Over the past decade, the bulk of wireless traffic has shifted from speech to content. This shift creates the opportunity to cache part of the content in memories closer to the end users, for example in base stations. Most of the prior literature focuses on the reduction of load in the backhaul and core networks due to caching, i.e., on the benefits caching offers for the wireline communication link between the origin server and the caches. In this paper, we are instead interested in the benefits caching can offer for the wireless communication link between the caches and the end users. To quantify the gains of caching for this wireless link, we consider an interference channel in which each transmitter is equipped with an isolated cache memory. Communication takes place in two phases, a content placement phase followed by a content delivery phase. The objective is to design both the placement and the delivery phases to maximize the rate in the delivery phase in response to any possible user demands. Focusing on the three-user case, we show that through careful joint design of these phases, we can reap three distinct benefits from caching: a load balancing gain, an interference cancellation gain, and an interference alignment gain. In our proposed scheme, load balancing is achieved through a specific file splitting and placement, producing a particular pattern of content overlap at the caches. This overlap allows to implement interference cancellation. Further, it allows us to create several virtual transmitters, each transmitting a part of the requested content, which increases interference-alignment possibilities.
Other papers consider the wireless delivery as well. The load-balancing benefits of caching in ad-hoc wireless networks is investigated in @cite_5 . @cite_12 , content placement is optimized assuming a fixed capacity at each small cell, which is justified for orthogonal wireless multiple-access. @cite_4 focuses on device-to-device wireless networks, in which devices are equipped with a limited cache memory and may opportunistically download the requested file from caches of neighboring devices. @cite_20 , caching the same content at the base stations is suggested to improve the overall throughput by inducing cooperation among transmitters, and in @cite_21 the availability of common files at different devices is exploited to match transmitters with receivers such that treating interference as noise is approximately optimal.
@cite_4 @cite_21 @cite_5 @cite_12 @cite_20
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We consider a wireless device-to-device (D2D) network where the nodes have precached information from a library of available files. Nodes request files at random. If the requested file is not in the on-board cache, then it is downloaded from some neighboring node via one-hop local communication. An outage event occurs when a requested file is not found in the neighborhood of the requesting node, or if the network admission control policy decides not to serve the request. We characterize the optimal throughput-outage tradeoff in terms of tight scaling laws for various regimes of the system parameters, when both the number of nodes and the number of files in the library grow to infinity. Our analysis is based on Gupta and Kumar protocol model for the underlying D2D wireless network, widely used in the literature on capacity scaling laws of wireless networks without caching. Our results show that the combination of D2D spectrum reuse and caching at the user nodes yields a per-user throughput independent of the number of users, for any fixed outage probability in (0, 1). This implies that the D2D caching network is scalable: even though the number of users increases, each user achieves constant throughput. This behavior is very different from the classical Gupta and Kumar result on ad hoc wireless networks, for which the per-user throughput vanishes as the number of users increases. Furthermore, we show that the user throughput is directly proportional to the fraction of cached information over the whole file library size. Therefore, we can conclude that D2D caching networks can turn memory into bandwidth (i.e., doubling the on-board cache memory on the user devices yields a 100 increase of the user throughout). In this paper, we study the impact of caching on a recently-proposed spectrum sharing mechanism for device-to-device networks, ITLinQ, which schedules communication based on information-theoretic optimality principles. We provide a lower bound on the spectral reuse (the fraction of users simultaneously scheduled in the ITLinQ framework) as a function of the caching redundancy by proposing a greedy algorithm for source-user association and determining its achievable reuse. In order to demonstrate that higher spectral reuse also results in more efficient communication, we numerically evaluate the rates achieved by our scheme and show that it provides substantial throughput gain over the state-of-the-art. We consider the problem of delivering content cached in a wireless network of n nodes randomly located on a square of area n. The network performance is described by the 2n × n-dimensional caching capacity region of the wireless network. We provide an inner bound on this caching capacity region, and, in the high path-loss regime, a matching (in the scaling sense) outer bound. For large path-loss exponent, this provides an information-theoretic scaling characterization of the entire caching capacity region. The proposed communication scheme achieving the inner bound shows that the problems of cache selection and channel coding can be solved separately without loss of order-optimality. On the other hand, our results show that the common architecture of nearest-neighbor cache selection can be arbitrarily bad, implying that cache selection and load balancing need to be performed jointly. Small cells constitute a promising solution for managing the mobile data growth that has overwhelmed network operators. Local caching of popular content items at the small cell base stations (SBSs) has been proposed to decrease the costly transmissions from the macrocell base stations without requiring high capacity backhaul links for connecting the SBSs with the core network. However, the caching policy design is a challenging problem especially if one considers realistic parameters such as the bandwidth capacity constraints of the SBSs that can be reached in congested urban areas. We consider such a scenario and formulate the joint routing and caching problem aiming to maximize the fraction of content requests served locally by the deployed SBSs. This is an NP-hard problem and, hence, we cannot obtain an optimal solution. Thus, we present a novel reduction to a variant of the facility location problem, which allows us to exploit the rich literature of it, to establish algorithms with approximation guarantees for our problem. Although the reduction does not ensure tight enough bounds in general, extensive numerical results reveal a near-optimal performance that is even up to 38 better compared to conventional caching schemes using realistic system settings. We propose a novel MIMO cooperation framework called the cache-induced opportunistic cooperative MIMO (Coop-MIMO) for video streaming in backhaul limited multicell MIMO networks. By caching a portion of the video files, the base stations (BSs) opportunistically employ Coop-MIMO transmission to achieve MIMO cooperation gain without expensive payload backhaul. We derive closed form expressions of various video streaming performance metrics for cache-induced opportunistic Coop-MIMO and investigate the impact of BS level caching and key system parameters on the performance. Specifically, we first obtain a mixed fluid-diffusion limit for the playback buffer queueing system. Then we derive the approximated video streaming performance using the mixed fluid-diffusion limit. Based on the performance analysis, we formulate the joint optimization of cache control and playback buffer management as a stochastic optimization problem. Then we derive a closed form solution for the playback buffer thresholds and develop a stochastic subgradient algorithm to find the optimal cache control. The analysis shows that the video streaming performance improves linearly with the BS cache size BC, the transmit power cost decreases exponentially with BC, and the backhaul cost decreases linearly with BC.