# Joint Content Recommendation and Delivery in Mobile Wireless Networks with Outage Management
###### Abstract  
Personalized content retrieval service has become a major information service that consumes a large portion of mobile Internet traffic. Joint content recommendation and delivery is a promising design philosophy that could effectively improve the overall user experience with personalized content retrieval services. Existing research mostly focused on a push-type design paradigm called proactive caching, which, however, has multiple inherent drawbacks such as high device cost and low energy efficiency. This paper proposes a novel, interactive joint content recommendation and delivery system as an alternative to overcome the drawbacks of proactive caching systems. We present several optimal and heuristic algorithms for the proposed system and analyze the system performance in terms of user interest and transmission outage probability. Some theoretical performance bounds of the system are also derived. The effectiveness of the proposed system and algorithms is validated by simulation results. content recommendation; content delivery; outage probability; radio resource allocation 2018 2017 2018 2017 2018 2018 2017 2018 2018 2017  
improve the system performance and user experience. For example, in the context of the fixed Internet, it has been shown that CP-level intelligence can be used to improve the performance of traditional CDN networks [6]. In mobile networks, a content-format adaptive system was proposed in [7], which can adapt content formats according to wireless channel conditions. Among the various proposals, joint content recommendation and delivery has emerged as an important class of design that has attracted significant research interest. The underlying philosophy of joint content recommendation and delivery is to exploit the domain of the content file size as a new design space. This is based on the fact that different contents with roughly the same level of user interest may vary dramatically in file size. Such diversity in content file sizes can be exploited to shape the traffic volume, thereby giving content delivery another degree of freedom for performance optimization. For example, a user may have a relatively lower interest in a web page that is ten-times smaller in size than a video clip. When the channel is congested, it is desirable to recommend the web page to avoid causing excessive delays. On the contrary, when the channel is clear, recommendation of the video clip is preferred. In this way, content recommendation can serve as a new mechanism of congestion avoidance in the communication network. This is particularly useful for mobile communication networks, whose capacity is severely limited by the available radio and infrastructure resources. In the literature, most studies on joint content recommendation and delivery in mobile communication networks fall into a category of technologies called proactive caching [8; 9; 10], which can recommend, push and cache contents of interest to the user devices according to the status of communications links. Multiple issues such as energy efficiency [11; 12], multicast support [13; 14], heterogeneous networks [14] and adaptive traffic pricing [15; 16] had been investigated. Although proactive caching technology can help to improve network performance via load balancing and enhance user QoE by reducing content access delay, it also has some inherent drawbacks. First, large caching space is required at the user device, which is not always available in practice. Second, even using the state-of-the-art content recommendation technologies, a significant portion of pushed content will not be viewed by the users due to user behavior uncertainties [17]. This will result in significant waste of network resource and energy consumption. Third, because a portion of pushed contents is unavoidably \"invalid\", traffic pricing also becomes a problematic issue. Apart from the push-type protocols, a few novel \"pull-type\" content retrieval protocols were recently reported in the literature [18; 19; 20; 21; 22].