Caching at the Edge with LT codes

We study the performance of caching schemes based on LT under peeling (iterative) decoding algorithm. We assume that users ask for downloading content to multiple cache-aided transmitters. Transmitters are connected through a backhaul link to a master node while no direct link exists between users and the master node. Each content is fragmented and coded with LT code. Cache placement at each transmitter is optimized such that transmissions over the backhaul link is minimized. We derive a closed form expression for the calculation of the backhaul transmission rate. We compare the performance of a caching scheme based on LT with respect to a caching scheme based on maximum distance separable codes. Finally, we show that caching with \acl{LT} codes behave as good as caching with maximum distance separable codes

Dynamic Coded Caching in Wireless Networks

We consider distributed and dynamic caching of coded content at small base stations (SBSs) in an area served by a macro base station (MBS). Specifically, content is encoded using a maximum distance separable code and cached according to a time-to-live (TTL) cache eviction policy, which allows coded packets to be removed from the caches at periodic times. Mobile users requesting a particular content download coded packets from SBSs within communication range. If additional packets are required to decode the file, these are downloaded from the MBS. We formulate an optimization problem that is efficiently solved numerically, providing TTL caching policies minimizing the overall network load. We demonstrate that distributed coded caching using TTL caching policies can offer significant reductions in terms of network load when request arrivals are bursty. We show how the distributed coded caching problem utilizing TTL caching policies can be analyzed as a specific single cache, convex optimization problem. Our problem encompasses static caching and the single cache as special cases. We prove that, interestingly, static caching is optimal under a Poisson request process, and that for a single cache the optimization problem has a surprisingly simple solution

Caching in Heterogeneous Networks

A promising solution in order to cope with the massive request of wireless data traffic consists of having replicas of the potential requested content memorized across the network. In cache-enabled heterogeneous networks, content is pre-fetched close to the users during network off-peak periods in order to directly serve the users when the network is congested. In fact, the main idea behind caching is the replacement of backhaul capacity with storage capabilities, for example, at the edge of the network. Caching content at the edge of heterogeneous networks not only leads to significantly reduce the traffic congestion in the backhaul link but also leads to achieve higher levels of energy efficiency. However, the good performance of a system foresees a deep analysis of the possible caching techniques. Due to the physical limitation of the caches’ size and the excessive amount of content, the design of caching policies which define how the content has to be cached and select the likely data to store is crucial. Within this thesis, caching techniques for storing and delivering the content in heterogeneous networks are investigated from two different aspects. The first part of the thesis is focused on the reduction of the power consumption when the cached content is delivered over an Gaussian interference channel and per-file rate constraints are imposed. Cooperative approaches between the transmitters in order to mitigate the interference experienced by the users are analyzed. Based on such approaches, the caching optimization problem for obtaining the best cache allocation solution (in the sense of minimizing the average power consumption) is proposed. The second part of the thesis is focused on caching techniques at packet level with the aim of reducing the transmissions from the core of an heterogeneous network. The design of caching schemes based on rate-less codes for storing and delivering the cached content are proposed. For each design, the placement optimization problem which minimizes the transmission over the backhaul link is formulated

Caching in Heterogeneous Networks

A promising solution in order to cope with the massive request of wireless data traffic consists of having replicas of the potential requested content memorized across the network. In cache-enabled heterogeneous networks, content is pre-fetched close to the users during network off-peak periods in order to directly serve the users when the network is congested. Caching content at the edge of heterogeneous networks not only leads to significantly reduce the traffic congestion in the backhaul link but also leads to achieve higher levels of energy efficiency. However, the good performance of a system foresees a deep analysis of the possible caching techniques. Due to the physical limitation of the caches' size and the excessive amount of content, the design of caching policies which define how the content has to be cached and select the likely data to store is crucial. Within this thesis, caching techniques for storing and delivering the content in heterogeneous networks are investigated from two different aspects. The first part of the thesis is focused on the reduction of the power consumption when the cached content is delivered over an Gaussian interference channel and per-file rate constraints are imposed. Cooperative approaches between the transmitters in order to mitigate the interference experienced by the users are analyzed. Based on such approaches, the caching optimization problem for obtaining the best cache allocation solution (in the sense of minimizing the average power consumption) is proposed. The second part of the thesis is focused on caching techniques at packet level with the aim of reducing the transmissions from the core of an heterogeneous network. The design of caching schemes based on rate-less codes for storing and delivering the cached content are proposed. For each design, the placement optimization problem which minimizes the transmission over the backhaul link is formulated