Cross-Layer Optimization of Fast Video Delivery in Cache-Enabled Relaying Networks

This paper investigates the cross-layer optimization of fast video delivery and caching for minimization of the overall video delivery time in a two-hop relaying network. The half-duplex relay nodes are equipped with both a cache and a buffer which facilitate joint scheduling of fetching and delivery to exploit the channel diversity for improving the overall delivery performance. The fast delivery control is formulated as a two-stage functional non-convex optimization problem. By exploiting the underlying convex and quasi-convex structures, the problem can be solved exactly and efficiently by the developed algorithm. Simulation results show that significant caching and buffering gains can be achieved with the proposed framework, which translates into a reduction of the overall video delivery time. Besides, a trade-off between caching and buffering gains is unveiled.Comment: 7 pages, 4 figures; accepted for presentation at IEEE Globecom, San Diego, CA, Dec. 201

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

Cloud-Edge Non-Orthogonal Transmission for Fog Networks with Delayed CSI at the Cloud

In a Fog Radio Access Network (F-RAN), the cloud processor (CP) collects channel state information (CSI) from the edge nodes (ENs) over fronthaul links. As a result, the CSI at the cloud is generally affected by an error due to outdating. In this work, the problem of content delivery based on fronthaul transmission and edge caching is studied from an information-theoretic perspective in the high signal-to-noise ratio (SNR) regime. For the set-up under study, under the assumption of perfect CSI, prior work has shown the (approximate or exact) optimality of a scheme in which the ENs transmit information received from the cloud and cached contents over orthogonal resources. In this work, it is demonstrated that a non-orthogonal transmission scheme is able to substantially improve the latency performance in the presence of imperfect CSI at the cloud.Comment: 5 pages, 4 figures, submitte