## 1 Introduction  
Inspired by the development of intelligent terminal such as smart phones, the demand for data traffic in mobile communication systems is exponentially growing. To cater for this demand, a 1000-fold improvement of capacity per area in the next generation of mobile communication system (5G) compared to 4G is required. An Ultra-Dense Network (UDN) is capable of significantly improving the capacity per area under the limited spectrum resource due to the high splitting-gain of densely located small cells and is widely considered as one of the most promising techniques in the coming 5G. It also benefits load balance between Base Stations (BSs) since Small Base Stations (SBSs) can offload data traffic of Macro Base Stations (MBSs). Nevertheless, due to the short distance between BSs, the intercell interference in UDNs is severe, therefore making the user experience unsatisfactory. Coordinated Multi-Point (CoMP) transmissions technique is widely studied in academia and the industry, which can leverage the cooperation of multiple BSs to enhance the signal to interference and noise ratio (SINR), to counteract intercell interference and to enhance network capacity in UDNs. Despite remarkable performance gain in network capacity, congestion on backhaul links caused by CoMP risks the mobile communication systems. In order to cooperatively serve users, BSs need to fetch more files from the Core Network (CN) via backhaul links in a CoMP-employed system, which brings heavy load to backhaul links between BSs and the CN and probably results in congestion. One way to alleviate backhaul load is to cache popular files on BSs. When BSs cache files requested by users, it does not need to fetch files from the CN, so the backhaul load can be dramatically reduced. In [1], an architecture based on distributed caching of content in SBSs was presented. Works on proactive caching in UDNs concentrate on two major issues: Content placement and content distribution. Content placement focuses on how to distribute popular and hotspot files to the BSs' caching unit whose capacity is limited. In [2], an optimal content placement strategy is proposed to maximize the hit rate. In [3], the problem of content placement is studied to maximize energy efficiency. In [4], an approximation algorithm is proposed to jointly optimize routing and caching policy to maximize the fraction of requested files cached locally. In [5], a distributed algorithm is proposed to investigate content placement and user association jointly. In [6], a content placement strategy is investigated based on reinforcement learning. In [7], a content placement strategy is proposed under cooperation schemes of maximum ratio transmission (MRT) and zero-forcing beamforming (ZFBF). In [8], a caching space allocation scheme is proposed to improve the hit rate based on the categories of contents and UEs. Content distribution is the study of how to associate UEs and BSs to improve the hit rate. In [9], the user association problem is modeled as an one-to-many game problem, based on which algorithm is proposed to maximize the average download rate under a given content placement strategy. In [10], an user association algorithm under a given content distribution in a CoMP enabled network is proposed to minimize the backhaul load under a guaranteed rate requirements of UEs. In [11], the content caching and user association schemes are proposed on two different scales: The caching algorithm operates in a long time scale and the user association algorithm operates frequently. In [12], user association is investigated to tradeoff between load balancing and backhaul savings in UDN. To the best of our knowledge, related works on the content placement caching and user association have been investigated separately in small-scale networks. We are thus motivated to jointly investigate the tasks of caching and user association in more realistic large-scale UDNs. The main contributions of this paper are summarized as follows.