User Selection and Power Minimization in Full-Duplex Cloud Radio Access Networks

Abstract

In this paper, we investigate the network power consumption (NPC) minimization in full-duplex cloud radio access networks (C-RANs) with quality-of-service requirements. We jointly optimize the beamforming vectors, the users' transmit power, the fronthaul compression ratio, and the set of transmitting remote radio heads (RRHs). Users' requirements of signal-to-interference-and-noise ratio, per-RRH and user power constraints, and fronthaul capacity constraints are considered. Due to these conflicting constraints, the optimization problem may be infeasible. Thus, we solve this problem in two steps. In Step I, a minimum-mean-square-error-based user selection algorithm is proposed to find the largest subset of feasible users. In Step II, an algorithm based on the reweighted l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -norm minimization method is proposed to solve the NPC problem with the users selected in Step I. The solutions obtained by the proposed algorithms are proved to monotonically converge and satisfy the Karush-Kuhn-Tucker conditions. Moreover, our proposed algorithms are applicable to both full-duplex and half-duplex C-RANs. We comprehensively compare these two types of C-RANs and propose some valuable insights for system design.