Radio resource management (RRM) plays a critical role in modern wireless communications networks. RRM 's ultimate goal is to devise strategies to efficiently manage the network's radio resources, e.g., infrastructure and spectrum, and thus coordinate interference and ensure QoS requirements for the UE. RRM has undergone a tremendous transformation from initially being limited to solely the physical layer with fixed policies to presently incorporating dynamic cross-layer algorithms that allow controlling multiple characteristics of the physical and higher layers.

Each succeeding generation of wireless mobile technology has contributed to expanding the network capabilities but has also posed new challenges for RRM in coordinating more radio spectrum, e.g., millimeter-wave spectrum, and more radio infrastructure, e.g., CoMP and IAB. Therefore, as wireless technologies evolve, RRM strategies must also adapt to account for emerging radio infrastructure and spectrum, ensuring their efficient utilization along with the existing resources.

This thesis proposes several RRM strategies and algorithms to improve radio resource utilization, addressing challenges intrinsic to the evolution of wireless mobile technologies. Different RRM research problems are investigated considering diverse radio resources, such as precoding, admission control, and discrete rate allocation, focusing on various use cases, such as Industry 4.0.

The strategies and algorithms developed herein not only target networks deployed using SDMA, adopted as de facto multiple access scheme, but also target emerging multiple access schemes, such as LDMA and RSMA. In addition, the strategies and algorithms are not limited to access networks only, but also include backhaul networks, specifically IAB technology.

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