In this work we focus on a cellular network where a full-duplex (FD) base-station (BS) communicates with multiple half-duplex (HD) downlink (DL) and uplink (UL) users. The introduction of FD capability at the BS causes a surge in the amount of interference compared to the HD network counterpart. In particular a new type of co-channel interference arises between UL and DL data, since they are transmitted simultaneously. Here, we consider the use of linear interference alignment (IA) to manage interference in such networks, under the availability of imperfect channel state information (CSI). We design two novel IA algorithms, the first is based on maximizing the signal-to-interference-plus-noise ratio (Max-SINR) and the second minimizes the mean squared error (MMSE). Both algorithms, 1) take into effect statistical knowledge of the CSI error for added robustness, 2) follow specific design principles that distribute the different interference components amongst the various beamformers, and 3) result in unitary precoders and receivers. Additionally, we show that under certain conditions the proposed Max-SINR and MMSE designs obtain identical beamformers.

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.

In this paper, we consider a system where full-duplex (FD) base-stations (BSs) communicate with half-duplex (HD) downlink (DL) and uplink (UL) users in a multi-user multi-cell network, where all nodes are equipped with multiple antennas. The introduction of FD BSs offers potential to increase spectral efficiency, however, it also causes a surge in the number of interference links compared with the HD network counterpart. Here, we apply linear interference alignment (IA) to manage interference in this network under imperfect channel state information (CSI). First, we characterize the performance losses incurred with respect to the achievable sum rate and degrees of freedom (DoFs). Results show that the general trend in performance loss is mainly determined by how the error scales with the signal-to-noise ratio (SNR). In particular, full UL and DL DoF can be achieved even under imperfect CSI when the channel error is at least inversely proportional to SNR. Moreover, in such cases the sum rate loss is always finite, and either goes to zero or is upper bounded by a derived value. Second, we design two linear IA algorithms applicable to the system under consideration. These are based on minimizing the mean square error (MMSE) and maximizing the signal-to-interference-plus-noise ratio, and consider statistical knowledge of the CSI error for added robustness. The proposed algorithms follow specific design principles that distribute the different interference components amongst the various beamformers and result in unitary receivers and precoders. In addition, we show that under certain conditions both designs result in identical beamforming solutions, even though the MMSE algorithm has lower computational complexity. Finally, we also derive the proper condition for IA feasibility in the multi-cell system under consideration.

Topological interference management is the study of achievable rates within communication networks with no channel state information at the transmitter (CSIT) beyond knowledge of the network structure itself. In this work, we study the degrees of freedom (DoF) of a two-cell two-user-per-cell interference broadcast channel (IBC) with alternating connectivity and global topological interference management. The topological information allows transmitters to track the changing network topology and exploit the varying connectivity states to achieve a DoF gain. We derive novel DoF outer bounds for the two-cell two-user-per-cell IBC with alternating connectivity. This analysis is carried out for different system configurations, namely, single-input single-output (SISO), multiple-input single-output (MISO), and multiple-input multiple-output (MIMO) systems. While global channel knowledge is always restricted to topological information only, we introduce a mixed CSIT setting where varying degrees of local CSIT availability are considered depending on the system configuration. Additionally, we investigate the achievability of the derived bounds and propose new transmission schemes based on joint coding across states. Results show that DoF higher than those conventionally obtained without global topological information are achievable, indicating that even such a minimal level of global CSIT is still highly useful.

Topological interference management refers to the study of achievable rates within communication networks with no channel state information at the transmitter (CSIT) beyond knowledge of the network structure itself. In this work we consider the topological interference management problem within the context of a two cell two user interference broadcast channel (IBC) with alternating connectivity. Topological information, even though minimal, allows the transmitters to track the changing network structure and then exploit the varying connectivity states to obtain a degrees of freedom (DoF) gain. Thus, the main result of this work is the derivation of a novel outer bound on the DoF achievable by the two cell two user IBC in an alternating connectivity scenario. Additionally, we propose a scheme based on joint coding across states that achieves this outer bound for the case where all alternating connectivity states are equiprobable.

Topological interference management is the study of achievable rates within communication networks with no channel state information at the transmitter (CSIT) beyond knowledge of the network structure itself. In this paper, we consider topological interference management within the context of a two-cell two-user-per-cell interference broadcast channel (IBC) with alternating connectivity. Topological feedback, even though minimal, allows the transmitters to track the changing network topology and then exploit the varying connectivity states to obtain a degrees of freedom (DoF) gain. We derive novel outer bounds on the DoF achievable by the two-cell two-user-per-cell IBC with alternating connectivity. The analysis initially focuses on the single-input single-output (SISO) case and is later extended to multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) systems. While global channel knowledge is restricted to topological information only, varying degrees of local CSIT availability are considered, depending on the network configuration. Additionally, we investigate the achievability of the derived bounds and for the case where all alternating connectivity states are equiprobable propose new transmission schemes based on joint coding across states.

In this work we consider the multiple-input multiple-output (MIMO) interference broadcast channel (IBC) and analyse the performance of interference alignment (IA) under imperfect channel state information (CSI), where the variance of the CSI error depends on the signal-to-noise ratio (SNR). First, we derive an upper bound on asymptotic mean loss in sum rate compared to the perfect CSI case and then we quantify the achievable degrees of freedom (DoF) with imperfect CSI. Both sum rate loss and achievable DoF are found to be dependent on the number of cells in the system and the amount of users per cell, in addition to the CSI error parameters themselves. Results show that when error variance is inversely proportional to SNR, full DoF are achievable and the asymptotic sum rate loss is bounded by a derived value. Additionally if the CSI imperfection does not disappear for asymptotically high SNR, then the full DoF gain promised by IA cannot be achieved; we quantify this loss in relation to the CSI mismatch itself. The analytically derived bounds are validated via system simulation, with the cellular counterparts of the maximum signal-to-interference-plus-noise ratio (Max-SINR) and the minimum weighted leakage interference (Min-WLI) algorithms being the IA techniques of choice. Secondly, inspired by the CSI mismatch model used to derive the bounds, we present a novel Max-SINR algorithm with stochastic CSI error knowledge (Max-SINR-SCEK) for the MIMO IBC. Simulations show that the proposed algorithm improves performance over the standard one under imperfect CSI conditions, without any additional computational costs.

In this work we investigate the degrees of freedom (DoF) performance of the multiple-input multiple-output (MIMO) interference channel (IC) with limited channel state information (CSI) feedback. We generalise two space-time interference alignment (STIA) algorithms to the K user MIMO IC with a transmit power constraint and show how these schemes exploit both current and outdated CSI to achieve an improved DoF performance. We show that by combining the STIA schemes with traditional methods major DoF gain can be achieved for a variety of limited CSI feedback scenarios in comparison to what would be obtained via the use of the traditional techniques on their own. In particular we prove that optimal DoF can still be achieved in situations where current CSI is unavailable for a derived fraction of the time. Finally we validate the promised DoF results via system simulation and show how these DoF gains reflect in terms of sum rate achievable.