Open Thesis

Optimal resource allocation for utility maximization in 5G networks

5G, network slicing, optimization


The slice dimensioning for the three types (eMBB, URLLC, and mMTC) of traffic in 5G would be the focus of this thesis. Each user, depending on the type of traffic, is characterized by a weight. This could be e.g., the gain of the operator by serving a given user. We assume that the stringent the traffic requirement is, the higher the gain for the operator. In this way, mMTC users weight would be the lowest, whereas the URRLC’s the highest. Also, users have different channel conditions, which needs to be taken into account. For each admitted user, the traffic requirement would have to be satisfied. The problem would then reduce to deciding how many slices are to be allocated to each service type, and the corresponding number of users within the slice, so that the utility for the operator is maximized. Three policies are to be analyzed. The first is motivated by the finite number of resource blocks each cell has, so that a brute-force solution is found. The computational complexity of this policy has to be obtained as well. The second, less complex policy, is one in which resources are reserved beforehand (i.e., it is a static policy) based depending on the ratio between the weight and the resources needed for a user of the given service type. Finally, the third policy, which would be based on a heuristic, would decide on-the-fly on how to dimension RAN slice sizes.


Fidan Mehmeti