One of the main issues that prevents mmWave communications from being used in cellular networks is the performance in mobility scenarios. Indeed, as described here, mmWave links suffer from blockage from obstacles such as the human body, vehicles, buildings, etc. Moreover, mmWave cells will cover a small area, thus requiring a dense deployment. As the mobile user moves, it may suddenly lose connectivity with respect to the current mmWave base station, or it may even be in outage with respect to all of them. The mobility management under these hypothesis becomes challenging, because the number of handovers and/or beam switch events increases, and the solutions adopted in traditional networks are not enough. Indeed, if the mobile terminal is connected to a single Radio Access Network at any given time, a complete outage event would require a Radio Link Failure or a long and complex inter-RAT handover, for example to a legacy LTE network.
We propose a mobility management solution based on dual connectivity, in which the mobile user is connected to an LTE and a mmWave base station at the same time. Moreover, each group of mmWave base station is coordinated by a local mobility anchor, so that there is no need to interact with the core network for local mobility. The user plane is split at the PDCP layer.
With this architecture it is possible to:
- Collect channel measurements and track the optimal base station for each mobile user;
- Design faster network procedures, to quickly switch from LTE to mmWave and viceversa, and to perform a swift secondary cell handover without interacting with the core network.
The dual connectivity architecture was analyzed with the first simulation campaign combining a mmWave dynamic channel model (with experimental traces to model the transition between LOS and NLOS and vice versa) and end-to-end TCP/IP and cellular network protocol stacks, using the tool described in the Simulation page. With respect to a traditional single connectivity solution, our architecture is able to better adapt to the dynamic mmWave channel conditions, thus keeping a lower latency and smaller throughput variations. This increases the robustness of the network, enhancing the quality of experience of the mobile user.
|M. Polese, M. Giordani, M. Mezzavilla, S. Rangan, and M. Zorzi, “Improved Handover Through Dual Connectivity in 5G mmWave Mobile Networks”, to appear on IEEE Journal on Selected Areas in Communications (JSAC)||2017/09||Mobility, Transport, Simulation|
|M. Giordani, M. Mezzavilla, S. Rangan, and M. Zorzi, “An Efficient Uplink Multi-Connectivity Scheme for 5G mmWave Control Plane Applications", submitted to IEEE Transaction on Wireless Communications||2017/07||Tracking, Mobility|
|M. Polese, M. Mezzavilla, and M. Zorzi, “Performance Comparison of Dual Connectivity and Hard Handover for LTE-5G Tight Integration,” in SIMUTools 2016||2016/08||Simulation, Mobility|
|M. Giordani, M. Mezzavilla, S. Rangan, and M. Zorzi, “Multi-Connectivity in 5G mmWave cellular networks,” in IEEE 15th Annual Mediterranean Ad Hoc Networking Workshop||2016/06||Mobility, Tracking|
|Mezzavilla, M., Goyal, S., Panwar, S., Rangan, S., and Zorzi, M., An mdp model for optimal handover decisions in mmWave cellular networks, in Proceedings of European Conference on Networks and Communications (EuCNC), June 2016, Athens, Greece||2016/06||Mobility|