Optimal Stochastic Power Control for Energy Harvesting Systems with Statistical Delay Constraint

Ahmed, Imtiaz; Phan, Khoa T.; Le‐Ngoc, Tho

doi:10.1109/glocom.2014.7417468

Cited by 3 publications

(5 citation statements)

References 21 publications

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“…During the past decade, extensive research efforts have focused on investigating resource scheduling with EH capabilities at the transmitters: [1], [2] for overview, and [3]- [12] for original works. In these works, several performance criteria have been optimized such as throughput, completion time, average delay, outage probability, for various models of energy arrival rate, battery capacity, or fading channel.…”

Section: Introductionmentioning

confidence: 99%

“…Near-optimal control policy was derived by applying stochastic online learning based on post-decision state framework. In [12], MDP modeling and online post-decision learning approach were also derived to maximize the data arrival rate at the transmitter queue under delay and energy constraints. Two delay constraints were separately considered: average delay constraint and statistical delay constraint.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Resource Scheduling for Energy Harvesting Communications under Strict Delay Constraint

Fawaz

Sarkiss²,

Ciblat

2018

2018 IEEE International Conference on Communications (ICC)

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Abstract-This paper investigates the resource scheduling minimizing the packet loss when the wireless communication system operates with Energy Harvesting (EH) based devices. The packet loss occurs when the buffer is overflowed and when the queued packet is older than a certain pre-defined threshold. We so consider a strict delay constraint rather than an average delay constraint. The associated optimization problem can be modeled as Markov Decision Problem (MDP) where the actions are the number of packets sent on the known channel at each slot. The optimal deterministic offline policy is exhibited through dynamic programming techniques, i.e. Value Iteration (VI) algorithm. We show the gain in the number of transmitted packets and the consumed energy is substantial compared to a naive policy which forces the system to send the maximum number of packets using the available energy in the battery.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Resource Scheduling for Energy Harvesting Communications under Strict Delay Constraint

Fawaz

Sarkiss²,

Ciblat

2018

2018 IEEE International Conference on Communications (ICC)

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“…Also, it cannot spend more energy than the currently available amount in the battery. Moreover, in addition to the average delay constraint model Parts of Chapter 4 are presented at the 2015 IEEE Global Communications Conference (GLOBECOM) in San Diego, CA, USA [102], and accepted for publication in the IEEE Journal of Selected Areas in Communications, Series on Green Communications and Networking [103].…”

Section: Power Allocation With Energy Harvesting Over Fading Channel mentioning

confidence: 99%

Radio Resource Allocation Over Fading Channels Under Statistical Delay Constraints

Phan¹,

Le‐Ngoc²

2017

SpringerBriefs in Electrical and Computer Engineering

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Wireless data transmission suffers from the fading nature of wireless channels, where the instantaneous channel conditions and hence transmission rates randomly fluctuate over time. Consequently, data arrivals at each transmitter might not be transmitted instantly. To cope with this situation, the transmitter employs buffer to store the data temporarily for later transmission. While data buffering enables more efficient radio resource allocation to opportunistically select the favorable fading conditions for transmission, it introduces queuing delay that needs to be controlled in order to meet the end-to-end delay quality-ofservice (QoS) requirements in supporting delay-sensitive communications. In this thesis, we study and develop radio resource allocation schemes for buffer-aided communications over wireless fading channels under statistical delay constraints. Using the buffering capability as a means to exploit the fading diversity, the nodes (source and relay) perform resource allocation, and adapt their transmissions to the channel state information (CSI) in order to enhance the system throughput while maintaining the statistical delay QoS requirements in terms of upper-bounded average delay or delay-outage probability.The thesis starts by considering a source-destination communications link over a fading channel with data arriving at the source transmission buffer. In the first scenario, the source is assumed to have a maximum power constraint and an average delay constraint. We consider admission control applied on random data arrivals to the source buffer in order to avoid constraint violation, and study the joint optimal data admission control and power allocation (AC-PA) problem for throughput maximization. In the second scenario, we consider an energy-harvesting (EH) source, where random amounts of energy are harvested from renewable energy sources, and stored in a battery during the course of data transmission. In every transmission time slot, the source is constrained to use at most the amount of energy currently stored. We then explore optimal power allocation problems for such EH systems under average delay or delay-outage constraints. We formulate the problems as infinite horizon constrained Markov decision process (MDP) problems, which incorporate the random variations of the fading channel, data arrival, and EH processes. A novel solution approach based on post-decision state-value function is proposed to study the properties of the optimal solutions. We also propose online allocation algorithms when the statistical knowledge of the random processes is unknown, which is typical in real-life communications. Illustrative results demonstrate the effectiveness of the proposed algorithms over existing approaches iii under similar power and delay constraints.The thesis continues with a source-relay-destination communications link over fading channels with buffers available at both source and relay, as part of a multi-hop network. We investigate and develop optimal resource allocation schemes ...

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“…Accordingly, the packet outage probability of a single node can be obtained by using (32) and (33) as follows:…”

Section: Packet Timeout Probability For a Single Nodementioning

confidence: 99%

“…In [29], authors have applied zero-forcing beamforming to optimize the energy harvesting capability and enhance the system performance. Given delay constraints, optimal stochastic power control for energy harvesting system has been investigated in [30][31][32]. Most recently, transmit power minimization for wireless networks with energy harvesting relays have been analyzed in [33].…”

Section: Introductionmentioning

confidence: 99%

RF energy harvesting: an analysis of wireless sensor networks for reliable communication

et al. 2017

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In this paper, we consider a wireless energy harvesting network consisting of one hybrid access point (HAP) having multiple antennas, and multiple sensor nodes each equipped with a single antenna. In contrast to conventional uplink wireless networks, the sensor nodes in the considered network have no embedded energy supply. They need to recharge the energy from the wireless signals broadcasted by the HAP in order to communicate. Based on the point-to-point and multipoints-to-point model, we propose two medium access control protocols, namely harvesting at the header of timeslot (HHT) and harvesting at the dedicated timeslot (HDT), in which the sensor nodes harvest energy from the HAP in the downlink, and then transform its stored packet into bit streams to send to the HAP in the uplink. Considering a deadline for each packet, the cumulative distribution functions of packet transmission time of the proposed protocols are derived for the selection combining and maximal ratio combining (MRC) techniques at the HAP. Subsequently, analytical expressions for the packet timeout probability and system reliability are obtained to analyze the performance of proposed protocols. Analytical results are validated by numerical simulations. The impacts of the system parameters, such as energy harvesting efficiency coefficient, sensor positions, transmit signal-to-noise ratio, and the length of energy harvesting time on the packet timeout probability and the system reliability are extensively investigated. Our results show that the performance of the HDT protocol outperforms the one using the HHT protocol, and the HDT protocol with the MRC technique has the best performance and it can be a potential solution to enhance the reliability for wireless sensor networks.

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Optimal Stochastic Power Control for Energy Harvesting Systems with Statistical Delay Constraint

Cited by 3 publications

References 21 publications

Optimal Resource Scheduling for Energy Harvesting Communications under Strict Delay Constraint

Optimal Resource Scheduling for Energy Harvesting Communications under Strict Delay Constraint

Radio Resource Allocation Over Fading Channels Under Statistical Delay Constraints

RF energy harvesting: an analysis of wireless sensor networks for reliable communication

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