Mitigating Interference in Content Delivery Networks by Spatial Signal Alignment: The Approach of Shot-Noise Ratio

摘要

Multimedia content especially videos is expected to dominate data traffic innext-generation mobile networks. Caching popular content at the network edgehas emerged to be a solution for low-latency content delivery. Compared withthe traditional wireless communication, content delivery has a keycharacteristic that many signals coexisting in the air carry identical popularcontent. They, however, can interfere with each other at a receiver if theirmodulation-and-coding (MAC) schemes are adapted to individual channelsfollowing the classic approach. To address this issue, we present a novel ideaof content adaptive MAC (CAMAC) where adapting MAC schemes to content ensuresthat all signals carry identical content are encoded using an identical MACscheme, achieving spatial MAC alignment. Consequently, interference can beharnessed as signals, to improve the reliability of wireless delivery. In theremaining part of the paper, we focus on quantifying the gain CAMAC can bringto a content-delivery network using a stochastic-geometry model. Specifically,content helpers are distributed as a Poisson point process, each of whichtransmits a file from a content database based on a given popularitydistribution. It is discovered that the successful content-delivery probabilityis closely related to the distribution of the ratio of two independent shotnoise processes, named a shot-noise ratio. The distribution itself is an openmathematical problem that we tackle in this work. Using stable-distributiontheory and tools from stochastic geometry, the distribution function is derivedin closed form. Extending the result in the context of content-deliverynetworks with CAMAC yields the content-delivery probability in different closedforms. In addition, the gain in the probability due to CAMAC is shown to growwith the level of skewness in the content popularity distribution.