Power Allocation in Uplink NOMA-Aided Massive MIMO Systems

In the development of the fifth-generation (5G) as well as the vision for the future generations of wireless communications networks, massive multiple-input multiple-output (MIMO) technology has played an increasingly important role as a key enabler to meet the growing demand for very high data throughput. By equipping base stations (BSs) with hundreds to thousands antennas, the massive MIMO technology is capable of simultaneously serving multiple users in the same time-frequency resources with simple linear signal processing in both the downlink (DL) and uplink (UL) transmissions. Thanks to the asymptotically orthogonal property of users' wireless channels, the simple linear signal processing can effectively mitigate inter-user interference and noise while boosting the desired signal's gain, and hence achieves high data throughput. In order to realize this orthogonal property in a practical system, one critical requirement in the massive MIMO technology is to have the instantaneous channel state information (CSI), which is acquired via channel estimation with pilot signaling. Unfortunately, the connection capability of a conventional massive MIMO system is strictly limited by the time resource spent for channel estimation. Attempting to serve more users beyond the limit may result in a phenomenon known as pilot contamination, which causes correlated interference, lowers signal gain and hence, severely degrades the system's performance. A natural question is ``Is it at all possible to serve more users beyond the limit of a conventional massive MIMO system?''. The main contribution of this thesis is to provide a promising solution by integrating the concept of nonorthogonal multiple access (NOMA) into a massive MIMO system. The key concept of NOMA is based on assigning each unit of orthogonal radio resources, such as frequency carriers, time slots or spreading codes, to more than one user and utilize a non-linear signal processing technique like successive interference cancellation (SIC) or dirty paper coding (DPC) to mitigate inter-user interference. In a massive MIMO system, pilot sequences are also orthogonal resources, which can be allocated with the NOMA approach. By sharing a pilot sequence to more than one user and utilizing the SIC technique, a massive MIMO system can serve more users with a fixed amount of time spent for channel estimation. However, as a consequence of pilot reuse, correlated interference becomes the main challenge that limits the spectral efficiency (SE) of a massive MIMO-NOMA system. To address this issue, this thesis focuses on how to mitigate correlated interference when combining NOMA into a massive MIMO system in order to accommodate a higher number of wireless users. In the first part, we consider the problem of SIC in a single-cell massive MIMO system in order to serve twice the number of users with the aid of time-offset pilots. With the proposed time-offset pilots, users are divided into two groups and the uplink pilots from one group are transmitted simultaneously with the uplink data of the other group, which allows the system to accommodate more users for a given number of pilots. Successive interference cancellation is developed to ease the effect of pilot contamination and enhance data detection. In the second part, the work is extended to a cell-free network, where there is no cell boundary and a user can be served by multiple base stations. The chapter focuses on the NOMA approach for sharing pilot sequences among users. Unlike the conventional cell-free massive MIMO-NOMA systems in which the UL signals from different access points are equally combined over the backhaul network, we first develop an optimal backhaul combining (OBC) method to maximize the UL signal-to-interference-plus-noise ratio (SINR). It is shown that, by using OBC, the correlated interference can be effectively mitigated if the number of users assigned to each pilot sequence is less than or equal to the number of base stations. As a result, the cell-free massive MIMO-NOMA system with OBC can enjoy unlimited performance when the number of antennas at each BS tends to infinity. Finally, we investigate the impact of imperfect SIC to a NOMA cell-free massive MIMO system. Unlike the majority of existing research works on performance evaluation of NOMA, which assume perfect channel state information and perfect data detection for SIC, we take into account the effect of practical (hence imperfect) SIC. We show that the received signal at the backhaul network of a cell-free massive MIMO-NOMA system can be effectively treated as a signal received over an additive white Gaussian noised (AWGN) channel. As a result, a discrete joint distribution between the interfering signal and its detected version can be analytically found, from which an adaptive SIC scheme is proposed to improve performance of interference cancellation

Implementation of Deep-Learning-Based CSI Feedback Reporting on 5G NR-Compliant Link-Level Simulator

Advances in machine learning have widened the range of its applications in many fields. In particular, deep learning has attracted much interest for its ability to provide solutions where the derivation of a rigorous mathematical model of the problem is troublesome. Our interest was drawn to the application of deep learning for channel state information feedback reporting, a crucial problem in frequency division duplexing (FDD) 5G networks, where knowledge of the channel characteristics is fundamental to exploiting the full potential of multiple-input multiple-output (MIMO) systems. We designed a framework adopting a 5G New Radio convolutional neural network, called NR-CsiNet, with the aim of compressing the channel matrix experienced by the user at the receiver side and then reconstructing it at the transmitter side. In contrast to similar solutions, our framework is based on a 5G New Radio fully compliant simulator, thus implementing a channel generator based on the latest 3GPP 3-D channel model. Moreover, realistic 5G scenarios are considered by including multi-receiving antenna schemes and noisy downlink channel estimation. Simulations were carried out to analyze and compare the performance with current feedback reporting schemes, showing promising results for this approach from the point of view of the block error rate and throughput of the 5G data channel

Técnicas de equalização híbridas para sistemas heterogéneos na banda das ondas milimétricas

With the constant demand for better service and higher transmission rates current technologies are reaching the limits of the channel capacity. Although, technologies such as MIMO and Heterogeneous systems appear to increase the channel capacity by introducing more antennas at the transceivers making the link between users and base station more reliable. Furthermore, the current spectrum, sub-6GHz, is becoming saturated and due to the properties of such frequencies the deployment of heterogeneous systems can introduce some levels of interference. Towards improving future communication systems a new part of the frequencies spectrum available should be used, researchers have their eyes on the mmWave band. This band allows to increase the carrier frequency and respective signal bandwidth and therefore increase the transmission speeds, moreover the properties of such frequencies unlock some advantages over the frequencies used in the sub-6G band. Additionally, mmWave band can be combined with massive MIMO technology to enhance the system capacity and to deploy more antenna elements in the transceivers. One more key technology that improves the energy efficiency in systems with hundreds of antenna elements is the possibility to combine analog and digital precoding techniques denoted as hybrid architectures. The main advantages of such techniques is that contrary to the full digital precoding processing used in current systems this new architecture allows to reduce the number of RF chains per antenna leading to improved energy efficiency. Furthermore to handle heterogeneous systems that have small-cells within the macro-cell, techniques such as Interference Alignment (IA) can be used to efficiently remove the existing multi-tier interference. In this dissertation a massive MIMO mmWave heterogeneous system is implemented and evaluated. It is designed analog-digital equalizers to efficiently remove both the intra an inter-tier interference. At digital level, an interference alignment technique is used to remove the interference and increase the spectral efficiency. The results showed that the proposed solutions are efficient to remove the macro and small cells interference.Com a constante procura de melhores serviços e taxas de transmissão mais elevadas, as tecnologias atuais estão a atingir os limites de capacidade do canal. Contudo tecnologias como o MIMO e os sistemas heterogéneos permitem aumentar a capacidade do canal através da introdução de mais antenas nos transcetores e através da implementação de pequenos pontos de acesso espalhados pela célula primária, com o intuito de tornar as ligações entre os utilizadores e a estação base mais fiáveis. Tendo também em atenção que o espectro atual, sub-6GHz, está sobrecarregado e que devido às propriedades das frequências utilizadas a implementação de sistemas heterogéneos pode levar a níveis de interferência insustentáveis. Por modo a resolver esta sobrecarga futuros sistemas de comunicação devem aproveitar uma maior parte do espectro de frequências disponível. A banda das ondas milimétricas (mmWave) tem sido apontada como solução, o que permite aumentar a frequência utilizada para transportar o sinal e consequentemente aumentar as velocidades de transmissão. Uma outra vantagem da banda mmWave é que pode ser combinada com a tecnologia MIMO massivo, permitindo implementar mais elementos de antena nos terminais e consequentemente aumentar a capacidade do sistema. Umas das tecnologias desenvolvida para melhorar a eficiência energética em sistemas com centenas de antenas é a possibilidade de combinar técnicas de codificação analógica e digital, designadas como arquiteturas híbridas. A principal vantagem desta técnica é que, contrariamente ao processamento feito nos sistemas atuais, totalmente no domínio digital, esta nova arquitetura permite reduzir o número de cadeias RF por antena. Com o intuito de reduzir a interferência em sistemas heterogéneos, técnicas como o alinhamento de interferência são usadas para separar utilizadores das células secundárias dos utilizadores das células primárias de modo a reduzir a interferência multi-nível existente no sistema geral. Nesta dissertação, é implementado e avaliado um sistema heterogéneo que combina MIMO massivo e ondas milimétricas. Este sistema é projetado com equalizadores analógico-digitais para remover com eficiência a interferência intra e inter-camadas. No domínio digital é utilizada a técnica de alinhamento de interferência para remover a interferência e aumentar a eficiência espectral. Os resultados mostram que as soluções propostas são eficientes para remover a interferência entre as células secundárias e a primária.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

RIS-Aided Cell-Free Massive MIMO Systems for 6G: Fundamentals, System Design, and Applications

An introduction of intelligent interconnectivity for people and things has posed higher demands and more challenges for sixth-generation (6G) networks, such as high spectral efficiency and energy efficiency, ultra-low latency, and ultra-high reliability. Cell-free (CF) massive multiple-input multiple-output (mMIMO) and reconfigurable intelligent surface (RIS), also called intelligent reflecting surface (IRS), are two promising technologies for coping with these unprecedented demands. Given their distinct capabilities, integrating the two technologies to further enhance wireless network performances has received great research and development attention. In this paper, we provide a comprehensive survey of research on RIS-aided CF mMIMO wireless communication systems. We first introduce system models focusing on system architecture and application scenarios, channel models, and communication protocols. Subsequently, we summarize the relevant studies on system operation and resource allocation, providing in-depth analyses and discussions. Following this, we present practical challenges faced by RIS-aided CF mMIMO systems, particularly those introduced by RIS, such as hardware impairments and electromagnetic interference. We summarize corresponding analyses and solutions to further facilitate the implementation of RIS-aided CF mMIMO systems. Furthermore, we explore an interplay between RIS-aided CF mMIMO and other emerging 6G technologies, such as next-generation multiple-access (NGMA), simultaneous wireless information and power transfer (SWIPT), and millimeter wave (mmWave). Finally, we outline several research directions for future RIS-aided CF mMIMO systems.Comment: 30 pages, 15 figure

An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

To meet the future demand for huge traffic volume of wireless data service, the research on the fifth generation (5G) mobile communication systems has been undertaken in recent years. It is expected that the spectral and energy efficiencies in 5G mobile communication systems should be ten-fold higher than the ones in the fourth generation (4G) mobile communication systems. Therefore, it is important to further exploit the potential of spatial multiplexing of multiple antennas. In the last twenty years, multiple-input multiple-output (MIMO) antenna techniques have been considered as the key techniques to increase the capacity of wireless communication systems. When a large-scale antenna array (which is also called massive MIMO) is equipped in a base-station, or a large number of distributed antennas (which is also called large-scale distributed MIMO) are deployed, the spectral and energy efficiencies can be further improved by using spatial domain multiple access. This paper provides an overview of massive MIMO and large-scale distributed MIMO systems, including spectral efficiency analysis, channel state information (CSI) acquisition, wireless transmission technology, and resource allocation