Publications (40)29.98 Total impact
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ABSTRACT: We consider the Gaussian wiretap channel with amplitude and variance constraints on the channel input. We first show that the entire rateequivocation region of the Gaussian wiretap channel with an amplitude constraint is obtained by discrete input distributions with finite support. We prove this result by considering the existing singleletter description of the rateequivocation region, and showing that discrete distributions with finite support exhaust this region. Our result highlights an important difference between the peak power (amplitude) constrained and the average power (variance) constrained cases. Although, in the average power constrained case, both the secrecy capacity and the capacity can be achieved simultaneously, our results show that in the peak power constrained case, in general, there is a tradeoff between the secrecy capacity and the capacity, in the sense that, both may not be achieved simultaneously. We also show that under sufficiently small amplitude constraints the possible tradeoff between the secrecy capacity and the capacity does not exist and they are both achieved by the symmetric binary distribution. Finally, we prove the optimality of discrete input distributions in the presence of an additional variance constraint.  [Show abstract] [Hide abstract]
ABSTRACT: We consider the delay minimization problem in an energy harvesting communication network with energy cooperation. In this network, nodes harvest energy from nature for use in data transmission, and may transfer a portion of their harvested energies to neighboring nodes through energy cooperation. For fixed data and energy routing topologies, we determine the optimum data rates, transmit powers and energy transfers, subject to flow and energy conservation constraints, in order to minimize the network delay. We start with a simplified problem with fixed data flows and optimize energy management at each node for the case of a single energy harvest per node. This is tantamount to distributing each node's available energy over its outgoing data links and energy transfers to neighboring nodes. For this case, with no energy cooperation, we show that each node should allocate more power to links with more noise and/or more data flow. In addition, when there is energy cooperation, our numerical results indicate that, energy is routed from nodes with lower data loads to nodes with higher data loads. We extend this setting to the case of multiple energy harvests per node over time. In this case, we optimize each node's energy management over its outgoing data links and its energy transfers to neighboring nodes, over multiple time slots. For this case, with no energy cooperation, we show that, for any given node, the sum of powers on the outgoing links is equal to the singlelink optimal power over time. Finally, we consider the problem of joint flow control and energy management for the entire network. We determine the necessary conditions for joint optimality of a power control, energy transfer and routing policy. We provide an iterative algorithm that updates the data and energy flows, and power distribution over outgoing data links. We show convergence to a Paretooptimal operating point. 
Article: Energy Harvesting Transmitters that Heat Up: Throughput Maximization under Temperature Constraints
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ABSTRACT: Motivated by damage due to heating in sensor operation, we consider the throughput optimal offline data scheduling problem in an energy harvesting transmitter such that the resulting temperature increase remains below a critical level. We model the temperature dynamics of the transmitter as a linear system and determine the optimal transmit power policy under such temperature constraints as well as energy harvesting constraints over an AWGN channel. We first derive the structural properties of the solution for the general case with multiple energy arrivals. We show that the optimal power policy is piecewise monotone decreasing with possible jumps at the energy harvesting instants. We derive analytical expressions for the optimal solution in the single energy arrival case. We show that, in the single energy arrival case, the optimal power is monotone decreasing, the resulting temperature is monotone increasing, and both remain constant after the temperature hits the critical level. We then generalize the solution for the multiple energy arrival case.  [Show abstract] [Hide abstract]
ABSTRACT: Wireless networks composed of energy harvesting devices will introduce several transformative changes in wireless networking as we know it: energy selfsufficient, energy selfsustaining, perpetual operation; reduced use of conventional energy and accompanying carbon footprint; untethered mobility; and an ability to deploy wireless networks in hardtoreach places such as remote rural areas, within structures, and within the human body. Energy harvesting brings new dimensions to the wireless communication problem in the form of intermittency and randomness of available energy, which necessitates a fresh look at wireless communication protocols at the physical, medium access, and networking layers. Scheduling and optimization aspects of energy harvesting communications in the medium access and networking layers have been relatively wellunderstood and surveyed in the recent paper [1]. This branch of literature takes a physical layer ratepower relationship that is valid in energy harvesting conditions under largeenough batteries and longenough durations between energy harvests so that informationtheoretic asymptotes are achieved, and optimizes the transmit power over time in order to maximize the throughput. Another branch of recent literature aims to understand the fundamental capacity limits, i.e. informationtheoretic capacities, of energy harvesting links under smaller scale dynamics, considering energy harvests at the channel use level. This branch necessitates a deeper look at the coding and transmission schemes in the physical layer, and ultimately aims to develop an information theory of energy harvesting communications, akin to Shannon's development of an information theory for average power constrained communications. In this introductory article, we survey recent results in this branch and point to open problems that could be of interest to a broad set of researchers in the fields of communication theory, information theory, signal processing, and netw rking. In particular, we review capacities of energy harvesting links with infinitesized, finitesized, and no batteries at the transmitter.  [Show abstract] [Hide abstract]
ABSTRACT: In this paper, we consider a binary energy harvesting transmitter that wishes to control the amount of side information the receiver can obtain about its energy harvests. Specifically, we study state amplification and state masking, which define the maximum and minimum amount of state information conveyed to the receiver for a given message rate, respectively. For an independent and identically distributed energy harvesting process, we first find the amplification and masking regions for a transmitter without a battery and a transmitter with an infinite battery. Next, we find inner bounds for these regions for a unitsized battery at the transmitter using two different encoding schemes, using instantaneous Shannon strategies and using a scheme based on the equivalent timing channel introduced in our previous work. We observe that the former provides better state amplification, while the latter provides better state masking.  [Show abstract] [Hide abstract]
ABSTRACT: We consider a binary energy harvesting communication channel with a finitesized battery at the transmitter. In this model, the channel input is constrained by the available energy at each channel use, which is driven by an external energy harvesting process, the size of the battery, and the previous channel inputs. We consider an abstraction where energy is harvested in binary units and stored in a battery with the capacity of a single unit, and the channel inputs are binary. Viewing the available energy in the battery as a state, this is a statedependent channel with inputdependent states, memory in the states, and causal state information available at the transmitter only. We find an equivalent representation for this channel based on the timings of the symbols, and determine the capacity of the resulting equivalent timing channel via an auxiliary random variable. We give achievable rates based on certain selections of this auxiliary random variable which resemble lattice coding for the timing channel. We develop upper bounds for the capacity by using a genieaided method, and also by quantifying the leakage of the state information to the receiver. We show that the proposed achievable rates are asymptotically capacity achieving for small energy harvesting rates. We extend the results to the case of ternary channel inputs. Our achievable rates give the capacity of the binary channel within 0.03 bits/channel use, the ternary channel within 0.05 bits/channel use, and outperform basic Shannon strategies that only consider instantaneous battery states, for all parameter values. 
Conference Paper: Improved capacity bounds for the binary energy harvesting channel
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ABSTRACT: We consider a binary energy harvesting channel (BEHC) where the encoder has unit energy storage capacity. We first show that an encoding scheme based on block indexing is asymptotically optimal for small energy harvesting rates. We then present a novel upper bounding technique, which upper bounds the rate by lowerbounding the rate of information leakage to the receiver regarding the energy harvesting process. Finally, we propose a timing based hybrid encoding scheme that achieves rates within 0.03 bits/channel use of the upper bound; hence determining the capacity to within 0.03 bits/channel use.  [Show abstract] [Hide abstract]
ABSTRACT: We consider data transmission with an energy harvesting transmitter that has hybrid energy storage with a perfect supercapacitor (SC) and an inefficient battery. The SC has finite storage space while the battery has unlimited space. The transmitter can choose to store the harvested energy in the SC or in the battery. The energy is drained from the SC and the battery simultaneously. In this setting, we consider throughput optimal offline energy allocation problem over a pointtopoint channel. In contrast to previous works, the hybrid energy storage model with finite and unlimited storage capacities imposes a generalized set of constraints on the transmission policy. As such, we show that the solution generalizes that for a single battery and is found by a sequential application of the directional waterfilling algorithm. Next, we consider offline throughput maximization in the presence of an additive timelinear processing cost in the transmitter's circuitry. In this case, the transmitter has to additionally decide on the portions of the processing cost to be drained from the SC and the battery. Despite this additional complexity, we show that the solution is obtained by a sequential application of a directional glue pouring algorithm, parallel to the costless processing case. Finally, we provide numerical illustrations for optimal policies and performance comparisons with some heuristic online policies. 
Conference Paper: Capacity of the discrete memoryless energy harvesting channel with side information
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ABSTRACT: We determine the capacity of a discrete memoryless communication channel with an energy harvesting transmitter and its battery state information available at the transmitter and the receiver. This capacity is an upper bound for the problem where side information is available only at the transmitter. Since channel output feedback does not increase the capacity in this case, we equivalently study the resulting finitestate Markov channel with feedback. We express the capacity in terms of directed information. Additionally, we provide sufficient conditions under which the capacity expression is further simplified to include the stationary distribution of the battery state. We also obtain a singleletter expression for the capacity with battery state information at both sides and an infinitesized battery. Lastly, we consider achievable schemes when side information is available only at the transmitter for the case of an arbitrary finitesized battery. We numerically evaluate the capacity and achievable rates with and without receiver side information.  [Show abstract] [Hide abstract]
ABSTRACT: We consider data transmission with an energy harvesting transmitter with nonnegligible processing circuitry power and a hybrid energy storage unit composed of an ideal supercapacitor (SC) and an inefficient battery. The SC has finite space for energy storage while the battery has unlimited space. The transmitter stores the harvested energy either in the SC or in the battery and the energy is drained from the SC and the battery simultaneously. In this setting, we address the offline throughput maximization problem over a pointtopoint channel. We show that the solution is obtained by a sequential application of the directional gluepouring algorithm.  [Show abstract] [Hide abstract]
ABSTRACT: This paper presents a distributed mechanism for improving the overall energy efficiency of a wireless network where users can control their uplink transmit power targeted to the multiple access points in the network. This mechanism lets the network achieve a tradeoff between energy efficiency and spectral efficiency through the use of suitably designed utility functions. A user's utility is a function of throughput and average transmission power. Throughput is assumed to be a sigmoidal function of signaltointerferenceplusnoise ratio. Each user, being selfish and rational, acts to maximise its utility in response to signaltointerferenceplusnoise ratio by adjusting its power. The resulting mechanism is a distributed power control scheme that can incline towards energyefficient or spectrally efficient operating points depending on the choice of utility function. Existence and uniqueness of Nash equilibrium points in this game are shown via convergence of the distributed power iterations. It is shown that, in the bestresponse strategy, each user selects a single access point. An extension of this result for a multicarrier system is considered, and the corresponding power levels used for various priorities between energy efficiency and spectral efficiency are characterised. Finally, several numerical studies are presented to illustrate the analysis. Copyright © 2012 John Wiley & Sons, Ltd.  [Show abstract] [Hide abstract]
ABSTRACT: We consider an energy harvesting transmitter sending messages to two users over parallel and fading Gaussian broadcast channels. Energy required for communication arrives (is harvested) at the transmitter and a finitecapacity battery stores it before being consumed for transmission. Under offline knowledge of energy arrival and channel fading variations, we obtain the tradeoff between the performances of the users by characterizing the maximum departure region in a given interval. We first analyze the transmission with an energy harvesting transmitter over parallel broadcast channels. We show that the optimal total transmit power policy that achieves the boundary of the maximum departure region is the same as the optimal policy for the nonfading broadcast channel, which does not depend on the priorities of the users, and therefore is the same as the optimal policy for the nonfading scalar singleuser channel. The optimal total transmit power can be found by a directional waterfilling algorithm. The optimal splitting of the power among the parallel channels is performed in each epoch separately. Next, we consider fading broadcast channels and obtain the transmission policies that achieve the boundary of the maximum departure region. The optimal total transmit power allocation policy is found using a specific directional waterfilling algorithm for fading broadcast channels. The optimal power allocation depends on the priorities of the users unlike in the case of parallel broadcast channels. Finally, we provide numerical illustrations of the optimal policies and maximum departure regions for both parallel and fading broadcast channels.  [Show abstract] [Hide abstract]
ABSTRACT: We consider data transmission with an energy harvesting transmitter which has a hybrid energy storage unit composed of a perfectly efficient supercapacitor (SC) and an inefficient battery. The SC has finite space for energy storage while the battery has unlimited space. The transmitter can choose to store the harvested energy in the SC or in the battery. The energy is drained from the SC and the battery simultaneously. In this setting, we consider the offline throughput maximization problem by a deadline over a pointtopoint channel. In contrast to previous works, the hybrid energy storage model with finite and unlimited storage capacities imposes a generalized set of constraints on the transmission policy. As such, we show that the solution generalizes that for a single battery and is obtained by applying directional waterfilling algorithm multiple times.  [Show abstract] [Hide abstract]
ABSTRACT: We consider the capacity of an energy harvesting communication channel with a finitesized battery. As an abstraction of this problem, we consider a system where energy arrives at the encoder in multiples of a fixed quantity, and the physical layer is modeled accordingly as a finite discrete alphabet channel based on this fixed quantity. Further, for tractability, we consider the case of binary energy arrivals into a unitcapacity battery over a noiseless binary channel. Viewing the available energy as state, this is a statedependent channel with causal state information available only at the transmitter. Further, the state is correlated over time and the channel inputs modify the future states. We show that this channel is equivalent to an additive geometricnoise timing channel with causal information of the noise available at the transmitter.We provide a singleletter capacity expression involving an auxiliary random variable, and evaluate this expression with certain auxiliary random variable selection, which resembles noise concentration and latticetype coding in the timing channel. We evaluate the achievable rates by the proposed auxiliary selection and extend our results to noiseless ternary channels.  [Show abstract] [Hide abstract]
ABSTRACT: In energy harvesting communications, users transmit messages using energy harvested from nature during the course of communication. With an optimum transmit policy, the performance of the system depends only on the energy arrival profiles. In this paper, we introduce the concept of energy cooperation, where a user wirelessly transmits a portion of its energy to another energy harvesting user. This enables shaping and optimization of the energy arrivals at the energyreceiving node, and improves the overall system performance, despite the loss incurred in energy transfer. We consider several basic multiuser network structures with energy harvesting and wireless energy transfer capabilities: relay channel, twoway channel and multiple access channel. We determine energy management policies that maximize the system throughput within a given duration using a Lagrangian formulation and the resulting KKT optimality conditions. We develop a twodimensional directional waterfilling algorithm which optimally controls the flow of harvested energy in two dimensions: in time (from past to future) and among users (from energytransferring to energyreceiving) and show that a generalized version of this algorithm achieves the boundary of the capacity region of the twoway channel.  [Show abstract] [Hide abstract]
ABSTRACT: We study the capacity regions of twoway and multipleaccess energy harvesting communication systems with oneway wireless energy transfer. In these systems, energy required for data transmission is harvested by the users from nature throughout the communication duration, and there is a separate unit that enables energy transfer from the first user to the second user with an efficiency of α. Energy harvests are known by the transmitters a priori. We first investigate the capacity region of the energy harvesting Gaussian twoway channel (TWC) with oneway energy transfer. We show that the boundary of the capacity region is achieved by a generalized twodimensional directional waterfilling algorithm. Then, we study the capacity region of the energy harvesting Gaussian multiple access channel (MAC) with oneway energy transfer. We show that if the priority of the first user is higher, then energy transfer is not needed. In addition, if the priority of the second user is sufficiently high, then the first user must transfer all of its energy to the second user.  [Show abstract] [Hide abstract]
ABSTRACT: In energy harvesting communication systems, an exogenous recharge process supplies energy necessary for data transmission and the arriving energy can be buffered in a battery before consumption. We determine the informationtheoretic capacity of the classical additive white Gaussian noise (AWGN) channel with an energy harvesting transmitter with an unlimited sized battery. As the energy arrives randomly and can be saved in the battery, codewords must obey cumulative stochastic energy constraints. We show that the capacity of the AWGN channel with such stochastic channel input constraints is equal to the capacity with an average power constraint equal to the average recharge rate. We provide two capacity achieving schemes: saveandtransmit and bestefforttransmit. In the saveandtransmit scheme, the transmitter collects energy in a saving phase of proper duration that guarantees that there will be no energy shortages during the transmission of code symbols. In the bestefforttransmit scheme, the transmission starts right away without an initial saving period, and the transmitter sends a code symbol if there is sufficient energy in the battery, and a zero symbol otherwise. Finally, we consider a system in which the average recharge rate is time varying in a larger time scale and derive the optimal offline power policy that maximizes the average throughput, by using majorization theory. 
Conference Paper: Gaussian wiretap channel with an amplitude constraint
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ABSTRACT: We consider the Gaussian wiretap channel with an amplitude constraint, i.e., a peak power constraint, on the channel input. We show that the entire rateequivocation region of the Gaussian wiretap channel with an amplitude constraint is obtained by discrete input distributions with finite support. We prove this result by considering the existing singleletter description of the rateequivocation region, and showing that discrete distributions with finite support exhaust this region. Our result highlights an important difference between the peak power constraint and the average power constraint cases: Although, in the average power constraint case, both the secrecy capacity and the capacity can be achieved simultaneously, our results show that in the peak power constraint case, in general, there is a tradeoff between the secrecy capacity and the capacity, in the sense that, both may not be achieved simultaneously. 
Conference Paper: Energy state amplification in an energy harvesting communication system
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ABSTRACT: In energy harvesting communication systems, the energy required for message transmission is maintained by an exogenous energy arrival process independent of the message. This links the problem of communication with an energy harvesting transmitter to the problem of communication over statedependent channels. In particular, if the transmitter has no battery, the available energy can be viewed as a state and the resulting channel is a statedependent channel with causal state information at the transmitter only. In general, information transmission blurs the state information that the receiver can get from the received signal. In this paper, we explore the tradeoff between the information rate R and the entropy reduction of the energy arrival process Δ at the receiver side over an AWGN channel with an energy harvesting transmitter. If the transmitter has no battery, the tradeoff points are achieved by Shannon strategies and we show that the optimal input distributions are discrete. Next, we consider the state amplification problem for an energy harvesting transmitter with an unlimited battery. We show that the optimal tradeoff region in this extreme case is expressed explicitly in a simple form and its boundary is achieved by a combination of bestefforttransmit and random binning schemes with an i.i.d. Gaussian codebook of average power equal to the average recharge rate. Finally, we propose an uncoded state amplification scheme that splits the energy between message transmission and entropy reduction and study its performance in a numerical example.  [Show abstract] [Hide abstract]
ABSTRACT: We consider the minimization of the transmission completion time with a battery limited energy harvesting transmitter in an Muser AWGN broadcast channel where the transmitter is able to harvest energy from the nature, using a finite storage capacity rechargeable battery. The harvested energy is modeled to arrive (be harvested) at the transmitter during the course of transmissions at arbitrary time instants. The transmitter has fixed number of packets for each receiver. Due to the finite battery capacity, energy may overflow without being utilized for data transmission. We derive the optimal offline transmission policy that minimizes the time by which all of the data packets are delivered to their respective destinations. We analyze the structural properties of the optimal transmission policy using a dual problem. We find the optimal total transmit power sequence by a directional waterfilling algorithm. We prove that there exist M1 cutoff power levels such that user i is allocated the power between the i1st and the ith cutoff power levels subject to the availability of the allocated total power level. Based on these properties, we propose an algorithm that gives the globally optimal offline policy. The proposed algorithm uses directional waterfilling repetitively. Finally, we illustrate the optimal policy and compare its performance with several suboptimal policies under different settings.
Publication Stats
801  Citations  
29.98  Total Impact Points  
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Institutions

20092015

University of Maryland, College Park
 Department of Electrical & Computer Engineering
CGS, Maryland, United States


20102013

Loyola University Maryland
Baltimore, Maryland, United States 
TOBB University of Economics and Technology
 Department of Electrical and Electronics Engineering
Engüri, Ankara, Turkey


20092010

Middle East Technical University
 Department of Electrical and Electronics Engineering
Engüri, Ankara, Turkey
