LAUSR

This paper tackles the resource allocation (RA) problem of a full-duplex (FD) device-to-device (D2D) communications enabled cellular network. In the considered scenario, multiple FD-D2D pairs share the uplink channels of the regular cellular users (CUs) which leads to mutual interference between the two communication types. Within this interference environment, this paper aims to properly allocate the network’s resources, such as the transmit power and the channels, to maximize a network-centric metric like the weighted-sum rate (WSR) and the global energy efficiency (GEE). The complex coupling between the mutual interference of the different links, as well as the flexibility of assigning the channels to the users, results in a non-convex RA optimization problem, for which the global optimal solution is hard to obtain. This paper is a first and innovative approach that globally solves the RA problem of an FD-D2D-based cellular network. In particular, we show that the global optimal solution can be achieved by decoupling the original problem into two sub-problems as power allocation (PA) and channel assignment (CA). The PA sub-problem is solved by means of monotonic optimization theory. Precisely, we propose a new polyblock-based algorithm, MARIO, which efficiently converges to the global solution of the PA problem. Then, based on the optimal PA solution, the CA problem reduces to an assignment problem, which can be solved by Khun–Munkers algorithm. Further, we propose a sub-optimal solution by solving the original RA problem in the reverse order, i.e., first assigning the channel and then allocating the power. The simulation results show the effectiveness of the proposed algorithms and provide important insights on the solution design parameters such as the proximity distance and the self-interference cancellation capability.