Improving DRX Performance For Emerging Use Cases In 5G

This thesis proposes approaches and models to increase the energy saving of the User Equipment (UE) in Long-Term Evolution (LTE) and 5G. The focus is mainly on Discontinuous Reception (DRX), the UE energy saving mechanism that was first introduced in LTE and will play an important role in 5G too.In this thesis, we take two main approaches. The first approach is based on joint optimization of DRX and resource allocation in order to improve the energy saving (increase battery life time) for different scenarios. In particular, we propose utilizing the possibility of predicting the channel capacities for the UEs in order to jointly optimize the resource allocation and DRX parameters. We also propose two new flexible DRX approaches, DRXset and VDRX which are adjustable according to the traffic and channel information. The proposed solutions can create longer sleep opportunities for the UEs, as well as increased network capacity and flexibility.Aside from this, we investigate the performance of DRX in different use cases related to 5G. For example we study the impact of 5G Radio Access Network (RAN) slicing on the energy saving and sleep opportunity of the UEs. We propose slicing strategies that are less sensitive, in terms of UE energy usage, to the inter-slice resource sharing policies. We also propose a novel DRX state model for Device-to-Device (D2D) communication. The proposed state model is based on semi-Markov process similar to the legacy DRX. However, we introduce extra states and sub-states to the DRX state model in order to make it suitable for the D2D communication