Autonomous Spectrum Enforcement
Relevant Publications: DySPAN '21, TMC '22*, TMC '20, MS Thesis '20, TCCN '19, DySPAN '19, DySPAN '18
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.
#1. Autonomous Spectrum Sensing
Autonomous Spectrum Sensing: Leverages crowdsourced measurements as eye-witness accounts to deploy mobile, multi-modal agents (unmanned ground, sea or aerial vehicles) to potential infraction sites for further sensing, depending on the veracity of crowd measurements.
#2. Distributed Enforcement
Distributed Fusion System: Leverages the distributed consensus mechanism employed in Blockchain networks to record and disseminate the sensing reports and their veracity. This information is used to make reliable inferences among distributed trust-less agents.
Maqsood Careem
Autonomous enforcement of spectrum policies requires consensus among spatially scattered sensors and fusion of sensing results to detect anomalous behavior with the highest possible accuracy.