This thesis studies the problem of determining achievable rates in heterogeneous wireless networks. We analyze the impact of location, traffic, and service heterogeneity. Consider a wireless network with n nodes located in a square area of size n communicating with each other over Gaussian fading channels. Location heterogeneity is modeled by allowing the nodes in the wireless network to be deployed in an arbitrary manner on the square area instead of the usual random uniform node placement. For traffic heterogeneity, we analyze the n x n dimensional unicast capacity region. For service heterogeneity, we consider the impact of multicasting and caching. This gives rise to the n x 2n dimensional multicast capacity region and the 2" x n dimensional caching capacity region. In each of these cases, we obtain an explicit information-theoretic characterization of the scaling of achievable rates by providing a converse and a matching (in the scaling sense) communication architecture.