Distributed Resource Allocation in Underlay Multicast D2D Communications

Multicast device-to-device communications operating underlay with cellular networks is a spectral efficient technique for disseminating data to nearby receivers. However, due to the critical challenge of having an intelligent interference coordination between multicast groups along with the cellular network, it is necessary to judiciously perform resource allocation for the combined network. In this work, we present a framework for a joint channel and power allocation strategy to maximize the sum rate of the combined network while guaranteeing minimum rate to individual groups and cellular users. The objective function is augmented by an austerity function that penalizes excessive assignment of low rate channels. The formulated problem is a mixed-integer-non-convex program, which requires exponential complexity to obtain the optimal solution. To tackle this, we exploit fractional programming and integer relaxation to obtain a parametric convex approximation. Based on sequential convex approximation approach, we first propose a centralized algorithm that ensures convergence to a limit point. Next, we propose a distributed algorithm in which via dual decomposition, separable sub-problems are formulated to be solved at the respective groups in cooperation with the base station. We provide convergence guarantees of the proposed solutions and demonstrate their merits by simulations, showing improvement in network throughput.