@inproceedings{
 title = {Waveform Design for Optimal Wireless Power Transfer Using Evolutionary Algorithms},
 type = {inproceedings},
 year = {2020},
 keywords = {Channel State Information,Evolutionary Algorithms,Waveform Design,Wireless Power Transfer},
 pages = {1-4},
 websites = {https://ieeexplore.ieee.org/document/9200277/},
 month = {9},
 publisher = {IEEE},
 id = {f105ac41-1429-3372-a2da-05da8ca26df0},
 created = {2020-09-29T12:14:02.807Z},
 file_attached = {true},
 profile_id = {92581d97-724a-345d-9f14-9035bd05a74d},
 last_modified = {2020-09-29T12:14:17.785Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {One of the possible ways to increase the end-to-end power transfer efficiency in a radiative Wireless Power Transfer (WPT) system is by transmitting multi-tone signals optimized according to the receiver rectenna's nonlinear behavior and the Channel State Information (CSI). This optimization problem is a non-convex problem that has been tackled in the past with Sequential Convex Programming (SCP) algorithms. Since SCP algorithms do not guarantee to track the globally optimal solutions, there is interest in applying some other optimization methods to this problem. Here we apply various Evolutionary Algorithms (EAs) with different characteristics. The performance of the designed waveforms is evaluated in Matlab, using a simplified Single Input Single Output (SISO) system model. EAs are successfully applied to waveform design for WPT and seem to track the optimal solutions in the tested cases. Moreover, the effectiveness of the SCP-QCLP method is verified.},
 bibtype = {inproceedings},
 author = {Doanis, Pavlos and Boursianis, Achilles D. and Huillery, Julien and Breard, Arnaud and Duroc, Yvan and Goudos, Sotirios K.},
 doi = {10.1109/MOCAST49295.2020.9200277},
 booktitle = {2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST)}
}

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