  In this paper, we present a detailed framework to analyze the evolution of
the random topology of a time-varying wireless network via the information
theoretic notion of entropy rate. We consider a propagation channel varying
over time with random node positions in a closed space and Rayleigh fading
affecting the connections between nodes. The existence of an edge between two
nodes at given locations is modeled by a Markov chain, enabling memory effects
in network dynamics. We then derive a lower and an upper bound on the entropy
rate of the spatiotemporal network. The entropy rate measures the shortest
per-step description of the stationary stochastic process defining the state of
the wireless system and depends both on the maximum Doppler shift and the path
loss exponent. It characterizes the topological uncertainty of the wireless
network and quantifies how quickly the underlying topology is varying with
time.
