Self-healing of Radio Access Network Slices

Radio Access Network (RAN) slicing is a promising architectural technology to address extremely diversified service demands for future mobile networks. As an essential requirement for RAN slicing, self-healing is to provide services with certain quality requirements by minimizing the impact of mobile network failings. In this paper, we propose a Multi-objective Pareto Optimization based Self-healing (MPOS) scheme to solve the SRANS problem. We model the SRANS problem as a multi-objective optimization problem with aim of maximizing the self-healing profits of individual RAN slices and demonstrate the NP-hardness. In proposed MPOS scheme, we employ self-conditioned GANs to replace the offspring reproduction module in the traditional Multi-Objective Evolutionary Algorithm (MOEA), where the insufficiency of diversity maintenance in MOEA is effectively overcome. Furthermore, we theoretically prove that MPOS framework is guaranteed to converge to the optimal Pareto solution set with probability 1. Numerical results demonstrate that our MPOS scheme is effective in reducing the inverted generational distance of optimal Pareto solutions and achieving high profit and isolation level of RAN slices

Self-Healing in 5G HetNets

The main requirements of 5G are emerging through the efforts of diverse groups such as 4G America in United States, IMT-2020 (5G) promotion group in China and the 5G Private Public Partnership (5G PPP) in Europe. The 5G requirements will tremendously increase the network complexity which requires auto-integration and self-management capabilities that are well beyond today\u27s self-organising network features. Additionally, ultra-reliable communications put very stringent latency and reliability requirements on the architecture