Uplink Resource Allocation Methods for Next Generation Wireless Networks

Facing the diversity of communication needs of 5G networks and the future 6G, resource allocation is considered as a key enabler to increase the number of devices, the data rate or the reliability of the communication links. In machine-type communications networks, recent work has proposed to adapt the temporal resource allocation as a function of the underlying process driving the activity of the devices. This thesis firstly focuses on the impact of having only limited knowledge of the underlying process, and proposes methods to mitigate the bias induced by the lack of knowledge. Secondly, an algorithm for the joint optimization of the temporal resource allocation and the transmit power of the devices is proposed. The algorithm ensures that devices that are likely to transmit on the same resources do so with a sufficient power diversity to ensure their decodability by the base station. Finally, in networks with an enhanced mobile broadband objective, we propose to jointly optimize the power, the frequency resources used, as well as the number of parallel data streams used by the devices. Our simulation study shows that our joint optimization outperforms current 5G baselines for which these parameters are common to all devices of the cell.