2,990 research outputs found
Energy Harvesting Communication Networks with System Costs
This dissertation focuses on characterizing optimal energy management policies for energy harvesting communication networks with system costs. The system costs that we consider are the cost of circuitry to be on (processing cost) at the transmitters, cost of decoding at the receivers, cost of moving to harvest more energy in mobile energy harvesting nodes, and the cost of collecting measurements (sampling cost) from physical phenomena.
We first consider receiver decoding costs in networks where receivers, in addition to transmitters, rely on energy harvested from nature to communicate. Energy harvested at the receivers is used to decode their intended messages, and is modeled as a convex increasing function of the incoming rate. With the goal of maximizing throughput by a given deadline, we study single-user and multi-user settings, and show that decoding costs at the receivers can be represented as generalized data arrivals at the transmitters. This introduces a further coupling between the transmitters and receivers of the network and allows us to characterize optimal policies by moving all constraints to the transmitter side.
Next, we study the decoding cost effect on energy harvesting cooperative multiple access channels, where users employ data cooperation to increase their achievable rates. Data cooperation requires each user to decode the other user's data before forwarding it to the destination, which uses up some of the harvested energy. With the presence of decoding costs, we show that data cooperation may not be always helpful; if the decoding costs are relatively high, then sending directly to the receiver without data cooperation between the users achieves higher throughput. When cooperation is helpful, we determine the optimum allocation of available energy between decoding cooperative partner's data and forwarding it to the destination.
We then study the impact of adding processing costs, on top of decoding costs, in energy harvesting two-way channels. Processing costs are the amounts of energy spent for circuitry operation, and are incurred whenever a user is communicating. We show that due to processing costs, transmission may become bursty, where users communicate through only a portion of the time. We develop an optimal scheme that maximizes the sum throughput by a given deadline under both decoding and processing costs.
Next, we focus on online policies. We consider a single-user energy harvesting channel where the transmitter is equipped with a finite-sized battery, and the goal is to maximize the long term average utility, for general concave increasing utility functions. We show that fixed fraction policies are near optimal; they achieve a long term average utility that lies within constant multiplicative and additive gaps from the optimal solution for all battery sizes and all independent and identically distributed energy arrival patterns. We then consider a specific scenario of a utility function that measures the distortion of Gaussian samples communicated over a Gaussian channel. We formulate two problems: one with, and the other without sampling costs, and design near optimal fixed fraction policies for the two problems.
Then, we consider another aspect of costs in energy harvesting single-user channels, that is, the energy spent in physical movement in search of better energy harvesting locations. Since movement has a cost, there exists a tradeoff between staying at the same location and moving to a new one. Staying at the same location allows the transmitter to use all its available energy in transmission, while moving to a new one may let the transmitter harvest higher amounts of energy and achieve higher rates at the expense of a cost incurred through the relocation process. We characterize this tradeoff optimally under both offline and online settings.
Next, we consider different performance metrics, other than throughput, in energy harvesting communication networks. First, we study the issue of delay in single-user and broadcast energy harvesting channels. We define the delay per data unit as the time elapsed from the unit's arrival at the transmitter to its departure. With a pre-specified amount of data to be delivered, we characterize delay minimal energy management policies. We show that the structure of the optimal policy is different from throughput-optimal policies; to minimize the average delay, earlier arriving data units are transmitted using higher powers than later arriving ones, and the transmit power may reach zero, leading to communication gaps, in between energy or data arrival instances.
Finally, we conclude this dissertation by considering the metric of the age of information in energy harvesting two-hop networks, where a transmitter is communicating with a receiver through a relay. Different from delay, the age of information is defined as the time elapsed since the latest data unit has reached the destination. We show that age minimal policies are such that the transmitter sends message updates to the relay just in time as the relay is ready to forward them to the receiver
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
Optimal Resource Allocation in Ultra-low Power Fog-computing SWIPT-based Networks
In this paper, we consider a fog computing system consisting of a
multi-antenna access point (AP), an ultra-low power (ULP) single antenna device
and a fog server. The ULP device is assumed to be capable of both energy
harvesting (EH) and information decoding (ID) using a time-switching
simultaneous wireless information and power transfer (SWIPT) scheme. The ULP
device deploys the harvested energy for ID and either local computing or
offloading the computations to the fog server depending on which strategy is
most energy efficient. In this scenario, we optimize the time slots devoted to
EH, ID and local computation as well as the time slot and power required for
the offloading to minimize the energy cost of the ULP device. Numerical results
are provided to study the effectiveness of the optimized fog computing system
and the relevant challenges
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article summarizes recent contributions in the broad area of energy
harvesting wireless communications. In particular, we provide the current state
of the art for wireless networks composed of energy harvesting nodes, starting
from the information-theoretic performance limits to transmission scheduling
policies and resource allocation, medium access and networking issues. The
emerging related area of energy transfer for self-sustaining energy harvesting
wireless networks is considered in detail covering both energy cooperation
aspects and simultaneous energy and information transfer. Various potential
models with energy harvesting nodes at different network scales are reviewed as
well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
Optimal Energy Management for Energy Harvesting Transmitter and Receiver with Helper
We study energy harvesting (EH) transmitter and receiver, where the receiver
decodes data using the harvested energy from the nature and from an independent
EH node, named helper. Helper cooperates with the receiver by transferring its
harvested energy to the receiver over an orthogonal fading channel. We study an
offline optimal power management policy to maximize the reliable information
rate. The harvested energy in all three nodes are assumed to be known. We
consider four different scenarios; First, for the case that both transmitter
and the receiver have batteries, we show that the optimal policy is
transferring the helper harvested energy to the receiver, immediately. Next,
for the case of non-battery receiver and full power transmitter, we model a
virtual EH receiver with minimum energy constraint to achieve an optimal
policy. Then, we consider a non-battery EH receiver and EH transmitter with
battery. Finally, we derive optimal power management wherein neither the
transmitter nor the receiver have batteries. We propose three iterative
algorithms to compute optimal energy management policies. Numerical results are
presented to corroborate the advantage of employing the helper.Comment: It is a conference paper with 5 pages and one figure, submitted to
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