Ali Cagatay Cirik

A Method for Broadband Full-Duplex MIMO Radio

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 50 dB SIC over a bandwidth of 30 MHz.

Achievable Rates of Full-Duplex MIMO Radios in Fast Fading Channels With Imperfect Channel Estimation

We study the theoretical performance of two full-duplex multiple-input multiple-output (MIMO) radio systems: a full-duplex bi-directional communication system and a full-duplex 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 nonconvex 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.

Weighted Sum-Rate Maximization for Full-Duplex MIMO Interference Channels

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-mean-squared-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 half-duplex (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.

Radio self-interference cancellation by transmit beamforming, all-analog cancellation and blind digital tuning

Radio self-interference cancellation has been a technological challenge for more than a century while it is the most critical enabler for full-duplex radios. The eventual success of radio self-interference cancellation may well depend on not only improved hardware technology but also innovative signal processing schemes. In this paper, we present a few latest discoveries on such schemes. The first is an improvement of time-domain transmit beamforming with robustness against the IQ imbalances in radio circuits, which is supported by both simulation and hardware experimental results. A key innovation here is due to the use of real-valued linear model instead of complex-valued linear (or widely linear) model. The second is a numerical investigation of the performance limits of an all-analog cancellation channel based on clustered-taps of attenuators when the interference channel has a large number of random multipaths. The third is a blind digital tuning method which uses only the baseband waveforms to determine the values of the variable attenuators embedded in the all-analog cancellation channel. This method is robust against imperfections in the knowledge of the transfer function of any component in the system provided that a real-valued linearity property holds (except for the transmit chain). HighlightsTime-domain transmit beamforming robust against IQ imbalances.Advantage of real-valued linear model over complex-valued linear or widely-linear model.New architecture for all-analog cancellation.Blind digital tuning using the output of radio receiver chain.Hardware efficiency and robustness against transmitter noise and nonlinearity.

MSE-Based Transceiver Designs for Full-Duplex MIMO Cognitive Radios

We study two scenarios of full-duplex (FD) multiple-input-multiple-output cognitive radio networks: FD cognitive ad hoc networks and FD cognitive cellular networks. In FD cognitive ad hoc networks (also referred as interference channels), each pair of secondary users (SUs) operate in FD mode and communicate with each other within the service range of primary users (PUs). Each SU experiences not only self-interference but also interuser interference from all other SUs, and all SUs generate interference on PUs. We address two optimization problems: one is to minimize the sum of mean-squared errors (MSE) of all estimated symbols, and the other is to minimize the maximum per-SU MSE of estimated symbols, both of which are subject to power constraints at SUs and interference constraints projected to each PU. We show that these problems can be cast as a second-order cone programming, and joint design of transceiver matrices can be obtained through an iterative algorithm. Moreover, we show that the proposed algorithm is not only applicable to interference channels but also to FD cellular systems, in which a base station operating in FD mode simultaneously serves multiple uplink and downlink users, and it is shown to outperform HD scheme significantly.

Weighted-Sum-Rate maximization for bi-directional full-duplex MIMO systems

We consider a full-duplex bi-directional communication system between two nodes that suffer from self-interference, where the nodes are equipped with multiple antennas and instantaneous channel state information (CSI) at the nodes is imperfect. We focus on the effect of the residual self-interference due to channel estimation errors and limited dynamic ranges of the transmitters and receivers. We consider the transmit filter design for Weighted Sum-Rate (WSR) maximization problem subject to total power constraint of the full-duplex system. Based on the relationship between WSR and Weighted Minimum Mean Square Error (WMMSE) problems for bi-directional full-duplex systems, we propose a low complexity alternating algorithm which converges to a local WSR optimum point. This algorithm exploits both spatial and temporal freedoms of the source co-variance matrices of the multiple-input multiple-output (MIMO) links between the nodes to achieve higher WSR.

Joint Subcarrier and Power Allocation for Sum-Rate Maximization in OFDMA Full-Duplex Systems

In this paper, we focus on the joint subcarrier and power allocation for an orthogonal frequency division multiple access (OFDMA) full-duplex (FD) system with the goal of maximizing the sum-rate subject to power constraints at the base station (BS) and uplink users, and subcarrier constraints. A greedy subcarrier allocation algorithm based on the necessary conditions of the optimization problem and a power allocation algorithm based on the iterative water-filling (IWF) are proposed. A hybrid scheduler that can switch between FD, half-duplex (HD) uplink and HD downlink mode at each time-slot to maximize the sum-rate is presented. Simulation results reveal that the proposed hybrid scheduling switches to FD scheduling at high self-interference cancellation values, and to HD-time-division- duplexing (TDD) scheduling at low self-interference cancellation values, and thus improves the sum-rate over the traditional HD-TDD scheduling.

MSE based transceiver designs for bi-directional full-duplex MIMO systems

We consider a multiple antenna full-duplex (FD) bi-directional (point-to-point) communication system with a limited analog domain self-interference cancellation capability. The effect of the residual self-interference resulting from independent and identically distributed (i.i.d.) channel estimation errors and limited dynamic ranges of the transmitters and receivers is studied in the digital domain. We design transceiver matrices based on the minimization of sum mean-squared error (MSE) and the maximum per-node MSE optimization problems subject to individual power constraints at each node through an iterative alternating algorithm, which is proven to converge to at least a local optimal solution.

A subcarrier and power allocation algorithm for OFDMA full-duplex systems

In this paper, we focus on subcarrier and power allocation for an orthogonal frequency division multiple access (OFDMA) full-duplex (FD) system. A three-step algorithm is proposed to maximize the sum-rate of the system subject to individual rate constraints at the uplink and downlink users, and transmit power constraints at the base station (BS) and uplink users. The steps are: 1) Subcarrier allocation that considers user target rate requirements, 2) residual subcarrier allocation that further increases the sum rate, and 3) power allocation based on iterative water-filling (IWF). Simulation results reveal that the proposed FD scheduling improves the sum-rate over the traditional half-duplex (HD) and round-robin (RR) scheduling significantly under the self-interference cancellation levels that has been recently achieved.

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

In this paper, we focus on a multi-user multi-cell scenario with full-duplex (FD) base-stations and half-duplex (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 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. In addition, 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.