Worst-Case Robust Sum Rate Maximization for Full-Duplex Bi-Directional MIMO Systems Under Channel Knowledge Uncertainty


O. Taghizadeh, R. Mathar,


        In this paper we address a worst-case weighted sum rate maximization problem for a full-duplex (FD) and point-to-point (P2P) system. The effects of channel-state information (CSI) error, as well as the signal distortion due to hardware impairments are jointly taken into account. Due to the intractable structure of the resulting problem, a weighted minimum mean squared error (WMMSE) method is applied to cast the rate maximization into a separately convex optimization problem, which can be iteratively solved with a guaranteed convergence. The provided rate maximization framework is also shown to provide a converging minimum mean squared error (MMSE) design as a special case. Moreover, a methodology to obtain the least favorable error matrices is proposed by casting the resulting non-convex quadratic optimization into a convex problem. The achievable guaranteed (worst-case) rate is then numerically studied, over different levels of CSI error intensity, transceiver accuracy, and available transmit power.

BibTEX Reference Entry 

	author = {Omid Taghizadeh and Rudolf Mathar},
	title = "Worst-Case Robust Sum Rate Maximization for Full-Duplex Bi-Directional {MIMO} Systems Under Channel Knowledge Uncertainty",
	pages = "5255-5261",
	booktitle = "{IEEE} {ICC} 2017 Signal Processing for Communications Symposium ({ICC}'17 SPC)",
	address = {Paris, France},
	month = May,
	year = 2017,
	hsb = RWTH-2017-05804,


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