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Multiple-user (MU) multiple-input multiple-output (MIMO) technology, which involves using multiple antennas to simultaneously serve multiple users or devices, is a cornerstone of both 5G and 6G. The use of MIMO in ultra-dense networks with smaller cell sizes and more antennas will result in a proportional increase in both inter- and intra-cell interference. To manage the interference, precoding or beamforming is needed to steer the transmit signals towards intended users and mitigate interference. Symbol level precoding (SLP) techniques exploit information about the symbols to be transmitted in addition to the channel state information (CSI), which can significantly improve performance at the expense of increased complexity at the transmitter. The additional degrees of freedom (DoF) provided by the symbol-level information make it possible to exploit the constructive component of the interference, converting it into constructive interference (CI) that can move the received signals further from the decision thresholds of the constellation points. CI-based SLP recasts the traditional viewpoint of interference as a source of degradation to one where interference is a potential resource that can be exploited. In this dissertation, we firstly study the use of SLP in the downlink of a multiuser multiple-input-single-output (MU-MISO) cognitive radio (CR) network, where a primary base station (PBS) serving primary users (PUs) and a cognitive base station (CBS) serving cognitive users (CUs) share the same frequency band. The SLP approach is designed using the symbol-wise Maximum Safety Margin (MSM) criterion, which exploits the constructive multiuser interference present in such a network. We adapt the non-linear MSM precoder to both underlay and overlay CR scenarios, depending on whether or not the primary system shares its information with the cognitive system. Secondly, we investigate robust SLP designs in an overlay CR network, where the primary and secondary networks transmit signals concurrently, however, the PBS shares imperfect CSI with the CBS. We propose robust SLP schemes in this scenario and consider two different CSI error models. For the norm-bounded CSI error model, we adopt a max-min philosophy to conservatively achieve robust SLP constraints; for the additive quantization noise model (AQNM), we employ a stochastic constraint to formulate the problem. Simulation results show that, rather than simply trying to eliminate the network's cross-interference, the proposed robust SLP schemes enable the primary and secondary networks to aid each other in meeting their quality of service constraints. Moreover, we propose precoding design in multi-antenna systems with improper Gaussian interference (IGI), characterized by correlated real and imaginary parts. We first study block level precoding (BLP) and SLP assuming the receivers apply a pre-whitening filter to decorrelate and normalize the IGI. We then shift to the scenario where the base station (BS) incorporates the IGI statistics in the SLP design, which allows the receivers to employ a standard detection algorithm without pre-whitenting. Finally we address the case where the non-circularity of the IGI is unknown, and we formulate robust BLP and SLP designs that minimize the worst case performance in such settings. Interestingly, we show that for BLP, the worst-case IGI is in fact proper, while for SLP the worst case occurs when the interference signal is maximally improper, with fully correlated real and imaginary parts. The numerical results reveal the superior performance of SLP in terms of symbol error rate (SER) and energy efficiency (EE), especially for the case where there is uncertainty in the non-circularity of the jammer.

In Constant Envelope Symbol Level Precoding (CESLP), the transmitted signals by the antennas have constant amplitude regardless of the channel realization and the conveyed information symbols. Such solutions enable the use of power-efficient components, i.e. non-linear power amplifiers and thus, are suitable for systems based on large-scale antenna arrays. In the latter systems, the hardware complexity and power consumption can be limiting factors since each antenna element requires dedicated hardware components. These components include the Digital-to-Analog Converters (DACs) that have exponential complexity and power consumption with the number of the supported resolution. To that end, in this paper, a CESLP precoding technique is presented for Multi-User Multiple Input-Multiple Output (MU-MIMO) systems with low resolution DACs. The case of a multi-carrier system employing the well-known Orthogonal Frequency Division Multiplexing (OFDM) technique is considered. The precoding design problem is formulated as a mixed discrete-continuous least-squares optimization one which is NP-hard. An efficient low complexity solution is developed based on the Cyclic Coordinate Descent (CCD) optimization framework. Simulations show that the proposed solution is able to achieve very close performance to the one of the infinite resolution CESLP precoding counterpart even though, it is based on DACs that have resolution of only a few bits.

Large-scale antennas are crucial for next generation wireless communication systems as they improve spectral efficiency, reliability and coverage compared to the traditional ones that are employing antenna arrays of few elements. However, the large number of antenna elements leads to a big increase in power consumption of conventional fully digital transceivers due to the one Radio Frequency (RF) chain / per antenna element requirement. The RF chains include a number of different components among which are the Digital-to-Analog Converters (DACs)/Analog-to-Digital Converters (ADCs) that their power consumption increases exponential with the resolution they support. Motivated by this, in this thesis, a number of different architectures are proposed with the view to reduce the power consumption and the hardware complexity of the transceiver. In order to optimize the transmission of data through them, corresponding symbol level precoding (SLP) techniques were developed for the proposed architectures. SLP is a technique that mitigates multi-user interference (MUI) by designing the transmitted signals using the Channel State Information and the information-bearing symbols. The cases of both frequency flat and frequency selective channels were considered. First, three different power efficient transmitter designs for transmission over frequency flat channels and their respective SLP schemes are considered. The considered systems tackle the high hardware complexity and power consumption of existing SLP techniques by reducing or completely eliminating fully digital RF chains. The precoding design is formulated as a constrained least squares problem and efficient algorithmic solutions are developed via the Coordinate Descent method. Next, the case of frequency selective channels is considered. To this end, Constant Envelope precoding in a Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing system (CE MIMO-OFDM) is considered. In CE MIMO-OFDM the transmitted signals for each antenna are designed to have constant amplitude regardless of the channel realization and the information symbols that must be conveyed to the users. This facilitates the use of power-efficient components, such as phase shifters and non-linear power amplifiers. The precoding problem is firstly formulated as a least-squares problem with a unit-modulus constraint and solved using an algorithm based on the coordinate descent (CCD) optimization framework and then, after reformulating the problem into an unconstrained non-linear least squares problem, a more computationally efficient solution using the Gauss-Newton algorithm is presented. Then, CE MIMO-OFDM is considered for a system with low resolution DACs. The precoding design problem is formulated as a mixed discrete- continuous least-squares optimization one which is NP-hard. An efficient low complexity solution is developed based also on the CCD optimization framework. Finally, a precoding scheme is presented for OFDM transmission in MIMO systems based on one-bit DACs and ADCs at the transmitter’s and the receiver’s end, respectively, as a way to reduce the total power consumption. The objective of the precoding design is to mitigate the effects of one-bit quantization and the problem is formulated and then is split into two NP hard least squares optimization problems. Algorithmic solutions are developed for the solution of the latter problems, based on the CCD framework.