Spectrum Opportunity Map

Unlike a static geolocation database, a SOM defines opportunities with three-dimensional precision: frequency (Hz), geography (lat/lon), and time (UTC window). Each opportunity is a discrete, queryable object with a defined expiration timestamp.

• Frequency Resolution: Opportunities are defined down to individual resource blocks or channels, not broad bands.
• Geographic Precision: Coordinates are mapped to standardized grids like H3 hexagonal cells for distortion-minimizing spatial indexing.
• Temporal Validity: Each opportunity includes a time-to-live (TTL) derived from predictive REM forecasts of incumbent return probability.

A SOM is not merely a map of empty spectrum; it is a policy-aware filter that applies regulatory and operational constraints before declaring an opportunity viable. It ingests rules from a Spectrum Access System (SAS) or internal policy engine.

• Exclusion Zone Enforcement: Automatically subtracts protected contours around federal incumbents, radio astronomy sites, and coastlines.
• Power Spectral Density Limits: Assigns maximum allowable EIRP (Equivalent Isotropically Radiated Power) per opportunity to prevent aggregate interference.
• Coexistence Rules: Applies fairness algorithms to prevent a single secondary user from monopolizing available bandwidth in high-demand areas.

Every opportunity in the map carries a probabilistic confidence score derived from the underlying REM's Gaussian Process variance. This allows secondary users to make risk-aware transmission decisions.

• High-Confidence Opportunities: Derived from direct sensor measurements or validated incumbent deactivation signals. Suitable for high-reliability links.
• Low-Confidence Opportunities: Generated by spatial interpolation across sparse sensor coverage. Suitable for best-effort data offloading.
• Confidence Decay Function: The score degrades predictably as the time since the last sensor sweep increases, forcing a refresh before the TTL expires.

A mature SOM integrates spectrum occupancy prediction models to publish future opportunities, enabling proactive resource allocation rather than reactive spectrum hopping.

• Recurrent Neural Network Forecasts: Predicts when a channel currently occupied by a primary user will become available based on historical duty cycle patterns.
• Pre-Scheduled Reservations: Allows secondary networks to book future spectrum blocks, enabling deterministic quality-of-service for industrial automation.
• Anomaly-Triggered Revocation: If real-time sensing detects an unexpected incumbent transmission, the SOM issues an immediate opportunity revocation notice to all subscribed secondary users.

A SOM is designed for autonomous consumption by cognitive radio engines and network orchestrators, not human visualization. It exposes a low-latency query API.

• Geo-Query Endpoint: GET /opportunities?lat=38.9&lon=-77.0&radius=500m returns all viable frequencies for a specific location.
• Streaming Revocation Feed: A WebSocket channel pushes real-time spectrum evacuation commands when an incumbent is detected.
• Semantic Data Format: Opportunities are serialized in JSON-LD or Protocol Buffers with explicit entity linking to the governing regulatory policy and the sensor that validated the vacancy.

The SOM functions as a distributed ledger of interference contributions, tracking the aggregate noise floor rise caused by all active secondary users to ensure the protection contour of incumbents is never breached.

• Aggregate Interference Margin: Calculates the total allowable interference at an incumbent receiver and subtracts the contributions of all active secondary transmitters.
• Opportunity Pricing: When the margin approaches zero, remaining opportunities may be prioritized by a QoS tier or auction mechanism.
• Hidden Node Mitigation: Cross-references sensor data from multiple nodes to identify opportunities that are valid from one sensor's perspective but would cause a hidden node problem for a distant incumbent receiver.