A Spatial Sigma-Delta Approach to Mitigation of Power Amplifier Distortions in Massive MIMO Downlink

In massive multiple-input multiple-output (MIMO) downlink systems, the physical implementation of the base stations (BSs) requires the use of cheap and power-efficient power amplifiers (PAs) to avoid high hardware cost and high power consumption. However, such PAs usually have limited linear amplification ranges. Nonlinear distortions arising from operation beyond the linear amplification ranges can significantly degrade system performance. Existing approaches to handle the nonlinear distortions, such as digital predistortion (DPD), typically require accurate knowledge, or acquisition, of the PA transfer function. In this paper, we present a new concept for mitigation of the PA distortions. Assuming a uniform linear array (ULA) at the BS, the idea is to apply a Sigma-Delta ($\Sigma \Delta$) modulator to spatially shape the PA distortions to the high-angle region. By having the system operating in the low-angle region, the received signals are less affected by the PA distortions. To demonstrate the potential of this spatial $\Sigma \Delta$ approach, we study the application of our approach to the multi-user MIMO-orthogonal frequency division modulation (OFDM) downlink scenario. A symbol-level precoding (SLP) scheme and a zero-forcing (ZF) precoding scheme, with the new design requirement by the spatial $\Sigma \Delta$ approach being taken into account, are developed. Numerical simulations are performed to show the effectiveness of the developed $\Sigma \Delta$ precoding schemes

Design of terahertz transceiver schemes for ultrahigh-speed wireless communications

Future ultra-high-speed wireless communication systems face difficult challenges due to the fundamental limitations of current technologies operating at microwave frequencies. Supporting high transmission rates will require the use of more spectral resources that are only available at higher frequencies. Within this context, terahertz (THz) communications have been attracting more and more attention, being considered by the research community as one of the most promising research fields on the topic due to the availability of extensive unused bandwidth segments. However, its widespread use is not yet possible due to some obstacles, such as the high propagation losses that occur in this band and the difficulty in designing devices that can effectively perform both transmission and detection tasks. The purpose of this dissertation is to contribute for the solution of both of the aforementioned problems and to propose novel THz transceiver schemes for ultra-high-speed wireless communications. Three main research areas were addressed: device modelling for the THz; index modulation (IM) based schemes for Beyond 5G (B5G) networks and hybrid precoding designs for THz ultra massive (UM) – multiple input multiple output (MIMO) systems. The main contributions of this work include the creation of a new design for a reconfigurable THz filter; the proposal of a precoded generalized spatial modulation scheme for downlink MIMO transmissions in B5G networks; the creation of a low-complexity hybrid design algorithm with a near fully-digital performance for multiuser (MU) mmWave/THz ultra massive MIMO systems that can incorporate different analog architectures; and the system-level assessment of cloud radio access network (C-RAN) deployments based on low-complexity hybrid precoding designs for massive MIMO downlink transmissions in B5G networks. The first contribution is especially suited for the implementation of reconfigurable THz filters and optical modulators, since it is based on a simple design, which transits from situations in which it presents a full transparency to situations where it achieves full opacity. Moreover, this approach can also be used for the implementation of simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RIS) which are important for enabling flexible system designs in RIS-assisted networks. The second contribution showed that the implementation of precoding schemes based on generalised spatial modulations is a solution with a considerable potential for future B5G systems, since it can provide larger throughputs when compared to conventional MU-MIMO schemes with identical spectral efficiencies.The last two contributions showed that through the proposed hybrid design algorithm it becomes possible to replace a fully digital precoder/combiner by a fully-connected or even by a partially-connected architecture (array of subarrays and dynamic array of subarrays), while achieving good tradeoffs between spectral efficiency, power consumption and implementation complexity. These proposals are particularly relevant for the support of UM-MIMO in severely hardware constrained THz systems. Moreover, the capability of achieving significant improvements in terms of throughput performance and coverage over typical cellular networks, when considering hybrid precoding‐based C-RAN deployments in two indoor office scenarios at the THz band, was demonstrated.Os futuros sistemas de comunicação sem fios de velocidade ultra-elevada enfrentam desafios difíceis devido às limitações fundamentais das tecnologias atuais que funcionam a frequências de microondas. O suporte de taxas de transmissão altas exigirá a utilização de mais recursos espectrais que só estão disponíveis em frequências mais elevadas. A banda Terahertz (THz) é uma das soluções mais promissoras devido às suas enormes larguras de banda disponíveis no espectro eletromagnético. No entanto, a sua utilização generalizada ainda não é possível devido a alguns obstáculos, tais como as elevadas perdas de propagação que se verificam nesta banda e a dificuldade em conceber dispositivos que possam desempenhar eficazmente as tarefas de transmissão e deteção. O objetivo desta tese de doutoramento, é contribuir para ambos os problemas mencionados anteriormente e propor novos esquemas de transcetores THz para comunicações sem fios de velocidade ultra-elevada. Três grandes áreas de investigação foram endereçadas, contribuindo individualmente para um todo: a modelação do dispositivo para o THz; esquemas baseados em modulações de índice (IM) para redes pós-5G (B5G) e desenhos de pré-codificadores híbridos para sistemas THz MIMO ultra-massivos. As principais contribuições deste trabalho incluem a criação de um novo design para um filtro THz reconfigurável; a proposta de uma nova tipologia de modulação espacial generalizada pré-codificada para transmissões MIMO de ligação descendente para redes B5G; a criação de um algoritmo de design híbrido de baixa complexidade com desempenho quase totalmente digital para sistemas MIMO multi-utilizador (MU) mmWave/THz ultra massivos que podem incorporar diferentes arquiteturas analógicas e a avaliação das implementações da rede de acesso de rádio na nuvem (C-RAN) com base em designs de pré-codificação híbridos de baixa complexidade para transmissões MIMO de ligação descendente massivas em redes B5G. A primeira contribuição é especialmente adequada para a implementação de filtros THz reconfiguráveis e moduladores óticos, uma vez que se baseia numa concepção mais simples, que transita de situações em que apresenta uma transparência total para situações em que atinge uma opacidade total. Para além disso, esta abordagem também pode ser utilizada para a implementação de superfícies inteligentes reconfiguráveis (RIS) de transmissão e reflexão simultânea (STAR). A segunda contribuição mostrou que a implementação de esquemas de pré-codificação baseados em modulações espaciais generalizadas é uma solução com um potencial considerável para futuros sistemas B5G, uma vez que permite alcançar maiores ganhos em termos de débito binário quando comparado com esquemas convencionais MU-MIMO com eficiências espectrais idênticas. As duas últimas contribuições mostraram que através do algoritmo proposto torna-se possível substituir a utilização de uma arquitectura totalmente digital por uma arquitetura totalmente conectada ou mesmo por uma arquitetura parcialmente conectada (arrays de subarrays e arrays dinâmicos de subarrays), conseguindo-se bons tradeoffs entre eficiência espectral, consumo de energia e complexidade de implementação. Estas propostas são particularmente relevantes para dar suporte a sistemas THz UM-MIMO com restrições severas ao nível de hardware. Demonstrou-se também a capacidade de se alcançar melhorias significativas em termos de débito binário e cobertura em relação a redes celulares típicas, considerando dois cenários na banda THz

Quasi-Newton FDE in One-Bit Pseudo-Randomly Quantized Massive MIMO-OFDM Systems

This letter offers a new frequency domain equalization (FDE) scheme that can work with a pseudo-random quantization (PRQ) scheme utilizing non-zero threshold quantization in one-bit uplink multi-user massive multiple-input multiple-output (MIMO) systems to mitigate quantization distortion and support high-order modulation schemes. The equalizer is based on Newton's method (NM) and applicable for orthogonal frequency division multiplexing (OFDM) transmission under frequency-selective fading by exploiting the properties of massive MIMO. We develop a low-complexity FDE scheme to obtain a quasi-Newton method. The proposed detector outperforms the benchmark detector with comparable complexity

A Reduced Complexity Ungerboeck Receiver for Quantized Wideband Massive SC-MIMO

Employing low resolution analog-to-digital converters in massive multiple-input multiple-output (MIMO) has many advantages in terms of total power consumption, cost and feasibility of such systems. However, such advantages come together with significant challenges in channel estimation and data detection due to the severe quantization noise present. In this study, we propose a novel iterative receiver for quantized uplink single carrier MIMO (SC-MIMO) utilizing an efficient message passing algorithm based on the Bussgang decomposition and Ungerboeck factorization, which avoids the use of a complex whitening filter. A reduced state sequence estimator with bidirectional decision feedback is also derived, achieving remarkable complexity reduction compared to the existing receivers for quantized SC-MIMO in the literature, without any requirement on the sparsity of the transmission channel. Moreover, the linear minimum mean-square-error (LMMSE) channel estimator for SC-MIMO under frequency-selective channel, which do not require any cyclic-prefix overhead, is also derived. We observe that the proposed receiver has significant performance gains with respect to the existing receivers in the literature under imperfect channel state information.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Energy efficient and low complexity techniques for the next generation millimeter wave hybrid MIMO systems

The fifth generation (and beyond) wireless communication systems require increased capacity, high data rates, improved coverage and reduced energy consumption. This can be potentially provided by unused available spectrum such as the Millimeter Wave (MmWave) frequency spectrum above 30 GHz. The high bandwidths for mmWave communication compared to sub-6 GHz microwave frequency bands must be traded off against increased path loss, which can be compensated using large-scale antenna arrays such as the Multiple-Input Multiple- Output (MIMO) systems. The analog/digital Hybrid Beamforming (HBF) architectures for mmWave MIMO systems reduce the hardware complexity and power consumption using fewer Radio Frequency (RF) chains and support multi-stream communication with high Spectral Efficiency (SE). Such systems can also be optimized to achieve high Energy Efficiency (EE) gains with low complexity but this has not been widely studied in the literature. This PhD project focussed on designing energy efficient and low complexity communication techniques for next generation mmWave hybrid MIMO systems. Firstly, a novel architecture with a framework that dynamically activates the optimal number of RF chains was designed. Fractional programming was used to solve an EE maximization problem and the Dinkelbach Method (DM) based framework was exploited to optimize the number of active RF chains and the data streams. The DM is an iterative and parametric algorithm where a sequence of easier problems converge to the global solution. The HBF matrices were designed using a codebook-based fast approximation solution called gradient pursuit which was introduced as a cost-effective and fast approximation algorithm. This work maximizes EE by exploiting the structure of RF chains with full resolution sampling unlike existing baseline approaches that use fixed RF chains and aim only for high SE. Secondly, an efficient sparse mmWave channel estimation algorithm was developed with low resolution Analog-to-Digital Converters (ADCs) at the receiver. The sparsity of the mmWave channel was exploited and the estimation problem was tackled using compressed sensing through the Stein's unbiased risk estimate based parametric denoiser. The Expectation-maximization density estimation was used to avoid the need to specify the channel statistics. Furthermore, an energy efficient mmWave hybrid MIMO system was developed with Digital-to- Analog Converters (DACs) at the transmitter where the best subset of the active RF chains and the DAC resolution were selected. A novel technique based on the DM and subset selection optimization was implemented for EE maximization. This work exploits the low resolution sampling at the converting units and provides more efficient solutions in terms of EE and channel estimation than existing baselines in the literature. Thirdly, the DAC and ADC bit resolutions and the HBF matrices were jointly optimized for EE maximization. The flexibility in choosing the bit resolution for each DAC and ADC was considered and they were optimized on a frame-by-frame basis unlike the existing approaches, based on the fixed resolution sampling. A novel decomposition of the HBF matrices to three parts was introduced to represent the analog beamformer matrix, the DAC/ADC bit resolution matrix and the baseband beamformer matrix. The alternating direction method of multipliers was used to solve this matrix factorization problem as it has been successfully applied to other non-convex matrix factorization problems in the literature. This work considers EE maximization with low resolution sampling at both the DACs and the ADCs simultaneously, and jointly optimizes the HBF and DAC/ADC bit resolution matrices, unlike the existing baselines that use fixed bit resolution or otherwise optimize either DAC/ADC bit resolution or HBF matrices

Optimizing Communication Beamforming for New Multiple Access under Low-Resolution Quantization: A Spectral and Energy Efficiency Perspective

Department of Electrical EngineeringCurrently, there is growing interest in 6G wireless communication beyond the era of 5G. In addition, the hardware devices require high-speed wireless communication and low-power communications. For example, there are applications such as the internet-of-things (IoT), where devices are limited by battery capacity and have low computing capabilities but require high spectral efficiency. In order to address the issue of power consumption in wireless communication, low-power hardware such as low-resolution analog-to-digital converter (ADC) and digital-to-analog converter (DAC) systems are having attention as a promising transceiver architecture. This is because the power consumption of quantizers decreases exponentially as the number of quantization bits decreases. In this dissertation, low-resolution quantizer system is considered to achieve the trade-off between high spectral efficiency and energy efficiency. Another challenge that needs to be addressed in the development of 6G wireless communications is the severe inter-user interference resulting from the exponential increase in the number of smart devices. For example, in IoT communications, the large number of IoT devices and high channel correlation among them can lead to a significant amount of inter-user interference, which in turn can cause considerable degradation in spectral performance. In this regard, new multiple access approaches are introduced such as rate-splitting multiple access (RSMA), non-orthogonal multiple access (NOMA), spatial-division multiple access (SDMA), and orthogonal multiple access (OMA) to control the interuser interference. Specifically, I consider rate-splitting multiple access to boost the spectral efficiency because rate-splitting multiple access provides extra achievable antenna degree-of freedom by dividing the messages into common and private messages. It is difficult to optimize rate-splitting multiple access precoders due to the minimum rate constraint involved in determining the common rate. Furthermore, the designing quantized precoders is more highly challenging to solve the optimization problem. In this dissertation, I develop a promising RSMA precoder algorithm coupled with quantization errors to maximize the spectral efficiency. To make the optimization problem in smooth function, I first approximate the spectral efficiency of common stream utilizing the Log-Sum Exp technique. Then, I derive the first-order optimality condition in terms of the nonlinear eigenvalue problem (NEP). I suggest computationally efficient method to find a sub-optimal solution for obtaining the principal eigen-vector of the nonlinear eigenvalue problem. In addition, I propose the weighted minimum mean square error-based RSMA precoding algorithm to the considered quantization system. Simulation results demonstrate the performance of the proposed algorithm in terms of the spectral efficiency, and more importantly, ratesplitting multiple access can achieve key benefit than spatial-division multiple access by balancing between the channel gain and quantization error utilizing the common stream in multiuser MIMO systems.clos