Dynamic Coordination Architecture and Mobility Management for Next Generation Cooperative Cellular Networks

Abstract

The fundamental challenges of existing cellular wireless networks are the exponential demand of mobile data traffic, higher data rates, massive numbers of user-coverage and lower latency. Moreover, the next generation of wireless cellular networks also consider potential use cases, such as autonomous vehicle control, smart cities, remote surgery and eHealth, tactile internet, etc. To address these challenges and potential use cases, network densification such as ultra-dense heterogeneous networks (UDHetNet) and multi-cell cooperation are considered as the foundation to support the 1000× capacity challenge in the next generation wireless cellular networks. In this thesis, we study the coordination architecture and mobility management of multi-cell cooperative communications and present novel algorithms to improve the performance of multi-cell cooperative cellular networks. We propose DCEC: Direct CSI-feedback to Elected Coordination-station, a CoMP coordination architecture for cooperative communication to improve the performance of cellular networks, reducing the signaling overhead and latency. We extended the DCEC approach to heterogeneous cellular networks named DCEC-HetNet as well. We also propose a handover procedure for heterogeneous multi-cell cooperative cellular networks named EHoLM: Enhanced Handover for Low and Moderate speed UEs. The goal of the EHoLM handover procedure is to improve the system performance and user experience, reducing the number of handovers, handover oscillation and handover failure rate. To examine the performance of the proposed algorithms we use the discrete event system specifications (DEVS) for modeling and simulation of cellular networks employing the DCEC and EHoLM methods. Simulation results show that the proposed algorithms have potentials to improve the performance of cooperative cellular networks compared to the conventional methods. We also study the verification and validation (V&V) process of simulation models. A revised lifecycle of modeling and simulation (M&S) has also been presented that accommodates both formal and conceptual approaches of the verification and validation (V&V) process. Finally, how we validated the simulation models we developed for analyzing the proposed algorithms has been presented.