Caching with Unknown Popularity Profiles in Small Cell Networks

Abstract

Abstract-A heterogenous network is considered where the base stations (BSs), small base stations (SBSs) and users are distributed according to independent Poisson point processes (PPPs). We let the SBS nodes to posses high storage capacity and are assumed to form a distributed caching network. Popular data files are stored in the local cache of SBS, so that users can download the desired files from one of the SBS in the vicinity subject to availability. The offloading-loss is captured via a cost function that depends on a random caching strategy proposed in this paper. The cost function depends on the popularity profile, which is, in general, unknown. In this work, the popularity profile is estimated at the BS using the available instantaneous demands from the users in a time interval [0, τ ]. This is then used to find an estimate of the cost function from which the optimal random caching strategy is devised. The main results of this work are the following: First it is shown that the waiting time τ to achieve an ǫ > 0 difference between the achieved and optimal costs is finite, provided the user density is greater than a predefined threshold. In this case, τ is shown to scale as N 2 , where N is the support of the popularity profile. Secondly, a transfer learning-based approach is proposed to obtain an estimate of the popularity profile used to compute the empirical cost function. A condition is derived under which the proposed transfer learning-based approach performs better than the random caching strategy.

The role of caching in next generation cellular networks: A survey and research outlook

“…Such networks offer an important applications area for local content caching by using the SBSs as cache storage units at the edge of the network. In other works, 48,[145][146][147][148][149][150][151][152][153] small cell network proactive caching has been studied. A distributed cache placement problem is recently studied in the work of Shanmugam et al 153 with an aim to reduce the delay in delivering the files to the end user; whereas, in the work of Blasco and Gunduz, 146 a single SBS cache content placement problem was addressed from a reinforcement learning perspective.…”

Joint and Competitive Caching Designs in Large-Scale Multi-Tier Wireless Multicasting Networks

“…file popularity) refers to the design in which each POA in tier j randomly stores K j files, in an i.i.d. manner with file n being selected with probability a n [31]. Baseline 3 (hybrid caching) refers to the hybrid caching design obtained by Algrithm 2 in [21].…”

Analysis and Optimization of Random Cache in Multi-Antenna HetNets with Interference Nulling

“…Recently, contrasted to traditional grid model, a random network model based on Poisson point processes (PPPs) has been widely applied in cache-enabled small cell networks to characterize the irregularity and randomness of base station (BS) locations [3]- [6]. These works proposed and analyzed some traditional cache placement schemes, such as the most popular cache (MPC) scheme [3] [4], the uniform cache (UC) scheme [5] and the i.i.d.…”

“…These works proposed and analyzed some traditional cache placement schemes, such as the most popular cache (MPC) scheme [3] [4], the uniform cache (UC) scheme [5] and the i.i.d. cache (IIDC) scheme [6]. However, these cache schemes [3]- [6] cannot sufficiently exploit the finite storage capacity, and may not yield optimal network performance.…”

“…cache (IIDC) scheme [6]. However, these cache schemes [3]- [6] cannot sufficiently exploit the finite storage capacity, and may not yield optimal network performance. In contrast, random cache (RC) scheme has been proved to achieve better performance by leveraging file diversity and file popularity.…”