Optimal Dense Base Station Deployment for Resilient Communication Networks

Communication networks are of critical importance to modern societies. However, they are often susceptible to disruption due to natural disasters, which can have significant economic and social impacts. In order, to mitigate the aforementioned impacts, a novel spatio-temporal risk-based optimization framework for designing disaster-resilient communication networks is introduced. This framework addresses both cost-effectiveness and risk minimization in a unified manner. The effects of physical damage, power disruption, and recovery dynamics on the outage probability over time are incorporated into a dual-objective optimization model. A key innovation is the incorporation of spatial heterogeneity, which enables region-specific base station density allocation that reflect spatial variations in seismic intensity. The proposed framework, which utilizes a convex optimization strategy and Karush-Kuhn-Tucker conditions, achieves optimal resource allocation while satisfying cost and risk constraints. This methodology has been demonstrated to enhance network resilience in high-risk regions while incurring no additional costs, thus providing a scalable and adaptable solution applicable to a variety types of natural hazards and geographic contexts.