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In this paper, a new optimization framework is presented for the joint designof user selection, power allocation, and precoding in multi-cell multi-usermultiple-input multiple-output (MU-MIMO) systems when imperfect channel stateinformation at transmitter (CSIT) is available. By representing the jointoptimization variables in a higher-dimensional space, the weighted sum-spectralefficiency maximization is formulated as the maximization of the product ofRayleigh quotients. Although this is still a non-convex problem, acomputationally efficient algorithm, referred to as generalized power iterationprecoding (GPIP), is proposed. The algorithm converges to a stationary point(local maximum) of the objective function and therefore it guarantees thefirst-order optimality of the solution. By adjusting the weights in theweighted sum-spectral efficiency, the GPIP yields a joint solution for userselection, power allocation, and downlink precoding. The GPIP is also extendedto a multi-cell scenario, where cooperative base stations perform joint userselection and design their precoding vectors by sharing global yet imperfectCSIT within the cooperative BSs. System-level simulations show the gains of theproposed approach with respect to conventional user selection and lineardownlink precoding.

Joint User Selection, Power Allocation, and Precoding Design with Imperfect CSIT for Multi-Cell MU-MIMO Downlink Systems