6G Multi-HAPS Networks: Coverage, Resilience and Priority-Aware Strategies

When terrestrial communications partially or completely fail, rapidly deployable non-terrestrial overlays can be decisive to preserve essential services. This thesis presents a modular simulation framework for multi-HAPS (High-Altitude Platform Station) networks targeting urban environments and large-scale outages. The framework integrates realistic MU-MIMO air-interface modeling, antenna directivity, and weather-aware propagation losses (free-space, atmospheric gases, rain, cloud/fog) within a priority-aware management layer. The architecture extends to HAPS-to-HAPS operation, enabling cooperative overlays when terrestrial infrastructure is degraded or unavailable. Evaluation over Paris, using Orange mobile-traffic traces, compares user association, scheduling, and content placement under fair-weather and worst-day meteorology. A BestHAPS association balancing link quality, platform load, and backhaul headroom, combined with weighted proportional-fair scheduling delivers robust per-area beam capacity (averaging ≈ 100 Mb/s). Capacity remains higher in suburban/rural sectors and tighter in dense urban zones, reflecting path loss and load patterns. Priority-aware allocation consistently favors critical services (e.g., hospitals, public safety), reducing blocking and tail latency. The simulator couples traffic, channel, and allocation policies, providing a reproducible testbed for multi-HAPS strategies. Limitations include simplified small-scale dynamics, coarse granularity in mobility and demand, and limited inter-HAPS coordination. Future work will incorporate richer channel and energy models, dynamic role switching, multi-hop relaying, and learning-based control for adaptive prioritization under uncertainty. Overall, the results support multi-HAPS overlays as a practical path to resilient communications for dual-use civil and military operations.