SIDSense: Database-Free TV White Space Sensing for Disaster-Resilient Connectivity
George M. Gichuru, Zoe Aiyanna M. Cayetano

TL;DR
SIDSense is a novel database-free TV White Space sensing framework that enhances disaster-resilient connectivity for Small Island Developing States by ensuring continuous operation during outages.
Contribution
It introduces a CNN-based spectrum classification system coupled with a hybrid sensing workflow and a compliance controller, enabling database-free TVWS operation in disaster-prone regions.
Findings
Achieved 94.2% sensing accuracy in field tests
Maintained zero missed 5G L1 deadlines during outages
Demonstrated sustained connectivity during simulated PAWS failures
Abstract
Small Island Developing States (SIDS) are disproportionately exposed to climate-driven disasters, yet often rely on fragile terrestrial networks that fail when they are most needed. TV White Space (TVWS) links offer long-range, low-power coverage; however, current deployments depend on Protocol to Access White Spaces (PAWS) database connectivity for channel authorization, creating a single point of failure during outages. We present SIDSense, an edge AI framework for database-free TVWS operation that preserves regulatory intent through a compliance-gated controller, audit logging, and graceful degradation. SIDSense couples CNN-based spectrum classification with a hybrid sensing-first, authorization-as-soon-as-possible workflow and co-locates sensing and video enhancement with a private 5G stack on a maritime vessel to sustain situational-awareness video backhaul. Field experiments…
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Taxonomy
TopicsCognitive Radio Networks and Spectrum Sensing · Mobile Crowdsensing and Crowdsourcing · Opportunistic and Delay-Tolerant Networks
