The Throughput-Outage Tradeoff of Wireless One-Hop Caching Networks

Abstract

We consider a wireless device-to-device (D2D) network where the nodes have pre-cached information from a library of available files. Nodes request files at random. If the requested file is not in the onboard 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).

Fundamental Limits of Caching in Wireless D2D Networks

“…1) if each node in the network can reach in a single hop all other nodes in the network, the proposed scheme achieves almost the same throughput of [10], without the need of a central base station; 2) if the transmission range of each node is limited, such that concurrent short range transmissions can co-exist in a spatial reuse scheme, then the throughput has the same scaling law (with possibly different leading term constants) of the reuse-only case [5], [8] or the coded-only case [10]. This result holds even if one optimizes the transmission range and therefore the spatial reuse of the system.…”

“…Motivated by the above question, in this paper we consider the same model of D2D wireless networks as in [5], [8], with a caching and delivery scheme inspired by [10], based on subpacketization in the caching phase and (inter-session) coding in the delivery phase. Our main contributions are as follows:…”

“…Hence, it is apparent that a conventional system is not able to exploit the inherent "content reuse" in the system, i.e., the fact that a large number of users ask for a limited number of library files. In contrast, both the caching approaches of [5], [8] and of [10] yield Θ M m , which is a much better scaling for nM m, i.e., in the regime of highly redundant demands, for which caching is expected to be efficient. Notably, the per-user throughput in both caching schemes scales linearly with the per-user cache memory size M , which is expected to grow with time according to Moore's law of VLSI integration.…”

“…The D2D approach of [5], [8] capitalizes on of the spatial reuse of D2D achieved by local communication, while the approach of [10] exploits global communication in order to multicast the coded messages, simultaneously useful to a large number of users. A natural question at this point is whether any further gain can be obtained by combining spatial reuse and coded multicasting.…”

“…In [5], [8] we studied a one-hop Device-to-Device (D2D) communication network with caching at the user nodes. The network is formed by n user nodes, each of which stores M files from a library of m files.…”