Transition probability estimates for long range random walks

Let $(M,d,\mu)$ be a uniformly discrete metric measure space satisfying space homogeneous volume doubling condition. We consider discrete time Markov chains on $M$ symmetric with respect to $\mu$ and whose one-step transition density is comparable to $(V_h(d(x,y)) \phi(d(x,y))^{-1}$, where $\phi$ is a positive continuous regularly varying function with index $\beta \in (0,2)$ and $V_h$ is the homogeneous volume growth function. Extending several existing work by other authors, we prove global upper and lower bounds for $n$-step transition probability density that are sharp up to constants.