On the Delay of Geographical Caching Methods in Two-Tiered Heterogeneous Networks

We consider a hierarchical network that consists of mobile users, a two-tiered cellular network (namely small cells and macro cells) and central routers, each of which follows a Poisson point process (PPP). In this scenario, small cells with limited-capacity backhaul are able to cache content under a given set of randomized caching policies and storage constraints. Moreover, we consider three different content popularity models, namely fixed content popularity, distance-dependent and load-dependent, in order to model the spatio-temporal behavior of users' content request patterns. We derive expressions for the average delay of users assuming perfect knowledge of content popularity distributions and randomized caching policies. Although the trend of the average delay for all three content popularity models is essentially identical, our results show that the overall performance of cached-enabled heterogeneous networks can be substantially improved, especially under the load-dependent content popularity model.Comment: to be presented at IEEE SPAWC'2016, Edinburgh, U

Cost-Effective Cache Deployment in Mobile Heterogeneous Networks

This paper investigates one of the fundamental issues in cache-enabled heterogeneous networks (HetNets): how many cache instances should be deployed at different base stations, in order to provide guaranteed service in a cost-effective manner. Specifically, we consider two-tier HetNets with hierarchical caching, where the most popular files are cached at small cell base stations (SBSs) while the less popular ones are cached at macro base stations (MBSs). For a given network cache deployment budget, the cache sizes for MBSs and SBSs are optimized to maximize network capacity while satisfying the file transmission rate requirements. As cache sizes of MBSs and SBSs affect the traffic load distribution, inter-tier traffic steering is also employed for load balancing. Based on stochastic geometry analysis, the optimal cache sizes for MBSs and SBSs are obtained, which are threshold-based with respect to cache budget in the networks constrained by SBS backhauls. Simulation results are provided to evaluate the proposed schemes and demonstrate the applications in cost-effective network deployment

Resource allocation for cache-enabled cloud-based small cell networks

To address the serious challenge of satisfying explosively increasing multimedia content requests from a massive number of users in mobile networks, deploying content caching in base stations to offload network traffic while satisfying content requests locally has been regarded as an effective approach to enhance the network performance. Moreover, content delivery via wireless transmissions in a cache-enabled mobile network needs to be optimized taking the proactive caching policy into consideration. Accordingly, in this paper, we investigate and propose an efficient resource allocation framework for cache-enabled cloud-based small cell networks (C-SCNs) to achieve the benefits of content caching by considering two phases, i.e., content placement and content delivery. In particular, for the content placement phase, we propose a low-complexity distributed popularity-based framework for allocating cache sizes of SBSs to popular contents, in order to offload network traffic and satisfy content requests locally. For the content delivery phase, we propose a low-complexity joint user association and subcarrier-power allocation scheme for min-rate guaranteed content delivery over orthogonal frequency division multiple access (OFDMA) based downlink transmissions. Trace-based simulations and numerical results demonstrate the effectiveness of the proposed schemes in the cache-enabled C-SCNs

Caching UAV-enabled small-cell networks

Unmanned aerial vehicles (UAVs) can be utilized to provide flexible wireless access in future wireless networks, with larger coverage and higher transmission rate. However, the wireless backhaul for UAVs is usually capacity-limited and congested, and UAVs cannot operate for a long time due to the limited battery life. In this paper, a framework of caching UAV-enabled small-cell networks is proposed, to offload data traffic for the small-cell base stations via caching. In the proposed scheme, the most popular contents are stored at the local caches of UAVs in advance, which can be delivered to mobile users directly from the caches when required. Thus, the congestion of wireless backhaul can be alleviated, the energy consumption can be reduced, and the quality of experience can be improved

Wireless Communications in the Era of Big Data

The rapidly growing wave of wireless data service is pushing against the boundary of our communication network's processing power. The pervasive and exponentially increasing data traffic present imminent challenges to all the aspects of the wireless system design, such as spectrum efficiency, computing capabilities and fronthaul/backhaul link capacity. In this article, we discuss the challenges and opportunities in the design of scalable wireless systems to embrace such a "bigdata" era. On one hand, we review the state-of-the-art networking architectures and signal processing techniques adaptable for managing the bigdata traffic in wireless networks. On the other hand, instead of viewing mobile bigdata as a unwanted burden, we introduce methods to capitalize from the vast data traffic, for building a bigdata-aware wireless network with better wireless service quality and new mobile applications. We highlight several promising future research directions for wireless communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications Magazin