Fronthaul compression and precoding design for MIMO full-duplex cognitive radio networks

Abstract

In this work, joint design of fronthaul compression and precoding in cloud radio access networks (C-RANs) is studied for full-duplex (FD) multiple-input multiple-output (MIMO) underlay cognitive radio networks. In this system, multiple secondary uplink (UL) and downlink (DL) users equipped with multiple antennas communicate with a control unit (CU) in the “cloud” through a set of multi-antenna secondary FD radio units (RU) which are connected to the CU through limited capacity links. We address the sum-rate maximization problem subject to UL and DL fronthaul rate constraints at each RU, power constraints at each RU and UL users, and maximum allowed interference at the primary users. Casting this non-convex problem as a difference of convex (DC) problem, an iterative algorithm based on the Majorization Minimization (MM) approach that guarantees convergence to a stationary point is proposed. Numerical results demonstrate the advantage of the proposed algorithm.