Zhouxiang Fei

Matching Network Elimination in Broadband Rectennas for High-Efficiency Wireless Power Transfer and Energy Harvesting

Impedance matching networks for nonlinear devices such as amplifiers and rectifiers are normally very challenging to design, particularly for broadband and multiband devices. A novel design concept for a broadband high-efficiency rectenna without using matching networks is presented in this paper for the first time. An off-center-fed dipole antenna with relatively high input impedance over a wide frequency band is proposed. The antenna impedance can be tuned to the desired value and directly provides a complex conjugate match to the impedance of a rectifier. The received RF power by the antenna can be delivered to the rectifier efficiently without using impedance matching networks; thus, the proposed rectenna is of a simple structure, low cost, and compact size. In addition, the rectenna can work well under different operating conditions and using different types of rectifying diodes. A rectenna has been designed and made based on this concept. The measured results show that the rectenna is of high power conversion efficiency (more than 60%) in two wide bands, which are 0.9–1.1 and 1.8–2.5 GHz, for mobile, Wi-Fi, and ISM bands. Moreover, by using different diodes, the rectenna can maintain its wide bandwidth and high efficiency over a wide range of input power levels (from 0 to 23 dBm) and load values (from 200 to 2000 Ω). It is, therefore, suitable for high-efficiency wireless power transfer or energy harvesting applications. The proposed rectenna is general and simple in structure without the need for a matching network hence is of great significance for many applications.

Uncertainty Quantification of Crosstalk Using Stochastic Reduced Order Models

This paper introduces a novel statistical method, referred to as the stochastic reduced order model (SROM) method, to predict the variability of cable crosstalk subject to a range of parametric uncertainties. The SROM method is a new member of the family of stochastic approaches to quantify propagated uncertainty in the presence of multiple uncertainty sources. It is nonintrusive, accurate, efficient, and stable, thus could be a promising alternative to some well-established methods, such as the Stochastic Galerkin and stochastic collocation (SC) methods. In this paper, the SROM method is successfully applied to obtain the statistics of cable crosstalk subject to single and multiple uncertainty sources. The statistics of uncertain cable parameters is first accurately approximated by SROM, i.e., pairs of very few samples with known probabilities, such that the uncertain input space is well represented. Then, a deterministic solver is used to produce the samples of cable crosstalk with the corresponding probabilities, and finally the uncertainty propagated to the crosstalk is quantified with good accuracy. Compared to the conventional Monte-Carlo simulation, the statistics of crosstalk obtained by the SROM method converge much faster by orders of magnitude. Also, the computational cost of the SROM method is shown to be small and can be tuned flexibly depending on the accuracy requirement. The SC method based on tensor product sampling strategy is also implemented to validate the efficacy of the SROM method.

Crosstalk variations caused by uncertainties in three-conductor transmission lines

The crosstalk is a very important aspect of cable EMC (electromagnetic compatibility) performance evaluation. As uncertainties are introduced during cable fabrication and installation process, deterministic prediction methods are not suitable for a good estimation of the cable performance. This paper is focused on predicting the crosstalk of cable bundles by considering the uncertainties introduced in three-conductor transmission lines. How the uncertainties of different parameters in three-conductor transmission lines might affect the crosstalk and its variations are investigated and a better understanding on how to avoid high crosstalk in applications is obtained and presented.

A Fast Method to Measure the Volume of a Large Cavity

How to quickly and accurately measure the volume of a large cavity is challenging. This paper presents an efficient method to measure the volume of a large conducting cavity. The proposed method is based on statistical wave theory. By measuring the Q factor in the time and frequency domains, the volume of the cavity can be extracted. In the time domain, the Q factor can be extracted directly from the time domain response, while in the frequency domain, the Q factor depends on the volume of the cavity and the transferred power; the transferred power can be measured directly. By correcting the frequency domain Q with the radiation efficiency of antennas, the Q factors obtained from both the time and frequency domains are equal in a well-stirred chamber; this provides an opportunity to measure the volume of the cavity. Measurements are conducted to verify the proposed method. Although the measurement is conducted using electromagnetic waves, acoustic waves can also be used; in this case, the approach can be applied to any cavity, not limited to a conducting cavity. The advantages and the limitations of the proposed method are also discussed.

Numerical Analysis of a Transmission Line Illuminated by a Random Plane-Wave Field Using Stochastic Reduced Order Models

A novel nonintrusive statistical approach, known as the stochastic reduced order model (SROM) method, is applied to efficiently estimate the statistical information of the terminal response (i.e., the induced current) in transmission lines excited by a random incident plane-wave field. The idea of the SROM method is conceptually simple, i.e., to represent the uncertain input space dimensioned by random variables using the SROM-based input model. This input model consists of a very small number of selected samples with assigned probabilities. Thus, only these input samples in the model need to be evaluated using the deterministic solver. The SROM-based output model can be constructed to approximate the propagated uncertainty to the real output response with elementary calculation. The efficiency and accuracy of the SROM method to obtain the statistics of the induced current are analyzed using two examples, where the complexity of the uncertain input space gradually increases. The performance of the SROM method is compared with that of the traditional Monte Carlo (MC) method. The stochastic collocation (SC) method based on sparse grid sampling strategy computed via the Smolyak algorithm is also implemented to fairly evaluate the SROM performance. The result shows that the SROM method is much more efficient than the MC method to obtain accurate statistics of the induced current, and even shows a faster convergence rate compared with that of the SC method in the examples considered. Therefore, the SROM method is a suitable approach to investigate the variability of radiated susceptibility in electromagnetic compatibility problems with a random incident wave.

Sensitivity analysis of cable crosstalk to uncertain parameters using stochastic reduced order models

This paper presents the sensitivity analysis of cable crosstalk against different uncertain variables using the stochastic reduced order model (SROM) method. A ranking of these uncertain variables is produced based on their impact levels on the crosstalk. This study shows that the complexity of the statistical problem can be reduced by ignoring the weak variables without affecting the accuracy. The statistical result is obtained with the SROM method, and compared with that of the conventional Monte Carlo (MC) method. It is found that the SROM method can reduce the computational cost required by the converged MC by at least two orders of magnitude. Also the SROM method is non-intrusive and straightforward to implement. Therefore, it could be an ideal solution to obtain the statistical solution in randomness-embedded electromagnetic compatibility (EMC) problems.