Rate Balancing in Full-Duplex MIMO Two-Way Relay Networks

Maximizing the minimum rate for a full-duplex multiple-input multiple-output (MIMO) wireless network encompassing two sources and a two-way (TW) relay operating in a two hop manner is investigated. To improve the overall performance, using a zero-forcing approach at the relay to suppress the residual self-interference arising from full-duplex (FD) operation, the underlying max-min problem is cast as an optimization problem which is non-convex. To circumvent this issue, semidefinite relaxation technique is employed, leading to upper and lower bound solutions for the optimization problem. Numerical results verify that the upper and lower bound solutions closely follow each other, showing that the proposed approach results in a close-to-optimal solution. In addition, the impact of residual self-interference upon the overall performance of the network in terms of the minimum rate is illustrated by numerical results, and for low residual self-interference scenarios the superiority of the proposed method compared to an analogous half-duplex (HD) counterpart is shown

Transceiver design for non-regenerative MIMO relay systems with decision feedback detection

In this paper we consider the design of zero forcing (ZF) and minimum mean square error (MMSE) transceivers for non-regenerative multiple input multiple output (MIMO) relay networks. Our designs utilise linear processors at each stage of the network along with a decision feedback detection device at the receiver. Under the assumption of full channel state information (CSI) across the entire link the processors are jointly optimised to minimise the system arithmetic mean square error (MSE) whilst meeting average power constraints at both the source and the relay terminals. We compare the presented methods to linear designs available in the literature and show the advantages of the proposed transceivers through simulation results

Hybrid Transceiver Optimization for Multi-Hop Communications

Multi-hop communication with the aid of large-scale antenna arrays will play a vital role in future emergence communication systems. In this paper, we investigate amplify-and-forward based and multiple-input multiple-output assisted multi-hop communication, in which all nodes employ hybrid transceivers. Moreover, channel errors are taken into account in our hybrid transceiver design. Based on the matrix-monotonic optimization framework, the optimal structures of the robust hybrid transceivers are derived. By utilizing these optimal structures, the optimizations of analog transceivers and digital transceivers can be separated without loss of optimality. This fact greatly simplifies the joint optimization of analog and digital transceivers. Since the optimization of analog transceivers under unit-modulus constraints is non-convex, a projection type algorithm is proposed for analog transceiver optimization to overcome this difficulty. Based on the derived analog transceivers, the optimal digital transceivers can then be derived using matrix-monotonic optimization. Numeral results obtained demonstrate the performance advantages of the proposed hybrid transceiver designs over other existing solutions.Comment: 32 pages, 6 figures. This manuscript has been submitted to IEEE Journal on Selected Areas in Communications (special issue on Multiple Antenna Technologies for Beyond 5G

Advanced DSP Algorithms For Modern Wireless Communication Transceivers

A higher network throughput, a minimized delay and reliable communications are some of many goals that wireless communication standards, such as the fifthgeneration (5G) standard and beyond, intend to guarantee for its customers. Hence, many key innovations are currently being proposed and investigated by researchers in the academic and industry circles to fulfill these goals. This dissertation investigates some of the proposed techniques that aim at increasing the spectral efficiency, enhancing the energy efficiency, and enabling low latency wireless communications systems. The contributions lay in the evaluation of the performance of several proposed receiver architectures as well as proposing novel digital signal processing (DSP) algorithms to enhance the performance of radio transceivers. Particularly, the effects of several radio frequency (RF) impairments on the functionality of a new class of wireless transceivers, the full-duplex transceivers, are thoroughly investigated. These transceivers are then designed to operate in a relaying scenario, where relay selection and beamforming are applied in a relaying network to increase its spectral efficiency. The dissertation then investigates the use of greedy algorithms in recovering orthogonal frequency division multiplexing (OFDM) signals by using sparse equalizers, which carry out the equalization in a more efficient manner when the low-complexity single tap OFDM equalizer can no longer recover the received signal due to severe interferences. The proposed sparse equalizers are shown to perform close to conventional optimal and dense equalizers when the OFDM signals are impaired by interferences caused by the insertion of an insufficient cyclic prefix and RF impairments

Hardware Impairments Aware Transceiver Design for Full-Duplex Amplify-and-Forward MIMO Relaying

In this work we study the behavior of a full-duplex (FD) and amplify-and-forward (AF) relay with multiple antennas, where hardware impairments of the FD relay transceiver is taken into account. Due to the inter-dependency of the transmit relay power on each antenna and the residual self-interference in an FD-AF relay, we observe a distortion loop that degrades the system performance when the relay dynamic range is not high. In this regard, we analyze the relay function in presence of the hardware inaccuracies 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. It is observed that compared to GP, (Alt)MuStR1 algorithms significantly reduce the required computational complexity at the expense of a slight performance degradation. Finally, the proposed methods are evaluated under various system conditions, and compared with the methods available in the current literature. In particular, it is observed that as the hardware impairments increase, or for a system with a high transmit power, the impact of applying a distortion-aware design is significant.Comment: Submitted to IEEE Transactions on Wireless Communication