Resource allocation for device-to-device and small cell uplink communication networks

This paper investigates the joint power control and subchannel allocation problem for device-to-device (D2D) and small cell uplink communications in a cellular network to improve the cellular throughput. For this considered throughput maximization problem, we propose to solve it leveraging a game-theoretic learning approach. However, there is an intractable issue for obtaining the optimal power allocation profile in the continuous space. To this end, we first deduce the optimal power expressions under any given subchannel allocations. Based on the optimal power profile, we then formulate the subchannel allocation problem into a game framework. Next, aiming to this optimization problem, a cloud-assisted learning algorithm with conditioned strategies is proposed to converge to an equilibrium point which maximizes the optimization objective. Finally, numerical results verify the effectiveness of the proposed scheme.