Date of Award




Document Type

Master's Thesis

Degree Name

Master of Science (MS)


Department of Electrical and Computer Engineering

Content Description

1 online resource (xi, 72 pages) : illustrations (some color)

Dissertation/Thesis Chair

Aveek Dutta

Committee Members

Dola Saha, Hany Elgala


Autonomous agent, Blockchain, Crowdsourced, Enforcement, Multiagent planning, Spectrum sensing, Multiple access protocols (Computer network protocols), Radio frequency allocation, Broadband communication systems, Wireless Internet, Wireless communication systems, Radio resource management (Wireless communications), Blockchains (Databases)

Subject Categories

Computer Engineering | Computer Sciences | Electrical and Electronics


A core limitation in existing wireless technologies is the scarcity of spectrum, to support the exponential increase in Internet-connected and multimedia-capable mobile devices and the increasing demand for bandwidth-intensive services. As a solution, Dynamic Spectrum Access policies are being ratified to promote spectrum sharing for various spectrum bands and to improve the spectrum utilization. This poses an equally challenging problem of enforcing these spectrum policies. The distributed and dynamic nature of policy violations necessitates the use of autonomous agents to implement efficient and agile enforcement systems. The design of such a fully autonomous enforcement system is complicated due to the lack of trust in the agents and the requirement for agile scheduling schemes. We architect a deployable system, which leverages crowdsourced agents as eye-witnesses, to efficiently deploy mobile, multi-modal agents (unmanned land, sea or aerial vehicles) to potential spectrum infraction sites to collectively improve the enforcement accuracy. We leverage the distributed consensus mechanism employed in Blockchain networks to make distributed accurate and credible inferences even from trust-less agents. Collectively this leads to a highly reliable and feasible autonomous spectrum enforcement strategy, which outperforms static and purely crowdsourced enforcement paradigms.