Joint Network Optimization in Cooperative Transmission Networks with Imperfect CSI

This paper investigates the power efficiency in downlink cooperative networks under spherical channel uncertainties, using a worst-case robust formulation. The aim of this paper is to jointly optimize the base station (BS) operation mode, mobile user (MU) association, and beamformings to achieve the robust network power gain. We formulate the problem as a mixed-integer non-convex problem with infinite number signal-to-interference-plus-noise ratio (SINR) and maximum transmit power constraints, which is nontrivial to solve even without this constraint. By firstly translating the uncertainty in CSI to the uncertainty in its covariance matrix, the SINR constraint spans a convex set using the Lagrangian based method. Due to the coupled integer variables, the complexity of exhaustive search grows exponentially with network size, motivating to develop low-complexity heuristic algorithms. We propose to solve the problem via a novel two-layer (TL) algorithm: inner and outer layer, successively. Specifically, the BS operation mode is determined successively in the outer layer using a Rank based Successive Search (RSS) method, while in the inner layer, an iterative Difference of Convex (DC) based algorithm is proposed to determine the MU association. Simulation results illustrate that the proposed algorithm can significantly reduce the total power consumption over existing alternatives.