Caching In Cellular Networks Research Articles

Interference-aware scheme to improve distributed caching in cellular networks via D2D underlay communications

Underlay Device-to-Device (D2D) communications is a promising networking technology intended to boost thespectral efficiency of future cellular networks, including 5G and beyond. When used for distributed caching, where cellulardevices store popular files for direct exchange later with other devices away from the cellular infrastructure, the technologybears more fruits such as enhancing throughput, reducing latency and offloading the infrastructure. However, due to theirnon-orthogonality, underlay D2D communications can result in excessive interference to the cellular user. To avoid thisproblem, the present article proposes a scheme with two interference-reduction elements: a guard zone intended to allowD2D communications only for devices far enough from the base station (BS), and a pairing strategy intended to allow D2Dpairing for only devices that are close enough to each other. We assess the performance of the scheme using a stochasticgeometry (SG) model, through which we characterize the coverage probability of the cellular user. This probability is aprincipal indicator of maintaining the quality of service (QoS) of the cellular user and of enabling successful caching for theD2D user. We introduce in the process a novel empirical technique which, given a desired level of interference, identifiesan upper bound for the distance between two devices to be paired without exceeding that level. We finally validate theanalytical findings obtained from the model by intensive simulation to ensure the correctness of both the model and thescheme performance. A salient feature of the scheme is that it requires for its implementation no software or hardwaremodification in the device

Data Repair-Efficient Fault Tolerance for Cellular Networks Using LDPC Codes

The base station-mobile device communication traffic has dramatically increased recently due to mobile data, which in turn heavily overloaded the underlying infrastructure. To decrease Base Station (BS) interaction, intra-cell communication between local devices, known as Device-to-Device, is utilized for distributed data caching. Nevertheless, due to the continuous departure of existing nodes and the arrival of newcomers, the missing cached data may lead to permanent data loss. In this study, we propose and analyze a class of Low-Density Parity Check (LDPC) codes for distributed data caching in cellular networks. Contrary to traditional distributed storage, a novel repair algorithm for LDPC codes is proposed which is designed to exploit the minimal direct BS communication. To assess the versatility of LDPC codes and establish performance comparisons to classic coding techniques, novel theoretical and experimental evaluations are derived. Essentially, the theoretical/numerical results for repair bandwidth cost in presence of BS are presented in a distributed caching setting. Accordingly, when the gap between the cost of downloading a symbol from BS and from other local network nodes is not dramatically high, we demonstrate that LDPC codes can be considered as a viable fault-tolerance alternative in cellular systems with caching capabilities for both low and high code rates.

Cache-Enabled Millimeter Wave Cellular Networks With Clusters

Wireless content caching in cellular networks is an efficient way to reduce the service delay and alleviate backhaul pressure. For the benefits of sharing spectral and storage resources, clustering in cached networks has recently attracted significant research interests. Meanwhile, since the multimedia content (e.g., video) of caching networks may require a huge transmission rates, millimeter wave (mmWave) communication is considered to be an efficient transmission scheme for cache-enabled networks. We investigate the ergodic rate and average service delay for typical user terminal (UT) in the clustered cache-enabled small cell networks (SCN) and ultra dense networks (UDN) with mmWave channels. In SCN, each cluster consists of cache-enabled UTs, and in the UDN a cluster is formed by cache-enabled UTs and small base stations (SBSs) with non-uniform caching capacity. The clusters are assumed to be discs and content sharing is only possible within clusters through mmWave device-to-device (D2D) tier and SBS tier communications. With stochastic geometry methods, the distributions of content sharing distance and signal-to-interference-noise-ratio (SINR) of typical UT in a cluster are derived for both SCN and UDN scenarios. To minimize the average service delay in high SINR region, we provide an algorithm to jointly optimize caching scheme for SBSs and UTs. By simulations, we validate our theoretical analysis and the performance of proposed caching scheme. The numerical results also show that there exists best radius in the design of cluster for UDNs.

Transcoding Based Video Caching Systems: Model and Algorithm

The explosive demand of online video watching brings huge bandwidth pressure to cellular networks. Efficient video caching is critical for providing high‐quality streaming Video‐on‐Demand (VoD) services to satisfy the rapid increasing demands of online video watching from mobile users. Traditional caching algorithms typically treat individual video files separately and they tend to keep the most popular video files in cache. However, in reality, one video typically corresponds to multiple different files (versions) with different sizes and also different video resolutions. Thus, caching of such files for one video leads to a lot of redundancy since one version of a video can be utilized to produce other versions of the video by using certain video coding techniques. Recently, fog computing pushes computing power to edge of network to reduce distance between service provider and users. In this paper, we take advantage of fog computing and deploy cache system at network edge. Specifically, we study transcoding based video caching in cellular networks where cache servers are deployed at the edge of cellular network for providing improved quality of online VoD services to mobile users. By using transcoding, a cached video can be used to convert to different low‐quality versions of the video as needed by different users in real time. We first formulate the transcoding based caching problem as integer linear programming problem. Then we propose a Transcoding based Caching Algorithm (TCA), which iteratively finds the placement leading to the maximal delay gain among all possible choices. We deduce the computational complexity of TCA. Simulation results demonstrate that TCA significantly outperforms traditional greedy caching algorithm with a decrease of up to 40% in terms of average delivery delay.

A Low-Complexity Approach to Distributed Cooperative Caching with Geographic Constraints

We consider caching in cellular networks in which each base station is equipped with a cache that can store a limited number of files. The popularity of the files is known and the goal is to place files in the caches such that the probability that a user at an arbitrary location in the plane will find the file that she requires in one of the covering caches is maximized. We develop distributed asynchronous algorithms for deciding which contents to store in which cache. Such cooperative algorithms require communication only between caches with overlapping coverage areas and can operate in asynchronous manner. The development of the algorithms is principally based on an observation that the problem can be viewed as a potential game. Our basic algorithm is derived from the best response dynamics. We demonstrate that the complexity of each best response step is independent of the number of files, linear in the cache capacity and linear in the maximum number of base stations that cover a certain area. Then, we show that the overall algorithm complexity for a discrete cache placement is polynomial in both network size and catalog size. In practical examples, the algorithm converges in just a few iterations. Also, in most cases of interest, the basic algorithm finds the best Nash equilibrium corresponding to the global optimum. We provide two extensions of our basic algorithm based on stochastic and deterministic simulated annealing which find the global optimum. Finally, we demonstrate the hit probability evolution on real and synthetic networks numerically and show that our distributed caching algorithm performs significantly better than storing the most popular content, probabilistic content placement policy and Multi-LRU caching policies.

Throughput Analysis of Decentralized Coded Content Caching in Cellular Networks

Decentralized coded content caching for next generation cellular networks is studied. The contents are linearly combined and cached in under-utilized caches of user terminals and its throughput capacity is compared with decentralized uncoded content caching. In both scenarios, we consider multihop device-to-device communications and the use of femtocaches in the network. It is shown that decentralized coded content caching can increase the network throughput capacity compared to decentralized uncoded caching by reducing the number of hops needed to deliver the desired content. Furthermore, the throughput capacity for Zipfian content request distribution is computed and it is shown that the decentralized coded content cache placement can increase the throughput capacity of cellular networks by a factor of $(\log (n))^{2}$ where $n$ is the number of nodes served by a femtocache.

Caching resource sharing in radio access networks: a game theoretic approach

Deployment of caching in wireless networks has been considered an effective method to cope with the challenge brought on by the explosive wireless traffic. Although some research has been conducted on caching in cellular networks, most of the previous works have focused on performance optimization for content caching. To the best of our knowledge, the problem of caching resource sharing for multiple service provider servers (SPSs) has been largely ignored. In this paper, by assuming that the caching capability is deployed in the base station of a radio access network, we consider the problem of caching resource sharing for multiple SPSs competing for the caching space. We formulate this problem as an oligopoly market model and use a dynamic non-cooperative game to obtain the optimal amount of caching space needed by the SPSs. In the dynamic game, the SPSs gradually and iteratively adjust their strategies based on their previous strategies and the information given by the base station. Then through rigorous mathematical analysis, the Nash equilibrium and stability condition of the dynamic game are proven. Finally, simulation results are presented to show the performance of the proposed dynamic caching resource allocation scheme.