2022
Maria S Papadopoulou; Achilles D Boursianis; Argyrios Chatzopoulos; Panagiotis Sarigiannidis; Spyridon Nikolaidis; Sotirios K Goudos
Comparative Performance of Algorithmic Techniques for Optimizing Dual-Band Rectifier Conference
2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST), 2022, ISBN: 978-1-6654-6717-9.
Περίληψη | BibTeX | Ετικέτες: genetic algorithm, impedance matching, Optimization technique, rectenna, rectifier, RF energy harvesting, wireless sensor network | Σύνδεσμοι:
@conference{9837645,
title = {Comparative Performance of Algorithmic Techniques for Optimizing Dual-Band Rectifier},
author = {Maria S Papadopoulou and Achilles D Boursianis and Argyrios Chatzopoulos and Panagiotis Sarigiannidis and Spyridon Nikolaidis and Sotirios K Goudos},
url = {https://www.researchgate.net/publication/362330125_Comparative_Performance_of_Algorithmic_Techniques_for_Optimizing_Dual-Band_Rectifier},
doi = {10.1109/MOCAST54814.2022.9837645},
isbn = {978-1-6654-6717-9},
year = {2022},
date = {2022-06-08},
booktitle = {2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)},
pages = {1-4},
abstract = {Radio Frequency (RF) energy harvesting (EH) is a technique to replenish the source of wireless sensor networks (WSNs). Also, many interdisciplinary fields in the Internet-of-Things (IoT) era use RF-EH, like precision agriculture, biomedical, and robotics. Over the years, various designs have been presented in the literature operating in multi- or wide-band frequencies. Usually, a designed system is optimized using specific goals and optimization parameters to obtain maximization in power conversion efficiency (PCE). In this work, a dual-band RF rectifier system that resonates in the Wi-Fi frequency bands of 2.45 GHz and 5.8 GHz is presented. The proposed system is optimized using four optimization techniques, namely the Gradient algorithm, the Minimax algorithm, the Simulated Annealing, and the Genetic algorithm. A set of comparative results is presented to assess the performance of each technique and to obtain the feasible solution of the proposed design. Numerical results demonstrate that a 42.8% efficiency is achieved, having a 16 dBm input power and a 1.7 kΩ output resistance load.},
keywords = {genetic algorithm, impedance matching, Optimization technique, rectenna, rectifier, RF energy harvesting, wireless sensor network},
pubstate = {published},
tppubtype = {conference}
}
2018
K.C. Fountoukidis; C. Kalialakis; K.E. Psannis; K. Siakavara; S.K. Goudos; P. Sarigiannidis; M. Obaidat
MIMO antenna selection using biogeography-based optimization with nonlinear migration models Journal Article
In: International Journal of Communication Systems, vol. 31, no. 17, 2018.
Περίληψη | BibTeX | Ετικέτες: ant colony optimization, antenna selection, biogeography-based optimization, evolutionaryr algorithms, genetic algorithm, multiple-input multiple-output systems | Σύνδεσμοι:
@article{Fountoukidis2018,
title = {MIMO antenna selection using biogeography-based optimization with nonlinear migration models},
author = { K.C. Fountoukidis and C. Kalialakis and K.E. Psannis and K. Siakavara and S.K. Goudos and P. Sarigiannidis and M. Obaidat},
url = {https://www.researchgate.net/publication/327201674_MIMO_Antenna_Selection_Using_Biogeography_Based_Optimization_with_Non-Linear_Migration_Models},
doi = {10.1002/dac.3813},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Communication Systems},
volume = {31},
number = {17},
abstract = {This papers deals with the problem of antenna selection (AS) for a multiple-input multiple-output (MIMO) wireless system under the constraint of the channel capacity maximization. The biogeography-based optimization (BBO) algorithm is applied on the joint transmitter and receiver AS problem. Moreover, the performance of different BBO migration models is compared with a real valued genetic algorithm (RVGA) as well as with the ant colony optimization (ACO). Representative simulation scenarios are provided in detail, involving selection of 2 × 4,3 × 5,4 × 6,8 × 8 antennas in a 16 × 16 MIMO system. The numerical results demonstrate the efficiency and the applicability of the BBO algorithm in modern MIMO wireless systems. © 2018 John Wiley & Sons, Ltd.},
keywords = {ant colony optimization, antenna selection, biogeography-based optimization, evolutionaryr algorithms, genetic algorithm, multiple-input multiple-output systems},
pubstate = {published},
tppubtype = {article}
}
Διεύθυνση
Internet of Things and Applications Lab
Department of Electrical and Computer Engineering
University of Western Macedonia Campus
ZEP Area, Kozani 50100
Greece
Πληροφορίες Επικοινωνίας
tel: +30 2461 056527
Email: ithaca@uowm.gr