# IBP Based Caching Strategy in D2D
## 1 Introduction  
According to Cisco VNI (Visual Networking Index) report, mobile data traffic will grow 7-fold from 2017 to 2022, and video traffic will be 79% of global mobile data traffic by 2022. It will be a big challenge to current wireless network. To reduce traffic and energy cost of backhaul links, D2D communication has been proposed. Within D2D communication network, device can communicate with nearby device directly by establishing D2D communication link between them. Another potential solution to this challenge is caching, which has been proved can improve network performance of several network scenarios [1, 2]. In recent years, caching also has been applied into CN (Core Network) and RAN (Ratio Access Network) of 5 th generation wireless systems (5G) to reduce backhaul traffic and network latency [3, 4, 5, 6, 7].  
Recently, several studies have proved that applying caching strategy into D2D communication network can offload backhaul traffic and improve user experience [8, 9]. In D2D caching network, each device is equipped with cache space for caching popular content. Device can receive its desired content from nearby devices instead of BS (Base Station) through one-hop or multi-hop D2D communication. Caching scheme is an important part of D2D caching network and impacts network performance. Most existing D2D caching schemes are proactive caching, i.e., pre-caching popular content to devices before the content being requested during off-peak time. The performance of proactive caching scheme depends on accuracy of prediction.  
According to a report released by data provider iResearch, China's short video mark was valued at 14 billion yuan ($2 billion) in 2018. With the explosive growth of short video mobile apps, proactive caching strategies face a big challenge, since short videos are posed by users in any time, it is impossible to make accurate prediction and update caches in time. Therefore, we propose an IBP based reactivecaching strategy. [PERSON] et al. proved that the influence of user's content selection by other users can be modeled by Indian Buffet Process (IBP) [10]. IBP defines a probability distribution over equivalence classes of sparse binary matrices with a finite number of rows and an unbounded number of columns [11]. In our model, we firstly construct a reliable D2D communication network according to geographical closeness between devices as in [10]. Then devices in the reliable D2D communication network are grouped into several social communities according to interaction between devices and ranked by their node importance to community. The caching decision is made by BS depending on contribution degree, which is calculated by BS according to IBP. The contributions of this paper are as follows:  
* To provide high quality D2D communication links, a reliable D2D communication network is constructed according to physical closeness. Then devices are divided into several social communities according to their interactions and ranked by node importance.
* We propose an IBP based social-aware caching strategy. Within a community, BS makes caching decision for devices according to the contribution of caching content to other devices. Contribution degree is defined to measure the contribution and calculated from IBP.
* Finally, we study the performance of proposed strategy and compare it with other strategies in terms of cache hit ratio and sum rate. The simulation results show that IBPSC strategy achieves better performance, especially in the condition of small cache size and large parameter \(\alpha\).  
The rest of the paper is organized as follows: We give an overview of related works in Section 2. Section 3 introduces an IBP based socially-aware D2D (IBPSC) caching strategy. Section 4 presents the simulation results. Finally, Section 5 concludes the paper.