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Future mobile networks are converging toward heterogeneous multi-tier networks, where various classes of base stations (BS) are deployed based on user demand. So it is quite necessary to utilize the BSs resources rationally when BSs are sufficient. In this paper, we develop a more realistic model that fully considering the inter-tier dependence and the dependence between users and BSs, where the macro base stations (MBSs) are distributed according to a homogeneous Poisson point process (PPP) and the small base stations (SBSs) follows a Matern cluster process (MCP) whose parent points are located in the positions of the MBSs in order to offload the users from the over-loaded MBSs. We also assume the users are just randomly located in the circles centered at the MBSs. Under this model, we derive the association probability and the average ergodic rate by stochastic geometry. An interesting result that the density of MBS and the radius of the clusters jointly affect the association probabilities in a joint form is obtained. We also observe that using the clustered SBSs results in aggressive offloading compared with previous cellular networks.

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With the exponential growth of mobile data traffic, the deployment of a large number of devices in the hot-spot gathering scenario has brought great challenges to the current wireless communication network. Considering that the user service latency of unidirectional data offloading scheme is still unacceptable when 5G and Wi-Fi coexist on the unlicensed 60 GHz band, we investigate a bidirectional data offloading scheme with resource allocation in this study. More specifically, aggregation nodes (ANs) are deployed in the coverage of Wi-Fi AP to receive multi-user data in parallel in order to reduce the collision probability of transmitted packets. Then, we formulate an optimization problem aiming to maximize the sum rate through spectrum and power allocation as well as user association. The problem is then decomposed into three sub-problems and solved successively, where RSSI (received signal strength indicator) as the standard determines the user association, while the algorithms of multi-stage matching and successive convex approximation are used for solving spectrum allocation and power allocation, respectively. Simulation results demonstrate that the proposed algorithm can effectively increase the total capacity of the uplink coexisting networks.