18 research outputs found
Energy Harvesting Broadband Communication Systems with Processing Energy Cost
Communication over a broadband fading channel powered by an energy harvesting
transmitter is studied. Assuming non-causal knowledge of energy/data arrivals
and channel gains, optimal transmission schemes are identified by taking into
account the energy cost of the processing circuitry as well as the transmission
energy. A constant processing cost for each active sub-channel is assumed.
Three different system objectives are considered: i) throughput maximization,
in which the total amount of transmitted data by a deadline is maximized for a
backlogged transmitter with a finite capacity battery; ii) energy maximization,
in which the remaining energy in an infinite capacity battery by a deadline is
maximized such that all the arriving data packets are delivered; iii)
transmission completion time minimization, in which the delivery time of all
the arriving data packets is minimized assuming infinite size battery. For each
objective, a convex optimization problem is formulated, the properties of the
optimal transmission policies are identified, and an algorithm which computes
an optimal transmission policy is proposed. Finally, based on the insights
gained from the offline optimizations, low-complexity online algorithms
performing close to the optimal dynamic programming solution for the throughput
and energy maximization problems are developed under the assumption that the
energy/data arrivals and channel states are known causally at the transmitter.Comment: published in IEEE Transactions on Wireless Communication
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
ISITA201
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
Hybrid NOMA-TDMA for Multiple Access Channels with Non-Ideal Batteries and Circuit Cost
We consider a multiple-access channel where the users are powered from
batteries having non-negligible internal resistance. When power is drawn from
the battery, a variable fraction of the power, which is a function of the power
drawn from the battery, is lost across the internal resistance. Hence, the
power delivered to the load is less than the power drawn from the battery. The
users consume a constant power for the circuit operation during transmission
but do not consume any power when not transmitting. In this setting, we obtain
the maximum sum-rates and achievable rate regions under various cases. We show
that, unlike in the ideal battery case, the TDMA (time-division multiple
access) strategy, wherein the users transmit orthogonally in time, may not
always achieve the maximum sum-rate when the internal resistance is non-zero.
The users may need to adopt a hybrid NOMA-TDMA strategy which combines the
features of NOMA (non-orthogonal multiple access) and TDMA, wherein a set of
users are allocated fixed time windows for orthogonal single-user and
non-orthogonal joint transmissions, respectively. We also numerically show that
the maximum achievable rate regions in NOMA and TDMA strategies are contained
within the maximum achievable rate region of the hybrid NOMA-TDMA strategy
Source-Channel Coding under Energy, Delay and Buffer Constraints
Source-channel coding for an energy limited wireless sensor node is
investigated. The sensor node observes independent Gaussian source samples with
variances changing over time slots and transmits to a destination over a flat
fading channel. The fading is constant during each time slot. The compressed
samples are stored in a finite size data buffer and need to be delivered in at
most time slots. The objective is to design optimal transmission policies,
namely, optimal power and distortion allocation, over the time slots such that
the average distortion at destination is minimized. In particular, optimal
transmission policies with various energy constraints are studied. First, a
battery operated system in which sensor node has a finite amount of energy at
the beginning of transmission is investigated. Then, the impact of energy
harvesting, energy cost of processing and sampling are considered. For each
energy constraint, a convex optimization problem is formulated, and the
properties of optimal transmission policies are identified. For the strict
delay case, , waterfilling interpretation is provided. Numerical
results are presented to illustrate the structure of the optimal transmission
policy, to analyze the effect of delay constraints, data buffer size, energy
harvesting, processing and sampling costs.Comment: 30 pages, 15 figures. Submitted to IEEE Transactions on Wireless
Communication