Let P := { X_i,i >= 1} be a stationary Poisson point process in R^d, { C_i,i >= 1} be a sequence of i.i.d. random sets in R^d, and { Y_i^t; t \geq 0, i >= 1} be i.i.d. { 0,1}-valued continuous time stationary Markov chains. We define the Markov-Poisson-Boolean model C_t := { Y_i^t(X_i + C_i), i >= 1}. C_t represents the coverage process at time t. We first obtain limit laws for k-coverage of an area at an arbitrary instant. We then obtain the limit laws for the k-coverage seen by a particle as it moves along a one-dimensional path.
Categories: math.PR