Improvements to Enhance The Security and Reliability of Crowdsourced Spectrum Access Systems and Cognitive Radio Networks
dc.contributor.author | Tolley, Joseph D. | en |
dc.contributor.committeecochair | Patterson, Cameron D. | en |
dc.contributor.committeecochair | Dietrich, Carl B. | en |
dc.contributor.committeemember | Reid, Kenneth J. | en |
dc.contributor.committeemember | Zeng, Haibo | en |
dc.contributor.committeemember | Paul, JoAnn M. | en |
dc.contributor.department | Electrical and Computer Engineering | en |
dc.date.accessioned | 2025-10-08T11:54:23Z | en |
dc.date.available | 2025-10-08T11:54:23Z | en |
dc.date.issued | 2025-09-23 | en |
dc.description.abstract | This dissertation addresses key challenges in dynamic spectrum sharing within Cognitive Radio Networks (CRNs) and Spectrum Access Systems (SASs), focusing on the U.S. 3.5 GHz Citizens Broadband Radio Service (CBRS) band. A structured survey of existing regulatory frameworks, coordination methods, and interference mitigation strategies provides context for the research contributions that follow. To enhance trust in user-reported data, the Whisper Key Location Verification method is introduced. It validates the physical location of crowdsourced nodes by combining radio and internet-based checks, filtering out falsified reports and improving Primary User (PU) protection. The Enhanced Heartbeat Protocol (EHP) enhances SAS–Secondary User (SU) communication through asynchronous messaging and an expanded message format, enabling faster spectrum reassignments and supporting mobile scenarios, such as UAV networks. To detect Spectrum Sensing Data Falsification (SSDF) attacks, a real-time framework using lightweight similarity metrics identifies duplicated or manipulated sensing data, increasing system resilience. Finally, the Radio Frequency Obstructed Observation Area Identification (RF-OOAI) method distinguishes environmental signal loss from intentional misreporting, preserving the reputation of honest users. These contributions collectively improve the accuracy, efficiency, and robustness of shared spectrum systems, advancing the design and reliability of CRNs and SASs in complex real-world settings. | en |
dc.description.abstractgeneral | This dissertation explores how wireless devices can share access to the airwaves more efficiently and fairly — especially in crowded parts of the spectrum like the 3.5 GHz Citizens Broadband Radio Service (CBRS) band in the U.S. As demand for wireless communication grows, it’s critical to find smarter ways for different users and systems to share frequencies without interfering with each other. To support this, the research introduces several new methods. One verifies the physical location of users who report data about local signal conditions, helping weed out false reports and protecting the rights of higher-priority users. Another improvement is communication between systems that manage spectrum access and devices that use it, allowing for quicker and more flexible updates, which is an important feature for mobile systems like drones. The work also addresses the threat of bad actors who submit fake data to manipulate spectrum availability. A lightweight detection system spots suspicious patterns in real-time, helping keep the system honest and reliable. Finally, a new technique can tell the difference between signal loss caused by natural obstacles like buildings or hills and cases where users might be misreporting signal conditions on purpose. Together, these innovations make shared wireless systems more secure, accurate, and responsive, laying the groundwork for better performance in everything from mobile networks to next-generation communication systems. | en |
dc.description.degree | Doctor of Philosophy | en |
dc.format.medium | ETD | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.uri | https://hdl.handle.net/10919/138097 | en |
dc.language.iso | en | en |
dc.publisher | Virginia Tech | en |
dc.rights | CC0 1.0 Universal | en |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | en |
dc.subject | Cognitive Radio | en |
dc.subject | Crowdsourcing | en |
dc.subject | Radio | en |
dc.subject | Spectrum Access | en |
dc.subject | Trust | en |
dc.title | Improvements to Enhance The Security and Reliability of Crowdsourced Spectrum Access Systems and Cognitive Radio Networks | en |
dc.type | Dissertation | en |
dc.type.dcmitype | Text | en |
thesis.degree.discipline | Computer Engineering | en |
thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
thesis.degree.level | doctoral | en |
thesis.degree.name | Doctor of Philosophy | en |