Cellular Offloading in Heterogeneous Mobile Networks With D2D Communication Assistance

Abstract

The next-generation mobile communication system [fifth-generation (5G)] needs to address the challenges stemming from the performance requirements in diverse technical scenarios, such as seamless wide-area coverage, high-capacity hot-spots, and low-power massive connections. It is widely recognized that traditional single-tier cellular network architecture is not adequate to meet these requirements, and thus, the heterogeneous cellular network (HetNet) has been identified as a promising network architecture for 5G. In HetNets, traffic offloading can be exploited to effectively improve network capacity by utilizing complementary network communication techniques. In this paper, we propose a device-to-device (D2D) communication assisted mobile traffic offloading (DATO) scheme, with focus on massive connections for machine type communications (MTC). DATO determines access mode for user equipments (UEs) to offload UEs from macro base stations (MBSs) to small base stations via D2D communications to improve the overall network capacity and mitigate the traffic congestion at MBSs. We formulate the DATO problem as a 0–1 linear programing and prove it to be NP-hard. We resort to dynamic programing to provide the optimal solution, as well as the theoretical performance upper bound of DATO. We develop an efficient algorithm to solve the DATO problem while preserving the optimality by making use of the location relationship of BSs and UEs. We apply our proposed DATO scheme to a series of typical network scenarios to validate its effectiveness. Numerical results reveal that DATO significantly outperforms traditional UE access mode in terms of network capacity and UE energy consumption, which are important to massive MTC.