Physical layer optimization, multiple access, and energy efficiency in extra-large scale massive MIMO and wireless networks aided by reconfigurable intelligent surfaces

• Ano de defesa: 2024
• Autor(a) principal: Souza, João Henrique Inácio de
• Orientador(a): Abrão, Taufik
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Massive multiple-input multiple-output (MIMO); Extra-large scale mas sive MIMO (XL-MIMO); Reconfigurable intelligent surface (RIS); Eficiência energética; Internet das coisas; Protocolos de acesso aleatório; Engenharia elétrica; Redes de comunicações móveis
• Área do conhecimento CNPq: Engenharias - Engenharia Elétrica
• Link de acesso: https://repositorio.uel.br/handle/123456789/18247

The mobile networks beyond the fifth generation (B5G) must be designed to supply an increasing demand for connectivity, coming not only from established applications but also from emerging ones that surge with progressively ambitious communication requirements. To that end, physical layer technologies such as extra-large scale massive multiple-input multiple-output (XL-MIMO) and reconfigurable intelligent surfaces (RISs) have been considered for integrating the specifications of the next-generation networks aiming to boost the key performance indicators (KPIs). XL-MIMO encompasses communication systems where the base station is equipped with a physically large antenna array, with hundreds to thousands of half-wavelength-spaced antennas. Seen as an evolution of massive MIMO, in XL-MIMO systems, the array provides extra spatial degrees of freedom (DoFs) that can be explored to spatially multiplex many users with high data rates. Furthermore, an RIS is a thin sheet of composite material equipped with electronic circuits that can be programmed to change the characteristics of the incoming electromagnetic field. It can be used to coherently reflect radio signals, enhancing the wireless channel in arbitrary spots of the service area, relying on low-cost and energy-efficient hardware. To unlock the potential of XL-MIMO and RIS, it is necessary to solve open research questions concerning channel modeling, system design, and optimization strategies. Addressing the challenges faced in the development of these technologies, this thesis investigates the applicability of XL-MIMO and RIS to leverage the communication KPIs in the B5G networks. Based on the B5G usage scenarios, it focuses on four objectives: 1) providing high data rates and supporting high connection density for gigabit per second communication; 2) enabling energy-efficient wireless communication for the Internet of Things (IoT); 3) providing reliable and low-latency communication for mission-critical applications; and 4) investigating the potential of RISs to program aspects of the wireless channel. Regarding XL-MIMO, to support multi-user communication in crowded environments, a strategy for system optimization is proposed to efficiently explore all the DoFs provided by the high-aperture array. Furthermore, concerning RIS, the energy efficiency of RIS-aided IoT networks is analyzed, producing relevant insights for system design aiming to extend the devices’ battery lifetime and enhance the network coverage. Moreover, a multiple access scheme to multiplex hybrid traffic is proposed, using the RIS to support the coexistence through network resource sharing of mission-critical services along with broadband communication services. Finally, tackling the integration of the RIS controllability and exploring its capability of shaping the wireless channel, a method is proposed to control the channel temporal statistics by using an RIS with time-varying stochastic configurations. In short, this thesis presents methods, procedures, and algorithms to implement XL-MIMO systems and RISs in the B5G networks, accompanied by comprehensive evaluations of the system trade-offs in terms of relevant KPIs, including spectral efficiency, energy efficiency, outage probability, and latency.