Dynamic User Association for Resilient Backhauling in Satellite-Terrestrial Integrated Networks

Abstract

The satellite-terrestrial integrated networks (STINs) have gradually become a new class of effective ways to satisfy the requirements of a higher capacity and stronger connection in the future communications. In contrast with terrestrial networks, the fast periodic motion of satellites results in the dynamic time-varying features of STIN, which further leads to frequent changes in the connectivity of satellite-terrestrial links and the backhaul capacities of satellite networks. To balance the accessible capacity of STIN under the intermittent connectivity and dynamic backhaul capacity, an effective user association mechanism is needed. In this article, a dynamic user association (DUA) mechanism with task classification is proposed to meet the requirements of load balancing and the user task processing. First, a STIN model is constructed with low earth orbit satellites and the three types of base station, which are a macro base station, small cell base station, and low earth orbit based base station. After that, the optimization problem is formulated via jointly considering the task classification, the load condition of base stations, and the backhaul capacity of low earth orbit based base stations. Then, the DUA mechanism is proposed to find the most suitable base station serving each user. In DUA, a dynamic cell range extension algorithm is developed to adjust the load of STIN in terms of the resilient backhaul capacity, and a greedy-based user-centric user association with task classification algorithm is proposed to find the base station, which has the maximum rate and minimum load for each user and to meet the requirements of user task processing. The simulation results show that the proposed DUA can enhance the load balance and guarantee the task processing demand of STIN compared with the reference signal receiving power association and the max-sum rate association algorithms.