Artificial Intelligence and Operations Research for Defense and Telecommunications

Network Configuration and Telecommunications Scheduling

In telecommunications systems, optimal network configuration and efficient communication scheduling are essential for ensuring reliable and resilient connectivity. Among the various Artificial Intelligence and Operations Research techniques, constraint programming and graph theory provide powerful tools to model and solve these complex problems.

Modeling Resilient Networks with Topological Constraints

A telecommunications network relies on a graph of connections between nodes (stations, satellites, antennas, relays, etc.). To ensure optimal connectivity, several constraints must be met:

• Network connectivity: Each node must be accessible from another to prevent isolated areas.
• Node degree: Each station or satellite has a limited number of possible connections.
• Frequency allocation: Frequencies must be assigned while avoiding interference and maximizing spectral efficiency.
• Network resilience: To ensure network resilience in case of node or link failure, a robust backbone must be designed. This can be modeled through the search for a dominating set in a graph.

Scheduling Communications with Time Windows

Satellite communications require precise temporal alignment between ground stations and satellites, with constraints such as:

• Visibility windows: Each station can only communicate with a satellite during specific time slots.
• Limited bandwidth: Transmissions must be scheduled based on available resources.
• Dynamic frequency allocation: To avoid interference and maximize radio spectrum efficiency.

With constraint programming, it is possible to ensure optimal scheduling of communications while complying with physical and operational constraints.