Energy Efficiency Optimization for Distributed Antenna Systems With D2D Communications Under Channel Uncertainty

In this paper, we investigate the energy efficiency (EE) maximization problem in distributed antenna systems (DAS) with underlaid device-to-device (D2D) communications. The EE optimization relies on the channel state information (CSI), and the interference from D2D pairs to the cellular user equipment (CUE) also closely depends on CSI. In this paper, we consider the case that the CSI in the systems is uncertain, which is more realistic and reasonable. We aim to obtain the robust power allocation (PA) solution that can achieve the maximum EE of the D2D systems. The optimization problem can be formulated as a non-convex and non-linear problem with infinite interference constraint. In order to solve it, the interference constraint is treated as chance constraint and handled by Bernstein approximation. Moreover, an equivalent objective function with a sub-tractive form is transformed by exploiting fractional programming theory. After that, the non-convex objective function can be transformed by using the difference of convex (D.C.) programming. The concave convex procedure (CCCP) algorithm is used to tackle the problem and obtain the optimal power allocation for D2D users. Simulation results show the robustness of the system and the effectiveness of the proposed algorithm.