Scalable Package-level RFI Filter for Digital Clock Noise Mitigation in 5-GHz and future 6-GHz WiFi Applications

Lee, Jaejin; Hsu, Hui‐Chin; Ho, Ying-Ern

doi:10.1109/isemc.2019.8825285

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…This range contains the newly allocated 6-GHz WiFi band, operating from 5.925 to 7.125 GHz. This WiFi band was expanded by the Federal Communications Commission to meet the growing bandwidth demands of WiFi channels [23]. The far-field radiation patterns of the antenna elements are simulated every 100 MHz (with total of 18 frequency points) in each evaluation scenario.…”

Section: A S Parametersmentioning

confidence: 99%

Numerical Analysis of Users’ Body Effects on a Fourteen-Element Dual-Band 5G MIMO Mobile Terminal Antenna

Elshirkasi

Al‐Hadi

Khan³

et al. 2022

IEEE Access

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This paper studies the performance of a 14-element dual-band 5G MIMO antenna with body effect and an antenna selection. The antenna operates in the lower frequency band from 3.10 to 3.85 GHz for 5G bands of LTE 42 and 43, whereas the upper band is from 5.60 to 7.20 GHz for the newly assigned 6 GHz WiFi band. The antenna performance was evaluated in free space and under the effect of human body in three scenarios, namely one-hand, two-hands, and call mode. All resulting envelope correlation coefficients are less than 0.3. On the other hand, the free space efficiency of the antenna elements is between 41 % to 77 % in the lower band and 61 % to 95 % in the upper band. Meanwhile, the efficiency of the elements varies depending on the interaction between each element with the hands and the head, with the least obstructed element efficiency degrading to 8 % relative to free space levels. Due to the body effect, multiplexing efficiency loss varies from 2.68 dB to 5.93 dB and the capacity loss is from 14 % to 38 %. Finally, a selection algorithm is used to assess the performance of the overall antenna when 12, 10 and 8 antenna elements are selected for operation. In free space and with number of elements 12, 10 and 8, the system achieves 91.7 %, 80 % and 67 % from the capacity of the 14-element MIMO antenna, respectively. However, in the vicinity of the body, these values increase to 96.3 %, 85.0 % and 72 % from the capacity of the 14-element MIMO antenna, respectively. This signifies that the less-contributing elements as a result of body blockage can be deselected in order to preserve system resources that these elements consume while contributing less significantly to the performance.INDEX TERMS Multiple-input-multiple-output antennas, antenna selection, channel capacity, user effects

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Section: A S Parametersmentioning

confidence: 99%

Numerical Analysis of Users’ Body Effects on a Fourteen-Element Dual-Band 5G MIMO Mobile Terminal Antenna

Elshirkasi

Al‐Hadi

Khan³

et al. 2022

IEEE Access

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“…Figure 3 shows the process and method of EMG sensing for measurements. Muscles activated through electrodes are amplified at a constant amplification rate via radio frequency interference (RFI) filter circuits [12] for high-frequency noise and interference removal, and are output through frequency filters. This output is digitized via the analogue to digital converting (ADC) circuit for conversion to data for analysis, and the resulting data is defined as "raw EMG".…”

Section: Measurement and Extraction Of Emgmentioning

confidence: 99%

Motion Recognition and an Accuracy Comparison of Left and Right Arms by EEG Signal Analysis

et al. 2019

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An electromyogram (EMG) is a signal for muscle output that indicates the degree of muscle contraction and relaxation. For these muscle signals to be output, certain signals must be received from the brain. To analyze these relations, electroencephalograms (EEGs) of the brain are measured to extract brain waves that are active at that time, although it is difficult to identify or distinguish expression patterns of the brain signal through EMG output. However, the brain signal operates via a partially reached signal and transmits the results of the operation. In this study, we analyze signals transmitted in this process and confirm whether human motion can be predicted from brain signals. It is not easy to guess the exact protocol of the brain using a general method, because a biosignal is a signal that differs from person to person. However, by analyzing the signals displayed by a particular user through actions, it is possible to determine the presence or absence of a signal to distinguish muscle movements. In the course of signal transduction, the energy of the left and right brain waves changes in the form of energy or signals that cause an arm’s movement. Responding to this, we analyze the signal transmission process of brain signals and EMGs to analyze loss and generated output. We extract EEG data from brain waves and determine EMG signals from the energy characteristics; we then collect and merge the results of spectra analysis through the Common Spatial Pattern (CSP) filter and explore the basis for predicting wills during muscle signals and stimulation transmission. The active information of the data within the working time of left and right brain waves depends on the changes of the left and right brain waves. It is proposed that the appearance of similar signals at these specific timescales can help identify the operations of the arms and outputs by the left and right biceps.

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Use of real time localization systems (RTLS) in the automotive production and the prospects of 5G – A literature review

Küpper

Rösch

Winkler

2022

Production & Manufacturing Research

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Scalable Package-level RFI Filter for Digital Clock Noise Mitigation in 5-GHz and future 6-GHz WiFi Applications

Cited by 4 publications

References 7 publications

Numerical Analysis of Users’ Body Effects on a Fourteen-Element Dual-Band 5G MIMO Mobile Terminal Antenna

Numerical Analysis of Users’ Body Effects on a Fourteen-Element Dual-Band 5G MIMO Mobile Terminal Antenna

Motion Recognition and an Accuracy Comparison of Left and Right Arms by EEG Signal Analysis

Use of real time localization systems (RTLS) in the automotive production and the prospects of 5G – A literature review

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