Abstract:
As the number of smart devices increases day by day, the need for new resource allocation techniques also increases. 5G technologies such as Long-Term Evolution Advanced (LTE-A), carrier aggregated heterogeneous networks (HetNets), or Internet of things (IoT) networks with mobile edge computing (MEC) features require high data rates and ultra low latency with the restricted resources. Resource allocation and secure communication are two of the most important challenges in wireless communication. Graph-based algorithms are proposed in order to achieve resource allocation with a low computational complexity. The primary objective of this thesis is to address the resource allocation challenges, e.g., fairness and stability, by using stable matching (SM)-based approaches. SM algorithm requires channel state information (CSI) before starting allocation. However, CSI transmission may cause an overload of the up-link channel. The problem is extensively elaborated in many aspects for different wireless communication systems such as HetNets and IoT networks. The overload on the uplink channel, through CSI transmission, is decreased significantly by the proposed partial feedback matching (PFM) algorithm. Finally, IoT networks are very fragile against attackers in physical layer as the number of connected smart devices increases. A three state SM-based attacker identification and punishment policy, is proposed in order to increase the robustness of the network. Both analytical and simulation results are presented to demonstrate that the proposed SM-based approaches have better performance than the algorithms that exist in the literature.
