Dual‐mode and triple‐band 10‐antenna handset array and its multiple‐input multiple‐output performance evaluation in 5G

2018 ◽  
pp. e21538 ◽  
Author(s):  
Yixin Li ◽  
Guangli Yang
Keyword(s):  
Performance Evaluation ◽  
Multiple Input Multiple Output ◽  
Dual Mode ◽  
Output Performance ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Triple Band

On multiple-input–multiple-output performance for Terrestrial Trunked Radio systems

2014 ◽  
Vol 8 (14) ◽  
pp. 2484-2488
Author(s):  
Peter D. Holm ◽  
Daniel Persson ◽  
Kia Wiklundh ◽  
Peter Stenumgaard
Keyword(s):  
Multiple Input Multiple Output ◽  
Output Performance ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Radio Systems

A new design of triple-band WLAN/WiMAX monopole antenna for multiple-input/multiple-output applications

2014 ◽  
Vol 56 (11) ◽  
pp. 2667-2671 ◽  
Author(s):  
Nasser Ojaroudi ◽  
Nuraddin Ghadimi ◽  
Mehdi Mehranpour ◽  
Yasser Ojaroudi ◽  
Sajjad Ojaroudi
Keyword(s):  
Multiple Input Multiple Output ◽  
Monopole Antenna ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Triple Band

scholarly journals Research on Personnel Performance Evaluation Model Based on Neural Wireless Network Data Mining Algorithm

2020 ◽  
Author(s):  
Wei Liang ◽  
Tingyi Li
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Evaluation Model ◽  
Multiple Input Multiple Output ◽  
Network Data ◽  
Data Mining Algorithm ◽  
Spatial Network ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Frequency Feature

Abstract In order to effectively evaluate personnel performance, a distributed data mining algorithm for spatial networks based on BP neural wireless network is proposed. In the cloud computing environment, an excavator is used to construct multiple input multiple output spatial network data, analyze the data structure, and perform redundant data compression of massive data through time-frequency feature extraction. Combined with adaptive matching filtering method, the characteristics of the data are matched. The spatial frequency feature extraction method is used to locate the features of the multiple-input multiple-output spatial network data, and the fourth-order cumulant slice is used for reorganization. Data in time series. In order to improve the accuracy of data mining, the BP neural network is used to classify and identify the extracted data features to achieve the optimization of data mining. This algorithm improves the accuracy of personnel performance evaluation, and simultaneously establishes a hierarchical analysis and quantitative evaluation model for the performance of government managers, and adjusts the results of hierarchical statistical analysis on government administrators as needed. The performance evaluation and optimization of government administrators were introduced. The empirical analysis results show that the method has higher accuracy for government managers' performance evaluation, higher efficiency of big data processing and better integration.

Dual circular slot ring triple-band MIMO antenna for 5G applications

Frequenz ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Anand Kumar ◽  
Santosh Kumar Mahto ◽  
Rashmi Sinha ◽  
Arvind Choubey
Keyword(s):  
Mutual Coupling ◽  
Ground Plane ◽  
Multiple Input Multiple Output ◽  
Mobile Terminal ◽  
High Gain ◽  
Mimo Antenna ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Smart Wearable ◽  
Triple Band

AbstractA Triple-band Multiple-Input-Multiple-Output (MIMO) antenna for 5G mobile terminal applications is proposed in this paper. The design comprises four-port/two resonators, each having two concentric circular slot ring radiators etched on a ground plane of size 50 mm ${\times}$ 50 mm. The antenna is fed by perpendicularly arranged 50 Ω microstrip line feeds on the top layer. Decoupling techniques were used to suppress mutual coupling between the two resonators. The perpendicular arrangement of the feed lines and port reduces mutual coupling between the two ports and increases isolation. The antenna operates in multiple bands: 3.35–3.69 GHz, 24–28 GHz, and 37–40 GHz frequency range with central frequencies at 3.5 GHz, 26 GHz, and 38 GHz, respectively allocated for 5G. The antenna provides a gain of 2.7–7.8 dB and a radiation efficiency of 0.49–0.85 in the operating bands. Diversity performance is studied in terms of the Envelop Correlation Coefficient (ECC), Diversity Gain (DG), and Total Active Reflection Coefficient (TARC) were found to be less than 0.01, greater than 9.99 dB, and less than −10 dB respectively. The proposed antenna offers good S-parameters, voltage standing wave ratio (VSWR), TARC, radiation pattern, high gain, and low ECC. The antenna was fabricated and tested. The measured results and simulated results are in good agreement. It possesses sufficient potential for 5G mobile terminal and smart wearable applications.

scholarly journals Research on human performance evaluation model based on neural network and data mining algorithm

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Wei Liang ◽  
Tingyi Li
Keyword(s):  
Data Mining ◽  
Performance Evaluation ◽  
Evaluation Model ◽  
Multiple Input Multiple Output ◽  
Network Data ◽  
Data Mining Algorithm ◽  
Spatial Network ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Frequency Feature

Abstract In order to effectively evaluate personnel performance, a distributed data mining algorithm for spatial networks based on BP neural wireless network is proposed. In the cloud computing environment, an excavator is used to construct multiple input multiple output spatial network data, analyze the data structure, and perform redundant data compression of massive data through time-frequency feature extraction. Combined with the adaptive matching filtering method, the characteristics of the data are matched. The spatial frequency feature extraction method is used to locate the features of the multiple-input multiple-output spatial network data. In order to improve the accuracy of data mining, the BP neural network is used to classify and identify the extracted data features to achieve the optimization of data mining. A wireless sensor network is a wireless network composed of a large number of stationary or moving sensors in a self-organizing and multi-hop manner. It cooperatively senses, collects, processes, and transmits the information of the perceived objects in the geographical area covered by the network and finally puts these The information is sent to the owner of the network. This algorithm improves the accuracy of personnel performance evaluation, simultaneously establishes a hierarchical analysis and quantitative evaluation model for the performance of government managers, and adjusts the results of hierarchical statistical analysis on government administrators as needed. The performance evaluation and optimization of government administrators were introduced. The empirical analysis results show that the method has higher accuracy for government managers’ performance evaluation, higher efficiency of big data processing, and better integration.

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