Optimal Power Allocation for Full-Duplex Underwater Relay Networks With Energy Harvesting: A Reinforcement Learning Approach

Wang, Ranning; Yadav, Animesh; Makled, Esraa A.; Dobre, Octavia A.; Zhao, Ruiqin; Varshney, Pramod K.

doi:10.1109/lwc.2019.2948992

Cited by 50 publications

(26 citation statements)

References 18 publications

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“…Different from References [ 21 , 27 ], we consider a complex joint relay selection and power allocation problem for EH-UASNs, rather than the single power allocation or relay selection. In addition, the traditional relay network optimization algorithms [ 8 , 9 ] assume the perfect real-time CSI is known.…”

Section: Problem Formulation and Solutionmentioning

confidence: 99%

“…Reinforcement learning (RL) based on artificial intelligence has been used as a powerful tool to solve complex resource allocation problem in various wireless networks with poor prior information [ 18 , 19 , 20 ]. In Reference [ 21 ], Running et al proposed a model-based RL power allocation algorithm for the energy harvesting underwater relay networks to maximize the long-term end-to-end information transmission rate. And in this algorithm, it assumed channel gain information is invariant for a while.…”

Section: Introductionmentioning

confidence: 99%

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Deep Q-Network-Based Cooperative Transmission Joint Strategy Optimization Algorithm for Energy Harvesting-Powered Underwater Acoustic Sensor Networks

Han

2020

Sensors

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Cooperative transmission is a promising technology for underwater acoustic sensor networks (UASNs) to ensure the effective collection of underwater information. In this paper, we study the joint relay selection and power allocation problem to maximize the cumulative quality of information transmission in energy harvesting-powered UASNs (EH-UASNs). First, we formulate the process of cooperative transmission with joint strategy optimization as a Markov decision process model. In the proposed model, an effective state expression is presented to better reveal interactive relationship between learning and environment, thereby improving the learning ability. Then, we further propose a novel reward function which can guide nodes to adjust power strategy adaptively to balance instantaneous capacity and long-term quality of service (QoS) under the dynamic unpredictable energy harvesting. More specifically, we propose a deep Q-network-based resource allocation algorithm for EH-UASNs to solve the complex coupled strategy optimization problem without any prior underwater environment information. Finally, simulation results verify the superior performance of the proposed algorithm in improving the cumulative network capacity and reducing outages.

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Section: Problem Formulation and Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deep Q-Network-Based Cooperative Transmission Joint Strategy Optimization Algorithm for Energy Harvesting-Powered Underwater Acoustic Sensor Networks

Han

2020

Sensors

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“…With the dramatic growth of user devices, especially those with low-cost and low-power requirements, we can envisage future networks employing wireless relays capable of using harvested power for information forwarding, rather than depending on the grid power supply. To this end, simultaneous wireless information and power transfer (SWIPT) technique is an effective means to realize both energy harvesting (EH) and information decoding from the transmitted radio-frequency (RF) signals, prolonging the network lifetime of relays [2]- [4]. Various SWIPT-based relay schemes based on time-switching relaying (TSR) and power-splitting relaying (PSR) have been proposed, including multiple-input multiple-output (MIMO) DF relay [5], self interference-aided EH relaying [6], and relays with interference alignment [7].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Rate Fairness in Multi-Pair Wireless-Powered Relaying Systems

Bui

Nguyen

et al. 2020

IEEE Commun. Lett.

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This letter considers a multi-pair decode-andforward relay network where a power-splitting (PS) protocol is adopted at the energy-constrained relay to provide simultaneous wireless information and energy harvesting (EH). To achieve higher efficiency of EH, we propose a new PS-based EH architecture at the relay by incorporating an alternating current (AC) computing logic, which is employed to directly use the wirelessly harvested AC energy for computational blocks. Under a nonlinear EH circuit, our goal is to maximize the fairness of end-to-end rate among user pairs subject to power constraints, resulting in a nonconvex problem. We propose an iterative algorithm to achieve a suboptimal and efficient solution to this challenging problem by leveraging the inner approximation framework. Numerical results demonstrate that the proposed algorithm outperforms the traditional direct current computing and other baseline schemes.Index Terms-Inner approximation, relay network, simultaneous wireless information and power transfer (SWIPT).

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“…The first method is mainly reducing the consumed power of the sensor nodes by using an efficient communication system to increase the battery life as much as possible [2, 18, 19]. In the second method, researchers tried their best to maximise the predictable overall delivered data over a finite time slot based on energy‐based protocols [20, 21]. In the third method, the energy harvesting source is a water current, underwater environment, and acoustic waves [22, 23].…”

Section: Introductionmentioning

confidence: 99%

Wireless information and power transfer for underwater acoustic time‐reversed NOMA

et al. 2020

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Optimal Power Allocation for Full-Duplex Underwater Relay Networks With Energy Harvesting: A Reinforcement Learning Approach

Cited by 50 publications

References 18 publications

Deep Q-Network-Based Cooperative Transmission Joint Strategy Optimization Algorithm for Energy Harvesting-Powered Underwater Acoustic Sensor Networks

Deep Q-Network-Based Cooperative Transmission Joint Strategy Optimization Algorithm for Energy Harvesting-Powered Underwater Acoustic Sensor Networks

Optimization of Rate Fairness in Multi-Pair Wireless-Powered Relaying Systems

Wireless information and power transfer for underwater acoustic time‐reversed NOMA

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