Paper Info
Title
Robust Downlink Transmit Optimization Under Quantized Channel Feedback via the Strong Duality for QCQP
Abstract
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transmitter is imperfectly known mainly due to the channel direction quantization errors, channel estimation errors and outdated channel effects.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.
Year
DOI
Venue
2021
10.1109/LSP.2020.3037508
IEEE Signal Processing Letters
Keywords
DocType
Volume
Feedback path errors,frequency division duplexing system,quantized channel feedback,robust downlink beamforming,the strong duality of QCQP
Journal
28
ISSN
Citations 
PageRank 
1070-9908
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Xianming Li100.34
Yongwei Huang281450.83
Wing-Kin Ma311.02