Skip to main content

Frequency-Agile Beam-Switchable Antenna

Gu, Chao, Gao, Steven, Sanz-Izquierdo, Benito, Parker, Edward A., Li, Wenting, Yang, Xuexia, Cheng, Zhiqun (2017) Frequency-Agile Beam-Switchable Antenna. IEEE Transactions on Antennas and Propagation, 65 (8). pp. 3819-3826. ISSN 0018-926X. (doi:10.1109/TAP.2017.2713978) (KAR id:62715)

PDF Publisher pdf
Language: English


Download (802kB) Preview
[thumbnail of 07951031.pdf]
Preview
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL
https://doi.org/10.1109/TAP.2017.2713978

Abstract

A novel antenna with both frequency and pattern reconfigurability is presented. The reconfigurability is achieved by integrating an active frequency selective surface (AFSS) with feed antenna. The smart FSS comprises a printed slot array loaded by varactors. A novel dc biasing arrangement is proposed to feed the slots vertically so that the unwanted effects caused by bias lines are minimized. A monopole antenna is designed to illuminate the AFSS. The resulting structure can operate in a frequency tuning range of 30%. By reconfiguring the different sections of active FSS cylinder into a transparent or reflector mode, the omnidirectional pattern of the source antenna can be converted to a directive beam. As an illustration, half of the AFSS cylinder is successively biased, enabling the beam switching to cover the entire horizontal plane over a range of frequencies. An antenna prototype was fabricated and measured. Experimental results demonstrate the capability of providing useful gain levels and good impedance matching from 1.7 to 2.3 GHz. The antenna offers a low-cost, low-power solution for wireless systems that require frequency and beam reconfigurable antennas. The proposed design consumes about 1000 times less dc power than the equivalent narrowband beam-switching antenna design using p-i-n diode-loaded AFSS.

Item Type: Article
DOI/Identification number: 10.1109/TAP.2017.2713978
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Steven Gao
Date Deposited: 14 Aug 2017 14:12 UTC
Last Modified: 16 Feb 2021 13:47 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/62715 (The current URI for this page, for reference purposes)
Gao, Steven: https://orcid.org/0000-0002-7402-9223
Sanz-Izquierdo, Benito: https://orcid.org/0000-0001-7313-2520
  • Depositors only (login required):

Downloads

Downloads per month over past year