Weighted Sum Rate Maximization in Full-Duplex Multi-User Multi-Cell MIMO Networks

Paula Aquilina, Ali Cagatay Cirik, Tharmalingam Ratnarajah

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we focus on a multi-user multi-cell scenario with full-duplex (FD) base-stations (BSs) and halfduplex (HD) downlink (DL) and uplink (UL) users, where all nodes are equipped with multiple antennas. Our goal is to design filters for weighted sum rate (WSR) maximization whilst taking into consideration the effect of transmitter and receiver distortion. Since WSR problems are non-convex we exploit the relationship between rate and mean squared error (MSE) in order to propose low complexity alternating optimization algorithms which are guaranteed to converge. While the initial design assumes perfect channel state information (CSI), we also move beyond this assumption and consider WSR problems under imperfect CSI. This is done using two types of error models; the first is a norm-bounded error model, suitable for cases where the CSI error is dominated by quantization issues, and the second is a stochastic error model, suitable for errors that occur during the channel estimation process itself. Results show that rates achieved in FD mode are higher than those achieved by the baseline HD schemes and demonstrate the robust performance of the proposed imperfect CSI designs. Additionally we also extend our original WSR problem to one which maximizes the total DL rate subject to each UL user achieving a desired target rate. This latter design can be used to overcome potential unfairness issues and ensure that all UL users are equally served in every time slot.
Original languageEnglish
JournalIEEE Transactions on Communications
Early online date16 Jan 2017
DOIs
Publication statusE-pub ahead of print - 16 Jan 2017

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