  In this paper, we consider networks of static sensors with integrated sensing
and communication capabilities. The goal of the sensors is to propagate their
collected information to every other agent in the network and possibly a human
operator. Such a task requires constant communication among all agents which
may result in collisions and congestion in wireless communication. To mitigate
this issue, we impose locally non-interfering connectivity constraints that
must be respected by every agent. We show that these constraints along with the
requirement of propagating information in the network can be captured by a
Linear Temporal Logic (LTL) framework. Existing temporal logic control
synthesis algorithms can be used to design correct-by-construction
communication schedules that satisfy the considered LTL formula. Nevertheless,
such approaches are centralized and scale poorly with the size of the network.
We propose a hierarchical LTL-based algorithm that designs communication
schedules that determine which agents should communicate while maximizing
network usage. We show that the proposed algorithm is complete and demonstrate
its efficiency and scalability through analysis and numerical experiments.
