6,370 research outputs found
A Learning Theoretic Approach to Energy Harvesting Communication System Optimization
A point-to-point wireless communication system in which the transmitter is
equipped with an energy harvesting device and a rechargeable battery, is
studied. Both the energy and the data arrivals at the transmitter are modeled
as Markov processes. Delay-limited communication is considered assuming that
the underlying channel is block fading with memory, and the instantaneous
channel state information is available at both the transmitter and the
receiver. The expected total transmitted data during the transmitter's
activation time is maximized under three different sets of assumptions
regarding the information available at the transmitter about the underlying
stochastic processes. A learning theoretic approach is introduced, which does
not assume any a priori information on the Markov processes governing the
communication system. In addition, online and offline optimization problems are
studied for the same setting. Full statistical knowledge and causal information
on the realizations of the underlying stochastic processes are assumed in the
online optimization problem, while the offline optimization problem assumes
non-causal knowledge of the realizations in advance. Comparing the optimal
solutions in all three frameworks, the performance loss due to the lack of the
transmitter's information regarding the behaviors of the underlying Markov
processes is quantified
Energy Optimal Transmission Scheduling in Wireless Sensor Networks
One of the main issues in the design of sensor networks is energy efficient
communication of time-critical data. Energy wastage can be caused by failed
packet transmission attempts at each node due to channel dynamics and
interference. Therefore transmission control techniques that are unaware of the
channel dynamics can lead to suboptimal channel use patterns. In this paper we
propose a transmission controller that utilizes different "grades" of channel
side information to schedule packet transmissions in an optimal way, while
meeting a deadline constraint for all packets waiting in the transmission
queue. The wireless channel is modeled as a finite-state Markov channel. We are
specifically interested in the case where the transmitter has low-grade channel
side information that can be obtained based solely on the ACK/NAK sequence for
the previous transmissions. Our scheduler is readily implementable and it is
based on the dynamic programming solution to the finite-horizon transmission
control problem. We also calculate the information theoretic capacity of the
finite state Markov channel with feedback containing different grades of
channel side information including that, obtained through the ACK/NAK sequence.
We illustrate that our scheduler achieves a given throughput at a power level
that is fairly close to the fundamental limit achievable over the channel.Comment: Accepted for publication in the IEEE Transactions on Wireless
Communication
Optimal Save-Then-Transmit Protocol for Energy Harvesting Wireless Transmitters
In this paper, the design of a wireless communication device relying
exclusively on energy harvesting is considered. Due to the inability of
rechargeable energy sources to charge and discharge at the same time, a
constraint we term the energy half-duplex constraint, two rechargeable energy
storage devices (ESDs) are assumed so that at any given time, there is always
one ESD being recharged. The energy harvesting rate is assumed to be a random
variable that is constant over the time interval of interest. A
save-then-transmit (ST) protocol is introduced, in which a fraction of time
{\rho} (dubbed the save-ratio) is devoted exclusively to energy harvesting,
with the remaining fraction 1 - {\rho} used for data transmission. The ratio of
the energy obtainable from an ESD to the energy harvested is termed the energy
storage efficiency, {\eta}. We address the practical case of the secondary ESD
being a battery with {\eta} < 1, and the main ESD being a super-capacitor with
{\eta} = 1. The optimal save-ratio that minimizes outage probability is
derived, from which some useful design guidelines are drawn. In addition, we
compare the outage performance of random power supply to that of constant power
supply over the Rayleigh fading channel. The diversity order with random power
is shown to be the same as that of constant power, but the performance gap can
be large. Furthermore, we extend the proposed ST protocol to wireless networks
with multiple transmitters. It is shown that the system-level outage
performance is critically dependent on the relationship between the number of
transmitters and the optimal save-ratio for single-channel outage minimization.
Numerical results are provided to validate our proposed study.Comment: This is the longer version of a paper to appear in IEEE Transactions
on Wireless Communication
Data Transmission Over Networks for Estimation and Control
We consider the problem of controlling a linear time invariant process when the controller is located at a location remote from where the sensor measurements are being generated. The communication from the sensor to the controller is supported by a communication network with arbitrary topology composed of analog erasure channels. Using a separation principle, we prove that the optimal linear-quadratic-Gaussian (LQG) controller consists of an LQ optimal regulator along with an estimator that estimates the state of the process across the communication network. We then determine the optimal information processing strategy that should be followed by each node in the network so that the estimator is able to compute the best possible estimate in the minimum mean squared error sense. The algorithm is optimal for any packet-dropping process and at every time step, even though it is recursive and hence requires a constant amount of memory, processing and transmission at every node in the network per time step. For the case when the packet drop processes are memoryless and independent across links, we analyze the stability properties and the performance of the closed loop system. The algorithm is an attempt to escape the viewpoint of treating a network of communication links as a single end-to-end link with the probability of successful transmission determined by some measure of the reliability of the network
Linear Transmission of Composite Gaussian Measurements over a Fading Channel under Delay Constraints
Delay constrained linear transmission (LT) strategies are considered for the transmission of composite Gaussian measurements over an additive white Gaussian noise fading channel under an average power constraint. If the channel state information (CSI) is known by both the encoder and decoder, the optimal LT scheme in terms of the average mean-square error distortion is characterized under a strict delay constraint, and a graphical interpretation of the optimal power allocation strategy is presented. Then, for general delay constraints, two LT strategies are proposed based on the solution to a particular multiple measurements-parallel channels scenario. It is shown that the distortion decreases as the delay constraint is relaxed, and when the delay constraint is completely removed, both strategies achieve the optimal performance under certain matching conditions. If the CSI is known only by the decoder, the optimal LT strategy is derived under a strict delay constraint. The extension to general delay constraints is elusive. As a first step towards understanding the structure of the optimal scheme in this case, it is shown that for the multiple measurementsparallel channels scenario, any LT scheme that uses only a oneto-one linear mapping between measurements and channels is suboptimal in general
Achievable Secrecy Rates of an Energy Harvesting Device
The secrecy rate represents the amount of information per unit time that can
be securely sent on a communication link. In this work, we investigate the
achievable secrecy rates in an energy harvesting communication system composed
of a transmitter, a receiver and a malicious eavesdropper. In particular,
because of the energy constraints and the channel conditions, it is important
to understand when a device should transmit and to optimize how much power
should be used in order to improve security. Both full knowledge and partial
knowledge of the channel are considered under a Nakagami fading scenario. We
show that high secrecy rates can be obtained only with power and coding rate
adaptation. Moreover, we highlight the importance of optimally dividing the
transmission power in the frequency domain, and note that the optimal scheme
provides high gains in secrecy rate over the uniform power splitting case.
Analytically, we explain how to find the optimal policy and prove some of its
properties. In our numerical evaluation, we discuss how the maximum achievable
secrecy rate changes according to the various system parameters. Furthermore,
we discuss the effects of a finite battery on the system performance and note
that, in order to achieve high secrecy rates, it is not necessary to use very
large batteries.Comment: Accepted for publication in IEEE Journal on Selected Areas in
Communications (Mar. 2016
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