Ergodic mutual information of full-duplex MIMO radios with residual self-interference

We study the theoretical performance of a full duplex multiple-input multiple-output (MIMO) bi-directional communication system. We focus on the effect of the residual self-interference due to channel estimation errors and transmitter impairments. We assume that the instantaneous channel state information (CSI) at the transmitting nodes is not known and the CSI at the receiving nodes is imperfect. To maximize the system ergodic mutual information, which is a non-convex function of power allocation vectors at the nodes, a gradient projection (GP) 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 the nodes to achieve higher sum ergodic mutual information. It is observed through the simulations that the algorithm reduces to a full-duplex scheme when the nominal residual self-interference is low, or to a half-duplex scheme when the nominal residual self-interference is high

On uplink-downlink sum-MSE duality of multi-hop MIMO relay channel

In this paper, the uplink and downlink sum mean-squared error (MSE) duality for multi-hop amplify-and-forward (AF) multiple-input multiple-output relay channels is established, which is a generalization of several sum-MSE duality results. Unlike the previous results that prove the duality by calculatingthe MSEs for each stream directly, we introduce an interesting perspective to the relation of the uplink-downlink duality based on the Karush-Kuhn-Tucker (KKT) conditions. We address the transceiver design based on the minimization of sum-MSE subject to the power constraints at the relay and user nodes for both uplink and downlink channels. Based on the KKT conditions of the transceiver design optimization problems, the sum-MSE uplink-downlink duality is established

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

We consider a multiple antenna full-duplex (FD) bidirectional (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

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

Fairness Considerations in Full-Duplex MIMO Interference Channels

In this paper, we address the proportional fair (PF) issue of a K link full-duplex (FD) multiple-input multiple-output (MIMO) interference channel, where each link consists of two FD nodes exchanging information simultaneously. The nodes in each pair suffer from self-interference due to operating in FD mode, and inter-user interference from the nodes in other links due to simultaneous transmission from each link. The PF issue is important for networks with asymmetric topology and/or asymmetric traffic demands. We demonstrate that the proposed algorithm provides a good trade-off between sum achievable rate and rate distribution for asymmetric links, and moreover we show that the sum-rate achieved by FD mode is higher than the sum-rate achieved by baseline half-duplex (HD) schemes

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 thetraditional half-duplex (HD) and round-robin (RR) scheduling significantly under the self-interference cancellation levels that has been recently achieved

On MAC-BC Duality of Multihop MIMO Relay Channel with Imperfect Channel Knowledge

In this paper, we establish the signal-to-interference-noise ratio (SINR) duality between multipleaccess (MAC) and broadcast (BC) multihop amplify-and-forward (AF) multiple-input multiple-output(MIMO) relay systems under an imperfect channel state model, which is a generalization of severalpreviously established MAC-BC duality results. We show that identical SINRs in the MAC and BCsystems can be achieved by two approaches. The first one is to use the Hermitian transposed MACrelay amplifying matrices at the relay nodes in the BC system, under the same total network transmission power constraint. The second one is to use the scaled and Hermitian transposed MAC relay amplifying matrices in the BC system, under the transmission power constraint at each node of the system, where the scaling factors are obtained by swapping the power constraints of the nodes in the MAC system. Moreover, we derive the MAC-BC mean-squared error (MSE) and capacity duality properties based on the SINR duality. Numerical results show the utility of the duality results established