| Abstract: | In this paper, the downlink of cell-free massive multiple-input multiple-output (MIMO) with zero-forcing processing is considered. To maximize the system energy efficiency (EE), we design power allocation algorithms taking into account imperfect channel state information, hardware, and backhaul power consumption. The total EE optimization problem is nonconvex, which traditionally is solved by the successive convex approximation framework which involves second order cone programs (SOCPs). As such methods have high complexity, the run time is extremely long, especially in large-scale systems with thousands of access points (APs) and users. To overcome this problem, in this paper, we propose to apply two computationally efficient methods, namely proximal gradient (PG) method and accelerated proximal gradient (APG) method to solve the considered problem. Numerical results show that, compared to the conventional SOCPs approximation methods, our proposed methods achieve the same performance while the run time is much smaller. |
