{"id":{"repo_id":"houston","oai_identifier":"oai:uh-ir.tdl.org:10657/20707"},"canonical_url":"https://search.dev.ndltd.org/etd/houston/oai:uh-ir.tdl.org:10657/20707","repository":{"repo_id":"houston","name":"University of Houston","base_url":"https://uh-ir.tdl.org/server/oai/request"},"display":{"title":"Multiobjective RF Communication Networks: Theory and Hardware Implementation","abstract":"Communication networks play a central role in many fields of modern technology, from industry to agriculture, to defense, to development of urban or rural areas. Regardless of the medium this dissertation is found on, either paper or a digital copy, it was brought to your hands thanks to an exchange of information between my computer and some server closer to your location. Even more with the evolution of cell phones and the advent of the Internet of Things (IoT), reliable, resilient and high speed networks are the backbone of modern society. By virtue of the pivotal role of networks, great focus is placed on the optimization of their cost. The cost of a network can be expressed in terms of several different factors: the cost of adding a node, the cost of transmitting a signal from a node to the other, the cost of reorganizing the network if a node fails, to name a few. If nodes have to perform additional tasks, possibly unrelated to communication, additional costs may need to be considered, and the resources of the underlying system may need to be shared between conflicting activities. Conflict, in this case, is defined as the tendency of two or more cost functions to have the same trend (decreasing or increasing) when the same system resource is consumed. Optimization of multiple concurrent costs, also known as Multi-objective optimization, is a branch of mathematics that generalizes single cost optimization, and to do so it introduces specific definitions and tools. This manuscript contributes to research on optimization of communication networks in two ways: on one side, by focusing on general algorithms that provide a quantitative guidance for network designers, to build a network that simultaneously optimizes some selected concurrent costs. On the other side, by developing a hardware solution that realizes a very specific transmission scheme for an individual network node: beamforming. Instead of a single antenna broadcasting information in the spatial directions dictated by its design, beamforming entails a system of antennas that collectively enhance broadcasting only in selected directions, exploiting constructive and destructive interference of the electromagnetic field. Beamforming has the advantage of focusing transmission power, limiting both energy waste and eavesdropping of information. Beamforming is widely used in radars and satellites, and in smaller scale, also in cellphones.","abstract_html":"Communication networks play a central role in many fields of modern technology, from industry to agriculture, to defense, to development of urban or rural areas. Regardless of the medium this dissertation is found on, either paper or a digital copy, it was brought to your hands thanks to an exchange of information between my computer and some server closer to your location. Even more with the evolution of cell phones and the advent of the Internet of Things (IoT), reliable, resilient and high speed networks are the backbone of modern society. By virtue of the pivotal role of networks, great focus is placed on the optimization of their cost. The cost of a network can be expressed in terms of several different factors: the cost of adding a node, the cost of transmitting a signal from a node to the other, the cost of reorganizing the network if a node fails, to name a few. If nodes have to perform additional tasks, possibly unrelated to communication, additional costs may need to be considered, and the resources of the underlying system may need to be shared between conflicting activities. Conflict, in this case, is defined as the tendency of two or more cost functions to have the same trend (decreasing or increasing) when the same system resource is consumed. Optimization of multiple concurrent costs, also known as Multi-objective optimization, is a branch of mathematics that generalizes single cost optimization, and to do so it introduces specific definitions and tools. This manuscript contributes to research on optimization of communication networks in two ways: on one side, by focusing on general algorithms that provide a quantitative guidance for network designers, to build a network that simultaneously optimizes some selected concurrent costs. On the other side, by developing a hardware solution that realizes a very specific transmission scheme for an individual network node: beamforming. Instead of a single antenna broadcasting information in the spatial directions dictated by its design, beamforming entails a system of antennas that collectively enhance broadcasting only in selected directions, exploiting constructive and destructive interference of the electromagnetic field. Beamforming has the advantage of focusing transmission power, limiting both energy waste and eavesdropping of information. Beamforming is widely used in radars and satellites, and in smaller scale, also in cellphones.","abstract_has_math":false,"creators":["Bernardini, Francesco 1983-"],"institution":"University of Houston","degree_name":"Doctor of Philosophy","degree_level":null,"degree_discipline":"Electrical Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Becker, Aaron T"],"committee_chairs":[],"committee_members":["Onofrei, Daniel","Jackson, David R","Leclerc, Julien","Chen, Jinghong","Chen, Yuhua","Ordonez, Carlos R."],"year":2025,"date_issued":"2025-08","date_published":"2025-08","updated_at":"2026-07-24T02:32:24Z","subjects":["Electrical engineering","Computer engineering"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10657/20707","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Becker, Aaron T"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Onofrei, Daniel","Jackson, David R","Leclerc, Julien","Chen, Jinghong","Chen, Yuhua","Ordonez, Carlos R."]},{"key":"dc:creator","label":"Author","values":["Bernardini, Francesco 1983-"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-10-06T20:00:19Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-08"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Houston"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical engineering","Computer engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10657/20707"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Communication networks play a central role in many fields of modern technology, from industry to agriculture, to defense, to development of urban or rural areas. Regardless of the medium this dissertation is found on, either paper or a digital copy, it was brought to your hands thanks to an exchange of information between my computer and some server closer to your location. Even more with the evolution of cell phones and the advent of the Internet of Things (IoT), reliable, resilient and high speed networks are the backbone of modern society. By virtue of the pivotal role of networks, great focus is placed on the optimization of their cost. The cost of a network can be expressed in terms of several different factors: the cost of adding a node, the cost of transmitting a signal from a node to the other, the cost of reorganizing the network if a node fails, to name a few. If nodes have to perform additional tasks, possibly unrelated to communication, additional costs may need to be considered, and the resources of the underlying system may need to be shared between conflicting activities. Conflict, in this case, is defined as the tendency of two or more cost functions to have the same trend (decreasing or increasing) when the same system resource is consumed. Optimization of multiple concurrent costs, also known as Multi-objective optimization, is a branch of mathematics that generalizes single cost optimization, and to do so it introduces specific definitions and tools. This manuscript contributes to research on optimization of communication networks in two ways: on one side, by focusing on general algorithms that provide a quantitative guidance for network designers, to build a network that simultaneously optimizes some selected concurrent costs. On the other side, by developing a hardware solution that realizes a very specific transmission scheme for an individual network node: beamforming. Instead of a single antenna broadcasting information in the spatial directions dictated by its design, beamforming entails a system of antennas that collectively enhance broadcasting only in selected directions, exploiting constructive and destructive interference of the electromagnetic field. Beamforming has the advantage of focusing transmission power, limiting both energy waste and eavesdropping of information. Beamforming is widely used in radars and satellites, and in smaller scale, also in cellphones."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Multiobjective RF Communication Networks: Theory and Hardware Implementation"]}]}],"canonical_facts":{"dc:contributor.advisor":["Becker, Aaron T"],"dc:contributor.committeemember":["Onofrei, Daniel","Jackson, David R","Leclerc, Julien","Chen, Jinghong","Chen, Yuhua","Ordonez, Carlos R."],"dc:creator":["Bernardini, Francesco 1983-"],"dc:date.accessioned":["2025-10-06T20:00:19Z"],"dc:date.issued":["2025-08"],"dc:description.abstract":["Communication networks play a central role in many fields of modern technology, from industry to agriculture, to defense, to development of urban or rural areas. 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Conflict, in this case, is defined as the tendency of two or more cost functions to have the same trend (decreasing or increasing) when the same system resource is consumed. Optimization of multiple concurrent costs, also known as Multi-objective optimization, is a branch of mathematics that generalizes single cost optimization, and to do so it introduces specific definitions and tools. This manuscript contributes to research on optimization of communication networks in two ways: on one side, by focusing on general algorithms that provide a quantitative guidance for network designers, to build a network that simultaneously optimizes some selected concurrent costs. On the other side, by developing a hardware solution that realizes a very specific transmission scheme for an individual network node: beamforming. Instead of a single antenna broadcasting information in the spatial directions dictated by its design, beamforming entails a system of antennas that collectively enhance broadcasting only in selected directions, exploiting constructive and destructive interference of the electromagnetic field. Beamforming has the advantage of focusing transmission power, limiting both energy waste and eavesdropping of information. Beamforming is widely used in radars and satellites, and in smaller scale, also in cellphones."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/10657/20707"],"dc:language.iso":["English"],"dc:subject":["Electrical engineering","Computer engineering"],"dc:title":["Multiobjective RF Communication Networks: Theory and Hardware Implementation"],"dc:type":["Thesis"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["University of Houston"]},"updated_at":"2026-07-24T02:32:24Z"}