antenna (of two ports) with a small size of less than 18.5 mm by 18.5 mm is proposed for mobile communication applications. The antenna can be orthogonally configured for corner installation or by placing it on a back-to-back structure for compact modules. To enhance the isolation and widen the bandwidth, the antenna is structured with multiple layers having differing dielectric constants. The feeding through a via significantly reduces the ground waves. A multi-fidelity surrogate model-assisted design exploration method is employed to obtain the optimized antenna geometric parameters efficiently. The antenna design was investigated using electromagnetic simulation and a physical realization of the optimal design was then created and subjected to a range of tests. The specific parameters investigated included reflection coefficients, mutual coupling between the input ports, radiation patterns, efficiency and parameters specific to MIMO behavior: envelope correlation coefficient and pattern diversity multiplexing coefficient. It was found that the antenna has an impedance bandwidth of approximately 4 GHz, mutual coupling between input ports of better than −18 dB and an envelope correlation coefficient of less than 0.002 across the operating band. This makes it a good candidate design for many mobile MIMO applications.

Generalized Constraint Neural Network Model System Parameter Identification

2010 ◽  
Vol 143-144 ◽  
pp. 1207-1212 ◽  
Author(s):  
Shuang Zhang ◽  
Gang Jin ◽  
Jing Xiao ◽  
Shu Li ◽  
Yu Ping Qin ◽  
...  
Keyword(s):  
Neural Network ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Black Box ◽  
System Model ◽  
Identification Method ◽  
The Neural Network ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Generalized Constraint

By analyzing and deducing generalized constraint neural network (GCNN) with model some present theories, the identification method of the m-input n-output (MINO) and multiple-input multiple–output (MIMO) systems is acquired. It is possible to improve the transparency of the black box through the practical test. This identification method is useful to enhance identification of GCNN model’s parameters, moreover, the identification ability of the neural network black box system model is further made better.

MIMO antennas with diversity and mutual coupling reduction techniques: a review

2017 ◽  
Vol 9 (8) ◽  
pp. 1763-1780 ◽  
Author(s):  
Leeladhar Malviya ◽  
Rajib Kumar Panigrahi ◽  
M. V. Kartikeyan
Keyword(s):  
Mutual Coupling ◽  
Review Paper ◽  
Multiple Input Multiple Output ◽  
Mimo Antenna ◽  
Mimo Antennas ◽  
Reduction Techniques ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Coupling Correlation ◽  
Mutual Coupling Reduction

Multiple input multiple output (MIMO) antenna is at core of the presently available wireless technologies. The design of MIMO antennas over a limited space requires various approaches of mutual coupling reduction, otherwise gain, efficiency, diversity gain, and radiation patterns will be severely affected. Various techniques have been reported in literature to control this degrading factor and to improve the performance of the MIMO antennas. In this review paper, we have carried out an extensive thorough investigation of diversity and mutual coupling (correlation) reduction techniques in compact MIMO antennas.

A Review of Massive Multiple Input Multiple Output for 5G Communication: Benefits and Challenges

2020 ◽  
Vol 1 (1) ◽  
pp. 22-26
Author(s):  
Shaik Nilofer
Keyword(s):  
Wireless Communication ◽  
Channel Capacity ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
System Model ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Primary Advantage ◽  
Time Division

Massive MIMO (mMIMO) systems become a primary advantage to overcome the problem of bandwidth restrictions. It improves the channel capacity of remote systems.The paper reviews about mMIMO systems. mMIMO consists of several number of antennas at base station (BS) which improves spectrum efficacy. The extra benefit of the mMIMO system is that the components cost is low because of utilization of less power components. The paper also discusses about the channel estimation at the BS and generally time division mode (TDD) is assumed for mMIMO systems. The paper also discusses system model, benefits for 5G wireless communication and its challenges.

scholarly journals Mutual Coupling Reduction of E-Shaped MIMO Antenna with Matrix of C-Shaped Resonators

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Raghad Ghalib Saadallah Alsultan ◽  
Gölge Ögücü Yetkin
Keyword(s):  
Mutual Coupling ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Surface Current ◽  
Antenna System ◽  
Total Efficiency ◽  
Mimo Antenna ◽  
Multiple Input ◽  
Parallel Arrangement ◽  
Input Multiple Output

E-shaped multiple-input-multiple-output (MIMO) microstrip antenna systems operating in WLAN and WiMAX bands (between 5 and 7.5 GHz) are proposed with enhanced isolation features. The systems are comprised of two antennas that are placed parallel and orthogonal to each other, respectively. According to the simulation results, the operating frequency of the MIMO antenna system is 6.3 GHz, and mutual coupling is below −18 dB in a parallel arrangement, whereas they are 6.4 GHz and −25 dB, respectively, in the orthogonal arrangement. The 2 × 3 matrix of C-shaped resonator (CSR) is proposed and placed between the antenna elements over the substrate, to reduce the mutual coupling and enhance the isolation between the antennas. More than 30 dB isolation between the array elements is achieved at the resonant frequency for both of the configurations. The essential parameters of the MIMO array such as mutual coupling, surface current distribution, envelop correlation coefficient (ECC), diversity gain (DG), and the total efficiency have been simulated to verify the reliability and the validity of the MIMO system in both parallel and orthogonal configurations. The experimental results are also provided and compared for the mutual coupling with simulated results. An adequate match between the measured and simulated results is achieved.

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