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Your search keyword '"Member, Graduate Student"' showing total 2 results
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2 results on '"Member, Graduate Student"'

1. Multitone PSK Modulation Design for Simultaneous Wireless Information and Power Transfer

Author

Dhull, Prerna, Member, Graduate Student, Schreurs, Dominique, Paolini, Giacomo, Costanzo, Alessandra, Abolhasan, Mehran, and Shariati, Negin

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Far-field wireless power transfer, based on radio frequency (RF) waves, came into the picture to fulfill the power need of large Internet of Things (IoT) networks, the backbone of the 5G and beyond era. However, RF communication signals carry both information as well as energy. Therefore, recently, simultaneous wireless information and power transfer (SWIPT) has attracted much attention in order to wirelessly charge these IoT devices. In this paper, we propose a novel N -tone multitone phase shift keying (PSK) modulation scheme, taking advantage of the non-linearity of integrated receiver rectifier architecture. The main advantage of the proposed modulation scheme is the reduction in ripple voltage, introduced by the symbol transmission through phases. Achievable power conversion efficiency (PCE) and bit error rate (BER) at the output are considered to measure the efficacy of the proposed modulation scheme. Simulation results are verified by the measurements over the designed rectifier circuitry. The effect of symbol phase range, modulation order, and the number of tones are analyzed. In the future, this transmission scheme can be utilized to satisfy the data and power requirements of low-power Internet of Things sensor networks.

Published
2024

2. Improved Estimation for Well-Logging Problems Based on Fusion of Four Types of Kalman Filters.

Author

Soltani, Sina, Kordestani, Mojtaba, Aghaee, Paknoosh Karim, Member, Graduate Student, Saif, Mehrdad, and Member, Senior

Subjects
GEOPHYSICAL well logging, DATA fusion (Statistics), KALMAN filtering, ESTIMATION theory, GAMMA rays, FUZZY systems, MATHEMATICAL models
Abstract

The concept of information fusion has gained a widespread interest in many fields due to its complementary properties. It makes systems more robust against uncertainty. This paper presents a new approach for the well-logging estimation problem by using a fusion methodology. The natural gammaray tool (NGT) is considered as an important instrument in the well logging. The NGT detects changes in natural radioactivity emerging from the variations in concentrations of micronutrients as uranium (U), thorium (Th), and potassium (K). The main goal of this paper is to have precise estimation of the concentrations of U, Th, and K. Four types of Kalman filters are designed to estimate the elements using the NGT sensor. Then, a fusion of the Kalman filters is utilized into an integrated framework by an ordered weighted averaging (OWA) operator to enhance the quality of the estimations. A real covariance of the output error based on the innovation matrix is utilized to design weighting factors for the OWA operator. The simulation studies indicate not only a reliable performance of the proposed method compared with the individual Kalman filters but also a better response in contrast with previous fusion methodologies. [ABSTRACT FROM AUTHOR]

Published
2018
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