With the dense deployment of small cell networks, the powering and backhaul problem of small cell base stations (SBSs) has attracted great attention, and energy harvesting technology and self-backhaul technology have been proposed as promising solutions. Although some excellent works have been done on energy harvesting and self-backhaul in small cell networks, most existing works do not consider them jointly. In this paper, we aim at green small cell networks by jointly achieving self-backhaul and energy harvesting. In addition, full-duplex and massive multiple-input and multiple-output technologies are also exploited to enhance the system performance. In order to improve the energy efficiency (EE) further, a novel precoding scheme is designed to eliminate both the inter-Tier and multi-user interference. Based on the proposed precoding scheme, we formulate the cell association and power allocation problem as an optimization problem to optimize the system EE performance, with the energy arrival rate and remaining battery energy in SBSs involved. The formulated optimization problem implies a sleep mechanism to control the ON/OFF of SBSs, which will further reduce the energy consumption of small cell networks. In addition, to reduce the computation complexity to solve this non-convex problem, we propose to transform the original problem into a difference of convex program, which can be efficiently solved via a constrained concave convex procedure-based algorithm. Extensive simulation results are presented to justify the effectiveness of the proposed scheme with different system configurations.

Additional Metadata
Keywords energy harvesting, full-duplex, massive MIMO, self-backhaul, Small cell networks
Persistent URL dx.doi.org/10.1109/JSAC.2016.2611846
Journal IEEE Journal on Selected Areas in Communications
Citation
Chen, L. (Lei), Yu, F.R, Ji, H. (Hong), Rong, B. (Bo), Li, X. (Xi), & Leung, V.C.M. (Victor C. M.). (2016). Green Full-Duplex Self-Backhaul and Energy Harvesting Small Cell Networks with Massive MIMO. IEEE Journal on Selected Areas in Communications, 34(12), 3709–3724. doi:10.1109/JSAC.2016.2611846