We consider a K link multiple-input multiple-output (MIMO) interference channel, where each link consists of two full-duplex (FD) nodes exchanging information simultaneously in a bi-directional communication fashion. The nodes in each pair suffer from self-interference due to operating in FD mode, and inter-user interference from other links due to simultaneous transmission at each link. We consider the transmit and receive filter design for Weighted Sum-Rate (WSR) maximization problem subject to sum-power constraint of the system or individual power constraints at each node of the system. Based on the relationship between WSR and Weighted Minimum-MeanSquared-Error (WMMSE) problems for FD MIMO interference channels, we propose a low complexity alternating algorithm which converges to a local WSR optimum point. Moreover, we show that the proposed algorithm is not only applicable to FD MIMO interference channels, but also applicable to FD cellular systems, in which a base station (BS) operating in FD mode serves multiple uplink (UL) and downlink (DL) users operating in halfduplex (HD) mode, simultaneously. It is shown in simulations that the sum-rate achieved by FD mode is higher than the sum-rate achieved by baseline HD schemes.

We present a time-domain transmit beamforming (TDTB) method for self-interference cancelation (SIC) at the radio frequency (RF) frontend of the receivers on broadband full-duplex MIMO radios. It is shown that the conventional frequency-domain transmit beamforming (FDTB) method along with the orthogonal frequency division multiplexing (OFDM) framework does not generally perform SIC in the prefix region of a transmitted frame. A hardware based test of the TDTB method shows a 50dB SIC over a bandwidth of 30MHz.

In this paper we focus on a multiuser 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.

In this work we consider a full-duplex (FD) and amplify-and-forward (AF) relay with multiple antennas, where hardware impairments of the FD relay are taken into account. Due to the inter-dependency of the transmit relay power and the residual self-interference in an AF-FD relay, we observe a distortion loop that degrades the system performance when relay dynamic range is not high. In this regard, we analyze the relay function, and an optimization problem is formulated to maximize the signal to distortion-plus-noise ratio (SDNR) under relay and source transmit power constraints. Due to the problem complexity, we propose a gradient-projection-based (GP) algorithm to obtain an optimal solution. Moreover, a nonalternating sub-optimal solution is proposed by assuming a rank-1 relay amplification matrix, and separating the design of the relay process into multiple stages (MuStR1). The proposed MuStR1 method is then enhanced by introducing an alternating update over the optimization variables, denoted as AltMuStR1 algorithm. Numerical simulations show that compared to GP, the proposed (Alt)MuStR1 algorithms significantly reduce the required computational complexity at the expense of a slight performance degradation. Moreover, as the hardware impairments increase, or for a system with a high transmit power, the impact of applying a distortion-aware design is significant.

We study the theoretical performance of two fullduplex multiple-input multiple-output (MIMO) radio systems: a full-duplex bi-directional communication system and a fullduplex relay system. We focus on the effect of a (digitally manageable) residual self-interference due to imperfect channel estimation (with independent and identically distributed (i.i.d.) Gaussian channel estimation error) and transmitter noise. We assume that the instantaneous channel state information (CSI) is not available the transmitters. To maximize the system ergodic mutual information, which is a non-convex function of power allocation vectors at the nodes, a gradient projection algorithm is developed to optimize the power allocation vectors. This algorithm exploits both spatial and temporal freedoms of the source covariance matrices of the MIMO links between transmitters and receivers to achieve higher sum ergodic mutual information. It is observed through simulations that the full-duplex mode is optimal when the nominal self-interference is low, and the half-duplex mode is optimal when the nominal self-interference is high. In addition to an exact closed-form ergodic mutual information expression, we introduce a much simpler asymptotic closed-form ergodic mutual information expression, which in turn simplifies the computation of the power allocation vectors. Index Terms-Full-duplex MIMO radio, bi-directional communication, full-duplex relays, fast fading channels. I. INTRODUCTION T His paper concerns radio frequency (RF) wireless communication systems or simply called radios. A radio can be used as a wireless relay between two other radios, which we call a relay system. Two radios can be used to communicate directly with each other, which we call a bi-directional system. Wireless relays have attracted a great deal of attention for next generations of wireless communication systems as relays can reduce the overall path loss and transmission power consumption and they also can increase cell coverage and capacity. A conventional wireless relay is half-duplex, which

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In this paper we address the linear precoding and decoding design problem for a bidirectional orthogonal frequencydivision multiplexing (OFDM) communication system, between two multiple-input multiple-output (MIMO) full-duplex (FD) nodes. The effects of hardware distortion as well as the channel state information error are taken into account. In the first step, we transform the available time-domain characterization of the hardware distortions for FD MIMO transceivers to the frequency domain, via a linear Fourier transformation. As a result, the explicit impact of hardware inaccuracies on the residual selfinterference (RSI) and inter-carrier leakage (ICL) is formulated in relation to the intended transmit/received signals. Afterwards, linear precoding and decoding designs are proposed to enhance the system performance following the minimum-mean-squarederror (MMSE) and sum rate maximization strategies, assuming the availability of perfect or erroneous CSI. The proposed designs are based on the application of alternating optimization over the system parameters, leading to a necessary convergence.Numerical results indicate that the application of a distortionaware design is essential for a system with a high hardware distortion, or for a system with a low thermal noise variance.

We consider a K link multiple-input multiple-output (MIMO) interference channel where each link consists of two full-duplex (FD) nodes. Two transmit beamforming design problems are solved, i) sum-power minimization problem subject to rate constraints, and ii) energy-efficiency maximization problem subject to individual power constraints. To tackle the sumpower minimization problem, we first generalize the well-known relationship between weighted-sum-rate (WSR) and weighted minimum-mean-squared-error (WMMSE) problems, originally used to solve the sum-rate maximization problems, and then propose a low complexity centralized algorithm which converges to a stationary point. To decrease the exchange of a huge amount of data and excessive signaling traffic among the nodes, a distributed algorithm is also proposed. For the energy-efficiency maximization problem, the original fractional form optimization problem is first transformed into an equivalent subtractiveform optimization problem by exploiting the properties of fractional programming, and then perform a dual-layer optimization scheme. In the outer layer, the energy-efficiency parameter is searched using a simple one-dimensional search, and in the inner layer, the relationship between WSR and WMMSE is exploited to solve the subtractive form optimization problem. Since the proposed algorithms require perfect channel-state-information (CSI), which is difficult to acquire in practice, we also propose a robust design, by taking the imperfect channel knowledge into consideration. It is shown in the simulations that the sum-power achieved in FD mode depends heavily on the transmitter/receiver distortion. Also the energy-efficiency of FD systems is lower than that of half-duplex (HD) systems, as FD nodes need to overcome self-interference and increased inter-user interference which leads to high power consumption.