Telecommunication customer satisfaction using selforganized network-based heuristic algorithm

摘要

The emerging network including long-term evolution-advanced (LTE-A) aims at enhancing the telecommunication customer satisfaction in numerous aspects including system capacity, network coverage, handover management, and quality of service (QoS). Effective handover (HO) management reduces HO failure and hence enhances the data rate and supports user mobility. There are numerous challenges that increase the call drop rate. Among the main challenges that increase the call drop rate, the variable user speeds and variable traffic loads are the major ones. Hence, the time to trigger (TTT), HO margin (HOM), and HO offset (HOO) are used to evaluate the HO management using self-organized network-based heuristic algorithm under variable user speeds and variable traffic loads. In recent researches, different HO management techniques were applied to manage the HO decision including fuzzy-logic tactics and Q-learning. However, they did not apply intelligent optimization techniques that adapt the variable user speeds and dynamic traffic loads. This paper aims at increasing the telecom customer satisfaction by decreasing the call drop rate using particle swarm optimization (PSO), which adaptively manages the handover control parameters according to the user speed and traffic loads. The simulation results have shown that the proposed optimization tool results in significant call drop rate reduction compared to the ordinary HO management.