Age Minimization in Energy Harvesting Communications: Energy-Controlled Delays

We consider an energy harvesting source that is collecting measurements from a physical phenomenon and sending updates to a destination within a communication session time. Updates incur transmission delays that are function of the energy used in their transmission. The more transmission energy used per update, the faster it reaches the destination. The goal is to transmit updates in a timely manner, namely, such that the total age of information is minimized by the end of the communication session, subject to energy causality constraints. We consider two variations of this problem. In the first setting, the source controls the number of measurement updates, their transmission times, and the amounts of energy used in their transmission (which govern their delays, or service times, incurred). In the second setting, measurement updates externally arrive over time, and therefore the number of updates becomes fixed, at the expense of adding data causality constraints to the problem. We characterize age-minimal policies in the two settings, and discuss the relationship of the age of information metric to other metrics used in the energy harvesting literature.Comment: Appeared in Asilomar 201

Energy Harvesting Networks with General Utility Functions: Near Optimal Online Policies

We consider online scheduling policies for single-user energy harvesting communication systems, where the goal is to characterize online policies that maximize the long term average utility, for some general concave and monotonically increasing utility function. In our setting, the transmitter relies on energy harvested from nature to send its messages to the receiver, and is equipped with a finite-sized battery to store its energy. Energy packets are independent and identically distributed (i.i.d.) over time slots, and are revealed causally to the transmitter. Only the average arrival rate is known a priori. We first characterize the optimal solution for the case of Bernoulli arrivals. Then, for general i.i.d. arrivals, we first show that fixed fraction policies [Shaviv-Ozgur] are within a constant multiplicative gap from the optimal solution for all energy arrivals and battery sizes. We then derive a set of sufficient conditions on the utility function to guarantee that fixed fraction policies are within a constant additive gap as well from the optimal solution.Comment: To appear in the 2017 IEEE International Symposium on Information Theory. arXiv admin note: text overlap with arXiv:1705.1030

Age-Minimal Transmission in Energy Harvesting Two-hop Networks

We consider an energy harvesting two-hop network where a source is communicating to a destination through a relay. During a given communication session time, the source collects measurement updates from a physical phenomenon and sends them to the relay, which then forwards them to the destination. The objective is to send these updates to the destination as timely as possible; namely, such that the total age of information is minimized by the end of the communication session, subject to energy causality constraints at the source and the relay, and data causality constraints at the relay. Both the source and the relay use fixed, yet possibly different, transmission rates. Hence, each update packet incurs fixed non-zero transmission delays. We first solve the single-hop version of this problem, and then show that the two-hop problem is solved by treating the source and relay nodes as one combined node, with some parameter transformations, and solving a single-hop problem between that combined node and the destination.Comment: Appeared in IEEE Globecom 201

Energy Cooperation in Energy Harvesting Communication Systems

In energy harvesting communications, users transmit messages using energy harvested from nature. In such systems, transmission policies of the users need to be carefully designed according to the energy arrival profiles. When the energy management policies are optimized, the resulting performance of the system depends only on the energy arrival profiles. In this dissertation, we introduce and analyze the notion of energy cooperation in energy harvesting communications where users can share a portion of their harvested energy with the other users via wireless energy transfer. This energy cooperation enables us to control and optimize the energy arrivals at users to the extent possible. In the classical setting of cooperation, users help each other in the transmission of their data by exploiting the broadcast nature of wireless communications and the resulting overheard information. In contrast to the usual notion of cooperation, which is at the signal level, energy cooperation we introduce here is at the battery energy level. In a multi-user setting, energy may be abundant in one user in which case the loss incurred by transferring it to another user may be less than the gain it yields for the other user. It is this cooperation that we explore in this dissertation for several multi-user scenarios, where energy can be transferred from one user to another through a separate wireless energy transfer unit. We first consider the offline optimal energy management problem for several basic multi-user network structures with energy harvesting transmitters and one-way wireless energy transfer. In energy harvesting transmitters, energy arrivals in time impose energy causality constraints on the transmission policies of the users. In the presence of wireless energy transfer, energy causality constraints take a new form: energy can flow in time from the past to the future for each user, and from one user to the other at each time. This requires a careful joint management of energy flow in two separate dimensions, and different management policies are required depending on how users share the common wireless medium and interact over it. In this context, we analyze several basic multi-user energy harvesting network structures with wireless energy transfer. To capture the main trade-offs and insights that arise due to wireless energy transfer, we focus our attention on simple two- and three-user communication systems, such as the relay channel, multiple access channel and the two-way channel. Next, we focus on the delay minimization problem for networks. We consider a general network topology of energy harvesting and energy cooperating nodes. Each node harvests energy from nature and all nodes may share a portion of their harvested energies with neighboring nodes through energy cooperation. We consider the joint data routing and capacity assignment problem for this setting under fixed data and energy routing topologies. We determine the joint routing of energy and data in a general multi-user scenario with data and energy transfer. Next, we consider the cooperative energy harvesting diamond channel, where the source and two relays harvest energy from nature and the physical layer is modeled as a concatenation of a broadcast and a multiple access channel. Since the broadcast channel is degraded, one of the relays has the message of the other relay. Therefore, the multiple access channel is an extended multiple access channel with common data. We determine the optimum power and rate allocation policies of the users in order to maximize the end-to-end throughput of this system. Finally, we consider the two-user cooperative multiple access channel with energy harvesting users. The users cooperate at the physical layer (data cooperation) by establishing common messages through overheard signals and then cooperatively sending them. For this channel model, we investigate the effect of intermittent data arrivals to the users. We find the optimal offline transmit power and rate allocation policy that maximize the departure region. When the users can further cooperate at the battery level (energy cooperation), we find the jointly optimal offline transmit power and rate allocation policy together with the energy transfer policy that maximize the departure region