Performance study of RASO algorithm beyond 4G

Self-optimization for random access procedure in SONs has a profound impact on user equipment experience and network performance in 3G/4G. However, the process of designing self-optimization towards a 5G system is a difficult challenge. In this paper, we proposed a multi-objective algorithm of random access self-optimization (RASO) in terms of auto-adjustment and configuration, which includes physical random access channel parameter, transmission power parameter, and backoff parameter jointly auto-adapted with respect to changes in the network. Our simulation demonstrated that a combination of these control parameters and their auto-adjustment directly improves the access probability and access delay at high load, compared to using a single control parameter. Such combination also enhances the reception of random access requests, thus producing better quality of service. Simulation results are thus presented to illustrate the algorithm's effectiveness.