A broadband folded Gilbert cell CMOS mixer

Krcmar, M.; Boeck, Georg

doi:10.1007/s10470-009-9358-y

Cited by 7 publications

(1 citation statement)

References 12 publications

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“…It can reduce the use of high-frequency components because the high-frequency component is costly due to fabrication difficulties [15]. Moreover, converting the frequency to IF reduces the supply voltage of the receiver [16].…”

Section: Frequency Mixermentioning

confidence: 99%

Development of Humidity Monitoring System in Greenhouse With Electromagnetic X Band and Artificial Neural Networks

Leekul¹,

Wongsiritorn²,

Chaisaeng³

2021

PIER M

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This paper presents a humidity monitoring system with X band electromagnetic transmission. The verification is performed by comparing the gain and phase difference of intermediate frequency between 10.2 GHz and 10.4 GHz. Measurement data are analyzed to classify relative humidity levels and make decisions with ANNs. The system is simulated with electromagnetic field simulation software to analyze the ability of humidity monitoring. The structure from the simulation is developed to be a prototype system, including transmitter and receiver modules. Each module consists of an antenna, a frequency synthesizer, and a frequency mixer. The different operation frequencies of the two modules are −200 MHz and +200 MHz. The obtained intermediate frequency by mixing signals from each module is introduced into the circuit to find the gain and phase difference to compare with a relative humidity level. Humidity monitoring experiment is set in a closed plastic box to control the environment. The relative humidity level is from 55% to 95%. The decrease in gain is associated with increased relative humidity. Results found that the phase difference decreases clearly at the relative humidity from 75% to 95%. Both gain and phase difference data are used to train ANNs to optimize ANNs structure. Data are divided into 50% for training and 50% for testing. The proposed ANNs structure with a learning rate of 0.05 provides 98.8% accuracy. The optimized ANNs structure is composed of two input nodes, eight hidden nodes, and four output nodes. Four output nodes represent the relative humidity in 11 levels. The simulated and experimental results show that the system is able to monitor humidity effectively for applying in the greenhouse.

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Section: Frequency Mixermentioning

confidence: 99%

Development of Humidity Monitoring System in Greenhouse With Electromagnetic X Band and Artificial Neural Networks

Leekul¹,

Wongsiritorn²,

Chaisaeng³

2021

PIER M

View full text Add to dashboard Cite

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Recent advancement in the design of mixers for software‐defined radios

Mehta

Donelli

2021

Int J RF Mic Comp-Aid Eng

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The implementation of software-defined radio necessitates a versatile radio frequency (RF) front-end that can support multiple standards in different frequency bands. This article presents the state-of-the-art multiband and wideband mixers in the context of different receiver architectures suitable for softwaredefined radio (SDR). Wideband and multiband mixer designs reported in the literature are categorized on the basis of their circuit architecture. This study tabulates the results of mixer designs with an emphasis on noise figure (NF), conversion gain (CG), linearity, and image rejection ratio. The best parameters reported in the comparison are 68-84 dB of CG, 3.2 dB of NF, 2.5 mW of power consumption, 12.5 dBm of third-order input intercept point, and 0.015 mm 2 of area at different frequencies. The study also discusses the design challenges and techniques to overcome those issues. The article concludes with the summary and prospective developments for SDR architectures.

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A LNA-merged RF front-end with digitally assisted technique for gain flatness and input-match compensation

Liu

Chen

et al. 2019

Analog Integr Circ Sig Process

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A broadband folded Gilbert cell CMOS mixer

Cited by 7 publications

References 12 publications

Development of Humidity Monitoring System in Greenhouse With Electromagnetic X Band and Artificial Neural Networks

Development of Humidity Monitoring System in Greenhouse With Electromagnetic X Band and Artificial Neural Networks

Recent advancement in the design of mixers for software‐defined radios

A LNA-merged RF front-end with digitally assisted technique for gain flatness and input-match compensation

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