126 research outputs found
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
RF Energy Harvesting Enabled Power Sharing in Relay Networks
Through simultaneous energy and information transfer, radio frequency (RF)
energy harvesting (EH) reduces the energy consumption of the wireless networks.
It also provides a new approach for the wireless devices to share each other's
energy storage, without relying on the power grid or traffic offloading. In
this paper, we study RF energy harvesting enabled power balancing within the
decode-and-forward (DF) relaying-enhanced cooperative wireless system. An
optimal power allocation policy is proposed for the scenario where both source
and relay nodes can draw power from the radio frequency signals transmitted by
each other. To maximize the overall throughput while meeting the energy
constraints imposed by the RF sources, an optimization problem is formulated
and solved. Based on different harvesting efficiency and channel condition,
closed form solutions for optimal joint source and relay power allocation are
derived.Comment: An abbreviated version will be presented at IEEE online GreenComm,
Nov., 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
Training Optimization for Energy Harvesting Communication Systems
Energy harvesting (EH) has recently emerged as an effective way to solve the
lifetime challenge of wireless sensor networks, as it can continuously harvest
energy from the environment. Unfortunately, it is challenging to guarantee a
satisfactory short-term performance in EH communication systems because the
harvested energy is sporadic. In this paper, we consider the channel training
optimization problem in EH communication systems, i.e., how to obtain accurate
channel state information to improve the communication performance. In contrast
to conventional communication systems, the optimization of the training power
and training period in EH communication systems is a coupled problem, which
makes such optimization very challenging. We shall formulate the optimal
training design problem for EH communication systems, and propose two solutions
that adaptively adjust the training period and power based on either the
instantaneous energy profile or the average energy harvesting rate. Numerical
and simulation results will show that training optimization is important in EH
communication systems. In particular, it will be shown that for short block
lengths, training optimization is critical. In contrast, for long block
lengths, the optimal training period is not too sensitive to the value of the
block length nor to the energy profile. Therefore, a properly selected fixed
training period value can be used.Comment: 6 pages, 5 figures, Globecom 201
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