Resource allocation techniques for spectral and energy-efficient next generation wireless networks

Efficient utilization of wireless resources is mandated to fulfill the requirements of the sixth-generation (6G) wireless networks, such as high data rates, low latency, and ubiquitous connectivity. The word "resource" implies quantities such as bandwidth, power, and time. Efficiently allocating such limited resources is an effective means to enhance the wireless systems’ performance. Specifically, resource allocation intends to assign limited resources to users, maximizing the utilization of these resources, and attaining the best system performance. In this line, in this dissertation, low-complexity and efficient resource allocation strategies in networks assisted by various technologies, including nonorthogonal multiple access (NOMA), reconfigurable intelligent surface (RIS), full-duplex (FD), cell-free massive multiple-input multiple-output (CFmMIMO), and integrated sensing and communication (ISAC) are developed and investigated. The first part of the dissertation focuses on analyzing the outage and throughput performances, as well as optimizing the sum rate for an FD NOMA-assisted cooperative spectrum-sharing network. The second part develops novel user clustering and resource allocation algorithms to boost the sum spectral efficiency of a CFmMIMO-NOMA system. Besides, novel lowcomplexity resource allocation algorithms for optimizing the energy efficiency and total transmit power of RIS-aided CF and RIS-enabled federated learning (FL) networks are proposed. The third part examines the application of RIS and FD in ISAC networks to improve the transmission rate and sensing performance. Finally, the last part draws concluding remarks and discusses several topics for future investigation.