Emergent Mind

Abstract

We consider a wireless device-to-device (D2D) caching network where n nodes are placed on a regular grid of area A(n). Each node caches L_CF (coded) bits from a library of size LF bits, where L is the number of files and F is the size of each file. Each node requests a file from the library independently according to a popularity distribution. Under a commonly used "physical model" and Zipf popularity distribution, we characterize the optimal per-node capacity scaling law for extended networks (i.e., A(n). Moreover, we propose a cache-induced hierarchical cooperation scheme and associated cache content placement optimization algorithm to achieve the optimal per-node capacity scaling law. When the path loss exponent \alpha<3, the optimal per-node capacity scaling law achieved by the cache-induced hierarchical cooperation can be significantly better than that achieved by the existing state-of-the-art schemes. To the best of our knowledge, this is the first work that completely characterizes the per-node capacity scaling law for wireless caching networks under the physical model and Zipf distribution with an arbitrary skewness parameter \tau. While scaling law analysis yields clean results, it may not accurately reflect the throughput performance of a large network with a finite number of nodes. Therefore, we also analyze the throughput of the proposed cache-induced hierarchical cooperation for networks of practical size. The analysis and simulations verify that cache-induced hierarchical cooperation can also achieve a large throughput gain over the cache-assisted multihop scheme for networks of practical size.

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