{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/107418"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/107418","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Reconfigurable Intelligent Metasurfaces for Wireless Communication and Sensing Applications","abstract":"In recent years, metasurfaces have shown promising abilities to control and manipulate electromagnetic (EM) waves through modified surface boundary conditions. These surfaces are electrically thin and comprise an array of spatially varying sub-wavelength scattering elements (or meta-atoms). Metasurfaces can transform an incident EM wave into an arbitrarily tailored transmitted or reflected wavefront through carefully engineering each meta-atom. Recent developments in metasurfaces have opened exciting new opportunities in antenna design, sensing, and communications systems. In particular, reconfigurable metasurfaces - wherein meta-atoms are embedded with active components - lead to the development of low-cost, lightweight, and compact systems capable of producing programmable radiation patterns and jointly performing multi-function communications, and enable advanced sensors for next-generation platforms. This research introduces reconfigurable metasurfaces and their various applications in designing simplified communications systems, wherein the RF aperture and transceiver are integrated within the metasurface. Finally, we will present our recent work on reconfigurable metasurfaces control, metasurface-enabled direct signal modulation, and deep learning-based metasurface design.","abstract_html":"In recent years, metasurfaces have shown promising abilities to control and manipulate electromagnetic (EM) waves through modified surface boundary conditions. These surfaces are electrically thin and comprise an array of spatially varying sub-wavelength scattering elements (or meta-atoms). Metasurfaces can transform an incident EM wave into an arbitrarily tailored transmitted or reflected wavefront through carefully engineering each meta-atom. Recent developments in metasurfaces have opened exciting new opportunities in antenna design, sensing, and communications systems. In particular, reconfigurable metasurfaces - wherein meta-atoms are embedded with active components - lead to the development of low-cost, lightweight, and compact systems capable of producing programmable radiation patterns and jointly performing multi-function communications, and enable advanced sensors for next-generation platforms. This research introduces reconfigurable metasurfaces and their various applications in designing simplified communications systems, wherein the RF aperture and transceiver are integrated within the metasurface. Finally, we will present our recent work on reconfigurable metasurfaces control, metasurface-enabled direct signal modulation, and deep learning-based metasurface design.","abstract_has_math":false,"creators":["Hodge II, John Adams"],"institution":"Virginia Tech","degree_name":"Doctor of Philosophy","degree_level":"doctoral","degree_discipline":"Electrical Engineering","degree_department":"Electrical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Zaghloul, Amir I."],"committee_members":["Scales, Wayne A.","Spence, Thomas G.","Manteghi, Majid","Mili, Lamine M.","Zheng, Xiaoyu"],"year":2022,"date_issued":"2022-01-05","date_published":"2022-01-05","updated_at":"2026-07-22T22:19:47Z","subjects":["Metasurfaces","Antennas","Electromagnetics","Reconfigurable Intelligent Surfaces","Wireless Communications","Deep learning (Machine learning)","Sensing"],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:33614"],"render_values":[{"text":"vt_gsexam:33614","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/107418","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Zaghloul, Amir I."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Scales, Wayne A.","Spence, Thomas G.","Manteghi, Majid","Mili, Lamine M.","Zheng, Xiaoyu"]},{"key":"dc:contributor.department","label":"Department","values":["Electrical Engineering"]},{"key":"dc:creator","label":"Author","values":["Hodge II, John Adams"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-01-06T09:00:15Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-01-06T09:00:15Z"]},{"key":"dc:date.issued","label":"Date","values":["2022-01-05"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Metasurfaces","Antennas","Electromagnetics","Reconfigurable Intelligent Surfaces","Wireless Communications","Deep learning (Machine learning)","Sensing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["vt_gsexam:33614"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/107418"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In recent years, metasurfaces have shown promising abilities to control and manipulate electromagnetic (EM) waves through modified surface boundary conditions. These surfaces are electrically thin and comprise an array of spatially varying sub-wavelength scattering elements (or meta-atoms). Metasurfaces can transform an incident EM wave into an arbitrarily tailored transmitted or reflected wavefront through carefully engineering each meta-atom. Recent developments in metasurfaces have opened exciting new opportunities in antenna design, sensing, and communications systems. In particular, reconfigurable metasurfaces - wherein meta-atoms are embedded with active components - lead to the development of low-cost, lightweight, and compact systems capable of producing programmable radiation patterns and jointly performing multi-function communications, and enable advanced sensors for next-generation platforms. This research introduces reconfigurable metasurfaces and their various applications in designing simplified communications systems, wherein the RF aperture and transceiver are integrated within the metasurface. Finally, we will present our recent work on reconfigurable metasurfaces control, metasurface-enabled direct signal modulation, and deep learning-based metasurface design."]},{"key":"dc:description.abstractgeneral","label":"General Abstract","values":["Metasurfaces are a promising new technology to enhance the capacity and coverage of wireless communication networks by dynamically reconfiguring the wireless propagation environment. These low-profile artificial electromagnetic surfaces, consisting of subwavelength resonant elements, are capable of tailoring electromagnetic waves controllably. In this dissertation, we control the transmission or reflection properties of the surface using digital codes by embedding tunable elements within each subwavelength element. Furthermore, metasurface antennas are a promising candidate for reducing the cost and hardware footprint of wireless sensor systems, such as radar or imaging. Using a digital microcontroller, we program the metasurface to steer the antenna beam in the direction of interest, modulate the radio wave, or change the polarization of an incoming signal. In addition to dynamic beamforming capabilities, we program the metasurface to reduce the scattering of an incoming signal, thereby reducing its perturbations on the radio environment. Still, the design of metasurfaces for specific applications remains complex and technically challenging. Lastly, we present innovative deep learning techniques to simplify metasurface design."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Doctor of Philosophy"]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["ETD"]},{"key":"dc:title","label":"Title","values":["Reconfigurable Intelligent Metasurfaces for Wireless Communication and Sensing Applications"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Zaghloul, Amir I."],"dc:contributor.committeemember":["Scales, Wayne A.","Spence, Thomas G.","Manteghi, Majid","Mili, Lamine M.","Zheng, Xiaoyu"],"dc:contributor.department":["Electrical Engineering"],"dc:creator":["Hodge II, John Adams"],"dc:date.accessioned":["2022-01-06T09:00:15Z"],"dc:date.available":["2022-01-06T09:00:15Z"],"dc:date.issued":["2022-01-05"],"dc:description.abstract":["In recent years, metasurfaces have shown promising abilities to control and manipulate electromagnetic (EM) waves through modified surface boundary conditions. These surfaces are electrically thin and comprise an array of spatially varying sub-wavelength scattering elements (or meta-atoms). Metasurfaces can transform an incident EM wave into an arbitrarily tailored transmitted or reflected wavefront through carefully engineering each meta-atom. Recent developments in metasurfaces have opened exciting new opportunities in antenna design, sensing, and communications systems. In particular, reconfigurable metasurfaces - wherein meta-atoms are embedded with active components - lead to the development of low-cost, lightweight, and compact systems capable of producing programmable radiation patterns and jointly performing multi-function communications, and enable advanced sensors for next-generation platforms. This research introduces reconfigurable metasurfaces and their various applications in designing simplified communications systems, wherein the RF aperture and transceiver are integrated within the metasurface. Finally, we will present our recent work on reconfigurable metasurfaces control, metasurface-enabled direct signal modulation, and deep learning-based metasurface design."],"dc:description.abstractgeneral":["Metasurfaces are a promising new technology to enhance the capacity and coverage of wireless communication networks by dynamically reconfiguring the wireless propagation environment. These low-profile artificial electromagnetic surfaces, consisting of subwavelength resonant elements, are capable of tailoring electromagnetic waves controllably. In this dissertation, we control the transmission or reflection properties of the surface using digital codes by embedding tunable elements within each subwavelength element. Furthermore, metasurface antennas are a promising candidate for reducing the cost and hardware footprint of wireless sensor systems, such as radar or imaging. Using a digital microcontroller, we program the metasurface to steer the antenna beam in the direction of interest, modulate the radio wave, or change the polarization of an incoming signal. In addition to dynamic beamforming capabilities, we program the metasurface to reduce the scattering of an incoming signal, thereby reducing its perturbations on the radio environment. Still, the design of metasurfaces for specific applications remains complex and technically challenging. Lastly, we present innovative deep learning techniques to simplify metasurface design."],"dc:description.degree":["Doctor of Philosophy"],"dc:format.medium":["ETD"],"dc:identifier.other":["vt_gsexam:33614"],"dc:identifier.uri":["http://hdl.handle.net/10919/107418"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:subject":["Metasurfaces","Antennas","Electromagnetics","Reconfigurable Intelligent Surfaces","Wireless Communications","Deep learning (Machine learning)","Sensing"],"dc:title":["Reconfigurable Intelligent Metasurfaces for Wireless Communication and Sensing Applications"],"dc:type":["Dissertation"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:47Z"}