# Caching-Aware Intelligent Handover Strategy for LEO Satellite Networks
###### Abstract
[16] proposed a user-centric handover scheme for ultra-dense LEO satellite networks, and it can realize seamless handover by buffering user's downlink data in multiple satellites simultaneously. [PERSON] et al. [17] proposed a handover algorithm based on the potential game, and the strategy considered the remaining service time and the satellite elevation angle which can be utilized to minimize the average satellite handover times and decrease call-dropping probability. They also proposed a terminal random-access algorithm aiming at balancing the network load. [PERSON] et al. [18] proposed a load-aware satellite handover strategy based on multi-agent reinforcement learning, and it can balance satellite load to avoid network congestion, while, at the same time, maintain low signaling overhead. [PERSON] et al. [19] proposed an LEO satellite handover strategy based on the multi-attribute decision. The strategy used the technique for order preference by similarity to an ideal solution (TOPSIS) evaluation method to calculate the weighted values of three attributes, which include signal strength, remaining service time, and remaining idle channels. And then, the stratgy selected the candidate satellite with the best overall performance. [PERSON] et al. [20] considered the impacts of channel quality, remaining service time, and the number of service users on handover strategy, and they used the entropy method to weight each factor and transform it into a single objective optimization problem. [PERSON] et al. [21] analyzed a quality of experience (QoE)-driven handover strategy, which considered routing delay, remaining service times, and remaining idle channels with high-speed mobile users for LEO satellite networks. Table 1 shows the summary and comparison of the above studies. Besides factors related to the communication metrics, resource management by considering the integration of communication, computing and caching (3C) is also important for future mobile edge computing (MEC) enhanced satellite systems [22]. Caching data at satellite nodes can improve communication efficiency by avoiding duplicate transmissions [23; 24]. [PERSON] et al. [23] proposed a novel caching algorithm by optimizing contents placement in LEO satellite constellation networks, which was used to minimize user terminals content access delay. [PERSON] et al. [25] analyzed the caching restricted resource allocation with joint optimization of satisfaction index and spectrum efficiency for multi-beam satellite systems. Since the satellite on-board caching resource is limited, we focus on evaluating the inter-satellite handover strategies for the LEO satellite systems with the caching aware strategy. Moreover, we aim to tackle the following problems encountered by the existing handover strategies:  
1. Although the existing handover strategies analyze several factors that affect the performance of handover, the effect of limited on-board caching is not considered. Moreover, the joint-effect of multiple attributes, which are on-board caching, remaining service time, and idle channels, is not considered either. 2. The existing handover strategies make the handover decisions with the snap shot-based topology. However, the topology of LEO satellite networks is time varying, and