Robust Downlink Transmit Optimization Under Quantized Channel Feedback via the Strong Duality for QCQP

Consider a robust multiple-input single-output downlink beamforming optimization problem in a frequency division duplexing system. The base station (BS) sends training signals to the users, and every user estimates the channel coefficients, quantizes the gain and the direction of the estimated channel and sends them back to the BS. Suppose that the channel state information at the transmitter is imperfectly known mainly due to the channel direction quantization errors, channel estimation errors and outdated channel effects. The actual channel is modeled as in an uncertainty set composed of two inequality homogeneous and one equality inhomogeneous quadratic constraints, in order to account for the aforementioned errors and effects. Then the transmit power minimization problem is formulated subject to robust signal-to-noise-plus-interference ratio constraints. Each robust constraint is transformed equivalently into a quadratic matrix inequality (QMI) constraint with respect to the beamforming vectors. The transformation is accomplished by an equivalent phase rotation process and the strong duality result for a quadratically constrained quadratic program. The minimization problem is accordingly turned into a QMI problem, and the problem is solved by a restricted linear matrix inequality relaxation with additional valid convex constraints. Simulation results are presented to demonstrate the performance of the proposed method, and show the efficiency of the restricted relaxation.

I. Introduction

In A MULTIUSER multiple-input single-out (MISO) downlink communication system, linear beamforming technique has played a vital role in improving spectrum efficiency and alleviating mutual interference (see e.g. [1]–[3] and references therein). Among many existing optimal beamforming designs, a quality-of-service (QoS) design problem is typically formulated such that the power consumed in the base station (BS) is minimized subject to signal-to-interference-plus-noise ratio (SINR) constraints at the receivers. In this design, the BS must be able to obtain the channel state information at the transmitter (CSIT) and determine the SINRs. However, the BS often has only estimated and imperfect CSIT and thus the SINRs are computed in an inaccurate way. To address the inexactness, the presence of uncertainties in these estimates has to be taken into account. A prominent approach is to design the beamforming vectors such that they are robust against the CSIT imperfectness (see e.g. [4] and references therein).