The fifth generation wireless networks must provide fast and reliable connectivity while coping with the ongoing traffic growth. It is of paramount importance that the required resources, such as energy and bandwidth, do not scale with traffic. While the aggregate network traffic is growing at an unprecedented rate, users tend to request the same popular contents at different time instants. Therefore, caching the most popular contents at the network edge is a promising solution to reduce the traffic and the energy consumption over the backhaul links. In this paper, two scenarios are considered, where caching is performed either at a small base station, or directly at the user terminals, which communicate using Device-to-Device (D2D) communications. In both scenarios, joint design of the transmission and caching policies is studied when the user demands are known in advance. This joint design offers two different caching gains, namely, the pre-downloading and local caching gains. It is shown that the finite cache capacity limits the attainable gains, and creates an inherent tradeoff between the two types of gains. In this context, a continuous time optimization problem is formulated to determine the optimal transmission and caching policies that minimize a generic cost function, such as energy, bandwidth, or throughput. The jointly optimal solution is obtained by demonstrating that caching files at a constant rate is optimal, which allows reformulation of the problem as a finite-dimensional convex program. The numerical results show that the proposed joint transmission and caching policy dramatically reduces the total cost, which is particularised to the total energy consumption at the Macro Base Station (MBS), as well as to the total economical cost for the service provider, when users demand economical incentives for delivering content to other users over the D2D links

We consider a cache network in which a single server is connected to multiple users via a shared error free link. The server has access to a database with N files of equal length F , and serves K users each with a cache memory of M F bits. A novel centralized coded caching scheme is proposed for scenarios with more users than files N ≤ K and cache capacities satisfying 1 K ≤ M ≤ N K . The proposed scheme outperforms the best rate-memory region known in the literature if N ≤ K ≤ N 2 +1 2 .

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Abstract-Demand-side energy management (EM) is studied from a privacy-cost trade-off perspective, considering time-of-use pricing and the presence of an energy storage unit. Privacy is measured as the variation of the power withdrawn from the grid from a fixed target value. Assuming non-causal knowledge of the household's aggregate power demand profile and the electricity prices at the energy management unit (EMU), the privacy-cost trade-off is formulated as a convex optimization problem, and a low-complexity backward water-filling algorithm is proposed to compute the optimal EM policy. The problem is studied also in the online setting assuming that the power demand profile is known to the EMU only causally, and the optimal EM policy is obtained numerically through dynamic programming (DP). Due to the high computational cost of DP, a low-complexity heuristic EM policy with a performance close to the optimal online solution is also proposed, exploiting the water-filling algorithm obtained in the offline setting. As an alternative, information theoretic leakage rate is also evaluated, and shown to follow a similar trend as the load variance, which supports the validity of the load variance as a measure of privacy. Finally, the privacy-cost trade-off, and the impact of the size of the storage unit on this trade-off are studied through numerical simulations using real smart meter data in both the offline and online settings.Index Terms-Smart meter, privacy, demand-side management, energy storage, home energy management.

Smart meters (SMs) measure and report users' energy consumption to the utility provider (UP) in almost realtime, providing a much more detailed depiction of the consumer's energy consumption compared to their analog counterparts. This increased rate of information flow to the UP, together with its many potential benefits, raise important concerns regarding user privacy. This work investigates, from an information theoretic perspective, the privacy that can be achieved in a multi-user SM system in the presence of an alternative energy source (AES). To measure privacy, we use the mutual information rate between the users' real energy consumption profile and the SM readings that are available to the UP. The objective is to characterize the privacy-power function, defined as the minimal information leakage rate that can be obtained with an average power limited AES. We characterize the privacy-power function in a singleletter form when the users' energy demands are assumed to be independent and identically distributed over time. Moreover, for binary and exponentially distributed energy demands, we provide an explicit characterization of the privacy-power function. For any discrete energy demands, we demonstrate that the privacypower function can always be efficiently evaluated numerically. Finally, for continuous energy demands, we derive an explicit lower-bound on the privacy-power function, which is tight for exponentially distributed loads.

Abstract-This paper addresses the energy efficiency analysis of the relay channel under additive white Gaussian noise. We consider the rate bounds given by decode and forward and the cut set bound and assume that resources are optimally allocated to maximize the spectral efficiency according to the channel information and the sum network energy. The low energy analysis tools are used to compute the maximum rate per energy (RPE) and the slope of the spectral efficiency as a function of the energy per bit. Using these metrics, the energy efficiency benefit of several capabilities at terminals is investigated. Specifically, we take into account: i) the phase synchronization between transmitters, ii) the full duplex capability at the relay and iii) the channel access via superposition.Index Terms-Relay channel, energy efficiency, low power communication, wideband regime, receiver constraints, half duplex, synchronism.

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Smart meter (SM) measurements provide near realtime information on the electricity consumption of a user to the utility provider (UP). This data can be used to extract private information on the energy consumption patterns of the user. Assuming that the user has access to an alternative energy source (AES) in addition to the power grid, SM privacy problem is studied from an information theoretic perspective. The energy requirement of the user (input load) at each time instant can be satisfied either from the power grid (output load) or from the AES. It is assumed that the output load can be perfectly tracked by the UP, and the privacy is measured through the information leakage rate. For given average and peak power constraints on the AES, privacy-power function is defined, and its equivalence to the rate-distortion function with a difference distortion measure is shown. Focusing on continuous input loads, the privacy-power function is characterized when there is only peak power limitation on the AES, while the Shannon lower bound is provided for the general case. The bound is shown to be achievable for the exponential input distribution.