Robust Transceiver Design for IRS-Assisted Cascaded MIMO Systems

{Robust transceiver design against unresolvable system uncertainties is of crucial importance for reliable communication. We consider a MIMO multi-hop system, where the source, the relay, and the destination are equipped with multiple antennas. Further, an intelligent reconfigurable surface (IRS) is established to cancel the RSI as much as possible. The considered decode-and-forward (DF) hybrid relay can operate in either half-duplex or full-duplex mode, and the mode changes adaptively depending on the RSI strength. We investigate a robust transceiver design problem, which maximizes the throughput rate corresponding to the worst-case RSI under a self-interference channel uncertainty bound constraint. To the best of our knowledge, this is the first work that uses the IRS for RSI cancellation in MIMO full-duplex DF relay systems. The yielded problem turns out to be a non-convex optimization problem, where the non-convex objective is optimized over the cone of semidefinite matrices. We propose a closed-from lower bound for the IRS worst case RSI cancellation. Eventually, we show an important result that, for the worst case scenario, IRS can be helpful only if the number of IRS elements are at least as large as the size of the interference channel. Moreover, a novel method based on majorization theory is proposed to find the best response of the transmitters and relay against worst case RSI. Furthermore, we propose a multi-level water-filling algorithm to obtain a locally optimal solution iteratively. Finally, we obtain insights on the optimal antenna allocation at the relay input-frontend and output-frontend, for relay reception and transmission, respectively.Comment: arXiv admin note: substantial text overlap with arXiv:1912.1283

Aperture-Level Simultaneous Transmit and Receive (STAR) with Digital Phased Arrays

In the signal processing community, it has long been assumed that transmitting and receiving useful signals at the same time in the same frequency band at the same physical location was impossible. A number of insights in antenna design, analog hardware, and digital signal processing have allowed researchers to achieve simultaneous transmit and receive (STAR) capability, sometimes also referred to as in-band full-duplex (IBFD). All STAR systems must mitigate the interference in the receive channel caused by the signals emitted by the system. This poses a significant challenge because of the immense disparity in the power of the transmitted and received signals. As an analogy, imagine a person that wanted to be able to hear a whisper from across the room while screaming at the top of their lungs. The sound of their own voice would completely drown out the whisper. Approaches to increasing the isolation between the transmit and receive channels of a system attempt to successively reduce the magnitude of the transmitted interference at various points in the received signal processing chain. Many researchers believe that STAR cannot be achieved practically without some combination of modified antennas, analog self-interference cancellation hardware, digital adaptive beamforming, and digital self-interference cancellation. The aperture-level simultaneous transmit and receive (ALSTAR) paradigm confronts that assumption by creating isolation between transmit and receive subarrays in a phased array using only digital adaptive transmit and receive beamforming and digital self-interference cancellation. This dissertation explores the boundaries of performance for the ALSTAR architecture both in terms of isolation and in terms of spatial imaging resolution. It also makes significant strides towards practical ALSTAR implementation by determining the performance capabilities and computational costs of an adaptive beamforming and self-interference cancellation implementation inspired by the mathematical structure of the isolation performance limits and designed for real-time operation