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Max-Min Fairness Design for MIMO Interference Channels: A Minorization-Maximization Approach
Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan 8415683111, Iran.
Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan 8415683111, Iran.
Isfahan Univ Technol, Dept Elect & Comp Engn, Esfahan 8415683111, Iran.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control.ORCID iD: 0000-0002-7957-3711
2019 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, no 18, p. 4707-4719Article in journal (Refereed) Published
Abstract [en]

We address the problem of linear precoder (beam-former) design in a multiple-input multiple-output interference channel. The aim is to design the transmit covariance matrices in order to achieve max-min utility fairness for all users. The corresponding optimization problem is non-convex and NP-hard in general. We devise an efficient algorithm based on the minorization-maximization technique to obtain quality solutions to this problem. The proposed method solves a second-order cone convex program at each iteration. We prove that the devised method converges to stationary points of the problem. We also extend our algorithm to the case where there are uncertainties in the noise covariance matrices or channel state information. Simulation results show the effectiveness of the proposed method compared with its main competitor.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2019. Vol. 67, no 18, p. 4707-4719
Keywords [en]
Interference channel, minorization-maximization (MM), max-min fairness, MIMO, rate optimization
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-393640DOI: 10.1109/TSP.2019.2929470ISI: 000481476200003OAI: oai:DiVA.org:uu-393640DiVA, id: diva2:1354818
Funder
Swedish Research CouncilAvailable from: 2019-09-26 Created: 2019-09-26 Last updated: 2019-09-26Bibliographically approved

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