CV


FA
HASSAN FARSI

HASSAN FARSI

Professor

hfarsi@birjand.ac.ir

دانشکده/پردیس: Electrical and Computer Engineering

Degree: Ph.D

CV
FA
HASSAN FARSI

Professor HASSAN FARSI

hfarsi@birjand.ac.ir
دانشکده/پردیس: Electrical and Computer Engineering Degree: Ph.D |

Dual-Objective Design of Broadband Rectenna and Anchor Node Optimization for Energy Harvesting and High-Accuracy UWB Localization

AuthorsHassan Farsi,Iman Poorjangi
JournalInternational Journal of Engineering, Transactions A: Basics
Page number1113-1128
Serial number40
Volume number4
Paper TypeFull Paper
Published At2027
Journal TypeTypographic
Journal CountryIran, Islamic Republic Of
Journal Indexisc،Scopus
KeywordsWireless power transfer (WPT), energy harvesting, rectenna, ultra, wideband (UWB), localization, anchor node optimization;

Abstract

Wireless sensor networks and portable devices face two major challenges: sustainable energy supply and high-precision indoor localization. While far-field wireless power transfer (WPT) offers energy solutions, it suffers from low power density and environmental sensitivity. To mitigate these drawbacks, the proposed system incorporates polarization diversity and a wideband impedance matching strategy. Simultaneously, GPS fails in indoor environments, driving the need for ultra-wideband (UWB) localization to achieve centimeter-level accuracy. This paper presents a dual-objective framework to tackle both issues. First, it designs a broadband antenna array (1–20 GHz) with multi-polarization reception, combined with an optimized matching network and Schottky-based rectifier to enhance RF-to-DC conversion under low power. Second, it introduces an anchor placement optimization algorithm for UWB that uses probabilistic target behavior models to minimize positioning errors. Simulation results confirm that the energy harvester remains effective across various incident angles and frequencies, while the localization error is consistently reduced to around one centimeter. The integrated approach provides a comprehensive solution for next-generation WSNs, overcoming power management bottlenecks while elevating localization accuracy to approximately one centimeter.

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