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252
Energy optimal control for time varying wireless networks
 IEEE Trans. Inform. Theory
, 2006
"... Abstract — We develop a dynamic control strategy for minimizing energy expenditure in a time varying wireless network with adaptive transmission rates. The algorithm operates without knowledge of traffic rates or channel statistics, and yields average power that is arbitrarily close to the minimum p ..."
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Cited by 184 (50 self)
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Abstract — We develop a dynamic control strategy for minimizing energy expenditure in a time varying wireless network with adaptive transmission rates. The algorithm operates without knowledge of traffic rates or channel statistics, and yields average power that is arbitrarily close to the minimum possible value achieved by an algorithm optimized with complete knowledge of future events. Proximity to this optimal solution is shown to be inversely proportional to network delay. We then present a similar algorithm that solves the related problem of maximizing network throughput subject to peak and average power constraints. The techniques used in this paper are novel and establish a foundation for stochastic network optimization.
Optimal Packet Scheduling in an Energy Harvesting Communication System
"... We consider the optimal packet scheduling problem in a singleuser energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modeled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to th ..."
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Cited by 132 (26 self)
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We consider the optimal packet scheduling problem in a singleuser energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modeled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to the traffic load and available energy, such that the time by which all packets are delivered is minimized. Under a deterministic system setting, we assume that the energy harvesting times and harvested energy amounts are known before the transmission starts. For the data traffic arrivals, we consider two different scenarios. In the first scenario, we assume that all bits have arrived and are ready at the transmitter before the transmission starts. In the second scenario, we consider the case where packets arrive during the transmissions, with known arrival times and sizes. We develop optimal offline scheduling policies which minimize the time by which all packets are delivered to the destination, under causality constraints on both data and energy arrivals.
Recent and Emerging Topics in Wireless Industrial Communications: A Selection
, 2007
"... In this paper we discuss a selection of promising and interesting research areas in the design of protocols and systemsforwirelessindustrialcommunications.Wehaveselected topicsthathaveeitheremergedashottopicsintheindustrial communicationscommunityinthelastfewyears(likewireless sensornetworks),orwhi ..."
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Cited by 96 (1 self)
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In this paper we discuss a selection of promising and interesting research areas in the design of protocols and systemsforwirelessindustrialcommunications.Wehaveselected topicsthathaveeitheremergedashottopicsintheindustrial communicationscommunityinthelastfewyears(likewireless sensornetworks),orwhichcouldbeworthwhileresearchtopicsin thenextfewyears(forexamplecooperativediversitytechniques for error control, cognitive radio/opportunistic spectrum access for mitigation of external interferences).
Joint source coding and transmission power managment for energy efficient wireless video communications
 IEEE TRANS. CIRCUITS SYST. VIDEO TECHNOL
, 2002
"... Abstract—We consider a situation where a video sequence is to be compressed and transmitted over a wireless channel. Our goal is to limit the amount of distortion in the received video sequence, while minimizing transmission energy. To accomplish this goal, we consider error resilience and concealme ..."
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Cited by 73 (20 self)
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Abstract—We consider a situation where a video sequence is to be compressed and transmitted over a wireless channel. Our goal is to limit the amount of distortion in the received video sequence, while minimizing transmission energy. To accomplish this goal, we consider error resilience and concealment techniques at the source coding level, and transmission power management at the physical layer. We jointly consider these approaches in a novel framework. In this setting, we formulate and solve an optimization problem that corresponds to minimizing the energy required to transmit video under distortion and delay constraints. Experimental results show that simultaneously adjusting the source coding and transmission power is more energy efficient than considering these factors separately. Index Terms—Error concealment, error resilience, expected distortion, optimal mode selection, power and rate control. I.
Optimal energy and delay tradeoffs for multiuser wireless downlinks
 Proc. IEEE INFOCOM
, 2006
"... Abstract — We consider the fundamental delay tradeoffs for minimizing energy expenditure in a multiuser wireless downlink with randomly varying channels. First, we extend the BerryGallager bound to a multiuser context, demonstrating that any algorithm that yields average power within O(1/V) of th ..."
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Cited by 64 (17 self)
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Abstract — We consider the fundamental delay tradeoffs for minimizing energy expenditure in a multiuser wireless downlink with randomly varying channels. First, we extend the BerryGallager bound to a multiuser context, demonstrating that any algorithm that yields average power within O(1/V) of the minimum power required for network stability must also have an average queueing delay greater than or equal to Ω ( √ V). We then develop a class of algorithms, parameterized by V, that come within a logarithmic factor of achieving this fundamental tradeoff. The algorithms overcome an exponential state space explosion, and can be implemented in real time without apriori knowledge of traffic rates or channel statistics. Further, we discover a “superfast ” scheduling mode that beats the BerryGallager bound in the exceptional case when power functions are piecewise linear. Index Terms — queueing analysis, stability, optimization, stochastic control, asymptotic tradeoffs
Energyefficient resource allocation in wireless networks: An overview of gametheoretic approaches
 IEEE Signal Process. Magazine
, 2007
"... A gametheoretic model is proposed to study the crosslayer problem of joint power and rate control with quality of service (QoS) constraints in multipleaccess networks. In the proposed game, each user seeks to choose its transmit power and rate in a distributed manner in order to maximize its own ..."
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Cited by 55 (8 self)
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A gametheoretic model is proposed to study the crosslayer problem of joint power and rate control with quality of service (QoS) constraints in multipleaccess networks. In the proposed game, each user seeks to choose its transmit power and rate in a distributed manner in order to maximize its own utility while satisfying its QoS requirements. The user’s QoS constraints are specified in terms of the average source rate and an upper bound on the average delay where the delay includes both transmission and queuing delays. The utility function considered here measures energy efficiency and is particularly suitable for wireless networks with energy constraints. The Nash equilibrium solution for the proposed noncooperative game is derived and a closedform expression for the utility achieved at equilibrium is obtained. It is shown that the QoS requirements of a user translate into a “size ” for the user which is an indication of the amount of network resources consumed by the user. Using this competitive multiuser framework, the tradeoffs among throughput, delay, network capacity and energy efficiency are studied. In addition, analytical expressions are given for users ’ delay profiles and the delay performance of the users at Nash equilibrium is quantified.
Optimal packet scheduling on an energy harvesting broadcast link
 IEEE J. Sel. Areas Commun
, 2011
"... The minimization of transmission completion time for a given number of bits per user in an energy harvesting communication system, where energy harvesting instants are known in an offline manner is considered. An achievable rate region with structural properties satisfied by the 2user AWGN Broadcas ..."
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Cited by 54 (1 self)
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The minimization of transmission completion time for a given number of bits per user in an energy harvesting communication system, where energy harvesting instants are known in an offline manner is considered. An achievable rate region with structural properties satisfied by the 2user AWGN Broadcast Channel capacity region is assumed. It is shown that even though all data are available at the beginning, a nonnegative amount of energy from each energy harvest is deferred for later use such that the transmit power starts at its lowest value and rises as time progresses. The optimal scheduler ends the transmission to both users at the same time. Exploiting the special structure in the problem, the iterative offline algorithm, FlowRight, from earlier literature, is adapted and proved to solve this problem. The solution has polynomial complexity in the number of harvests used, and is observed to converge quickly on numerical examples. Index Terms Packet scheduling, energy harvesting, AWGN broadcast channel, flowright, energyefficient scheduling.
Delaybounded packet scheduling of bursty traffic over wireless channels
 IEEE Transactions on Information Theory
"... Abstract—In this paper, we study minimal power transmission of bursty sources over wireless channels with constraints on mean queuing delay. The power minimizing schedulers adapt power and rate of transmission based on the queue and channel state. We show that packet scheduling based on queue state ..."
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Cited by 44 (3 self)
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Abstract—In this paper, we study minimal power transmission of bursty sources over wireless channels with constraints on mean queuing delay. The power minimizing schedulers adapt power and rate of transmission based on the queue and channel state. We show that packet scheduling based on queue state can be used to trade queuing delay with transmission power, even on additive white Gaussian noise (AWGN) channels. Our extensive simulations show that small increases in average delay can lead to substantial savings in transmission power, thereby providing another avenue for mobile devices to save on battery power. We propose a lowcomplexity scheduler that has nearoptimal performance. We also construct a variablerate quadrature amplitude modulation (QAM)based transmission scheme to show the benefits of the proposed formulation in a practical communication system. Power optimal schedulers with absolute packet delay constraints are also studied and their performance is evaluated via simulations. Index Terms—Packet scheduling, power control, queuing delay, traffic regulation, wireless channels. I.
Optimal broadcast scheduling for an energy harvesting rechargeable transmitter with a finite capacity battery
 IEEE TRANS. WIRELESS COMMUN
, 2012
"... 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 mo ..."
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Cited by 42 (19 self)
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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 M − 1 cutoff power levels such that user i is allocated the power between the i−1st 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.
A Calculus Approach to EnergyEfficient Data Transmission with QualityofService Constraints
"... Transmission rate adaptation in wireless devices provides a unique opportunity to tradeoff data service rate with energy consumption. In this paper, we study optimal ratecontrol to minimize the transmission energy expenditure subject to strict deadline or other qualityofservice (QoS) constraints ..."
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Cited by 40 (1 self)
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Transmission rate adaptation in wireless devices provides a unique opportunity to tradeoff data service rate with energy consumption. In this paper, we study optimal ratecontrol to minimize the transmission energy expenditure subject to strict deadline or other qualityofservice (QoS) constraints. Specifically, the system consists of a wireless transmitter with controllable transmission rate and with strict QoS constraints on data transmission. The goal is to obtain a rate control policy that minimizes the total transmission energy expenditure while ensuring that the QoS constraints are met. Using a novel formulation based on cumulative curves methodology, we obtain the optimal transmission policy and show that it has a simple and appealing graphical visualization. Utilizing the optimal “offline” results, we then develop an online transmission policy for an arbitrary stream of packet arrivals and deadline constraints, and show, via simulations, that it is significantly more energy efficient than a simple headofline drain policy. Finally, we generalize the optimal policy results to the case of timevarying powerrate functions.