Delay bounded rate and power control in energy harvesting wireless networks

Raghuvir, R. A.; Rajan, Dinesh

doi:10.1109/wcnc.2011.5779191

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…is the vector indicating the age of each packet in the data buffer, • b is the battery level, and • x is the channel gain. Notice that in the previous works [9], [10], the queue length q describes the data buffer states. In our work, q is replaced with k due the strict delay constraint.…”

Section: A State Spacementioning

confidence: 99%

“…The problem was modeled as a two-dimensional Markov chain and an optimal policy depending on a critical threshold of the queue length is proposed using Linear programming formulations. In [9], optimal deterministic scheduling in EH-powered network satisfying an average delay constraint and an average consumed energy constraint was obtained by minimizing the packet blocking probability, due to nontransmission at the transmitter. The problem was formulated as an MDP and solved using dynamic programming Value Iteration (VI) algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Delay-Optimal Resource Scheduling of Energy Harvesting-Based Devices

Fawaz

Sarkiss

Ciblat

2019

IEEE Trans. on Green Commun. Netw.

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This paper investigates resource scheduling in a wireless communication system operating with Energy Harvesting (EH) based devices and perfect Channel State Information (CSI). The aim is to minimize the packet loss that occurs when the buffer is overflowed or 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 is modeled as Markov Decision Process (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 that the gain in the number of transmitted packets and the consumed energy is substantial compared to: i) a naive policy which forces the system to send the maximum number of packets using the available energy in the battery, ii) two variants of the previous policy that take into account the buffer state, and iii) a policy optimized with an average delay constraint. Finally, we evaluate our optimal policy under imperfect CSI scenario where only an estimate of the channel state is available.

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Section: A State Spacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Delay-Optimal Resource Scheduling of Energy Harvesting-Based Devices

Fawaz

Sarkiss

Ciblat

2019

IEEE Trans. on Green Commun. Netw.

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show abstract

“…Notice that in the previous works [10], [11], the queue length q describes the data buffer states. In our work, q is replaced with k due the strict delay constraint.…”

Section: A State Spacementioning

confidence: 99%

“…The problem was modeled as a two-dimensional Markov chain and an optimal transmission policy depending on a critical threshold of the queue length is proposed using Linear programming formulations. In [10], optimal deterministic scheduling in EH-powered network was obtained by minimizing the packet blocking probability, due to non-transmission at the transmitter, under an average delay (equivalently queue length) constraint and an average consumed energy constraint. The problem was formulated as an MDP and solved using dynamic programming Value Iteration algorithm.…”

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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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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Optimal Relaying in a Slotted Aloha Wireless Network with Energy Harvesting Nodes

Moradian

Ashtiani

2015

IEEE J. Select. Areas Commun.

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Delay bounded rate and power control in energy harvesting wireless networks

Cited by 6 publications

References 16 publications

Delay-Optimal Resource Scheduling of Energy Harvesting-Based Devices

Delay-Optimal Resource Scheduling of Energy Harvesting-Based Devices

Optimal Resource Scheduling for Energy Harvesting Communications under Strict Delay Constraint

Optimal Relaying in a Slotted Aloha Wireless Network with Energy Harvesting Nodes

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