Optimizing Caching Policy at Base Stations by Exploiting User Preference and Spatial Locality

Most prior works of proactive caching at wireless edge optimize caching policies under the following assumptions: the preference of each user is identical to content popularity, all users request contents with the same active level and at uniformly-distributed locations. In this paper, we investigate what happens without these assumptions. To this end, we establish a framework to optimize caching policy at base stations exploiting user preference, active level, and spatial locality. We obtain optimal caching policy to minimize the weighted sum of the file download time averaged over all file requests and user locations in the network (reflecting network performance) and the maximal weighted download time averaged over possible file requests and locations of each user (reflecting user fairness). To investigate how user preference similarity and active level skewness affect the optimal caching policy, we then provide a method to synthesize user preference for given content popularity and user active level. The analysis and simulation results show that exploiting user preference can improve both network performance and user fairness remarkably compared with priori works. The gain of exploiting user preference increases with user preference heterogeneity, user spatial locality, and skewness of user active level. Index Terms Caching policy, user preference, content popularity, spatial locality, active level.