Leveraging Synergy of 5G SDWN and Multi-Layer Resource Management for Network Optimization

Fifth-generation (5G) cellular wireless networks are envisioned to predispose service-oriented, flexible, and spectrum/energy-efficient edge-to-core infrastructure, aiming to offer diverse smart-X (city, grid, and phones) applications. Convergence of software-defined networking (SDN), software-defined radio (SDR) compatible with multiple radio access technologies (RATs), and virtualization on the concept of 5G software-defined wireless networking (5G-SDWN) is a promising approach to provide such a dynamic network. The principal technique behind the 5G-SDWN framework is the separation of the control and data planes, from the deep core entities to edge wireless access points (APs). This separation allows the abstraction of resources as transmission parameters of each user over the 5G-SDWN. Similar to traditional wireless networks, in this user-centric, service-oriented and integrated environment, resource management plays a critical role to achieve efficiency and reliability. However, it is natural to wonder if 5G-SDWN can be leveraged to enable converged multi-layer (CML) resource management over the portfolio of resources, and reciprocally, if CML resource management can effectively provide performance enhancement and reliability for 5G-SDWN. We believe that replying to these questions and investigating this mutual synergy are not trivial, but multidimensional and complex for 5G-SDWN, which consists of different technologies and also inherits legacy generations of wireless networks. In this paper, we propose a flexible protocol structure based on three mentioned pillars for 5G-SDWN, which can handle all the required functionalities in a more crosslayer manner compared to the legacy wireless networks (2G, 3G and 4G). Based on this, we demonstrate how the general framework of CML resource management can control the enduser quality of experience. For two scenarios of 5G-SDWN, including both macro-cells and small-cells, we investigate the effects of joint user-association and resource allocation via CML resource management to improve performance in a virtualized network.