Robust Energy Harvesting Based on a Stackelberg Game

Sarma, Siddhartha; Kandhway, Kundan; Kuri, Joy

doi:10.1109/lwc.2016.2555901

Cited by 20 publications

(12 citation statements)

References 11 publications

(28 reference statements)

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“…In [31], the authors formulated a stochastic Stackelberg game to study the delay optimal power allocation scheme. There is a recent paper addressing the EAP assisted wireless energy harvesting by using Stackelberg game [19], but their system settings are different from those in our work. Only one EAP with multiple antennas was considered in this paper, and the EAP acts as the seller and the base station (BS) as the buyer in behalf of its sensors.…”

Section: Stackelberg Gamementioning

confidence: 99%

“…To successfully motivate self-interested EAPs to provide help, effective incentive mechanisms are required. There are several prior research works in designing the incentive mechanism [18]- [20] for the EAPs, where [18], [19] adopted Stackelberg game and [20] used auction to design the incentive mechanism. However, the existing incentive mechanisms only considered complete information scenario.…”

Section: A Eap Assisted Wireless Energy Harvestingmentioning

confidence: 99%

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Incentive Mechanism Design for Wireless Energy Harvesting-Based Internet of Things

Hou

Chen

et al. 2018

IEEE Internet Things J.

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Radio frequency energy harvesting (RFEH) is a promising technology to charge unattended Internet of Things (IoT) low-power devices remotely. To enable this, in future IoT system, besides the traditional data access points (DAPs) for collecting data, energy access points (EAPs) should be deployed to charge IoT devices to maintain their sustainable operations. Practically, the DAPs and EAPs may be operated by different operators, and the DAPs thus need to provide effective incentives to motivate the surrounding EAPs to charge their associated IoT devices. Different from existing incentive schemes, we consider a practical scenario with asymmetric information, where the DAP is not aware of the channel conditions and energy costs of the EAPs. We first extend the existing Stackelberg gamebased approach with complete information to the asymmetric information scenario, where the expected utility of the DAP is defined and maximized. To deal with asymmetric information more efficiently, we then develop a contract theory-based framework, where the optimal contract is derived to maximize the DAP's expected utility as well as the social welfare. Simulations show that information asymmetry leads to severe performance degradation for the Stackelberg game-based framework, while the proposed contract theory-based approach using asymmetric information outperforms the Stackelberg game-based method with complete information. This reveals that the performance of the considered system depends largely on the market structure (i.e., whether the EAPs are allowed to optimize their received power at the IoT devices with full freedom or not) than on the information availability (i.e., the complete or asymmetric information).

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Section: Stackelberg Gamementioning

confidence: 99%

Section: A Eap Assisted Wireless Energy Harvestingmentioning

confidence: 99%

Incentive Mechanism Design for Wireless Energy Harvesting-Based Internet of Things

Hou

Chen

et al. 2018

IEEE Internet Things J.

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“…The PB can make a profile by pricing the energy sends to each sensor node. The iteration between the PB and energy receivers can be modeled by Stackelberg game [22,23,24,25]. In [22], Liu et al studied the pricing problem for operating the antennas in the massive-MIMO enabled wireless virtualized networks by Stackelberg game.…”

Section: Introductionmentioning

confidence: 99%

“…The energy pricing issue is not addressed in [22]. In [23], Sarma et al studied the Stackelberg game between a BS and a multi-antenna PB for wireless energy harvesting in a multiple sensor nodes (SNs) scenario. An analytical solution is given for a single SN’s case.…”

Section: Introductionmentioning

confidence: 99%

Price-Based Resource Allocation in Wireless Power Transfer-Enabled Massive MIMO Networks

Wang

Huang

Yang

et al. 2019

Sensors

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This paper considers the price-based resource allocation problem for wireless power transfer (WPT)-enabled massive multiple-input multiple-output (MIMO) networks. The power beacon (PB) can transmit energy to the sensor nodes (SNs) by pricing their harvested energy. Then, the SNs transmit their data to the base station (BS) with large scale antennas by the harvesting energy. The interaction between PB and SNs is modeled as a Stackelberg game. The revenue maximization problem of the PB is transformed into the non-convex optimization problem of the transmit power and the harvesting time of the PB by backward induction. Based on the equivalent convex optimization problem, an optimal resource allocation algorithm is proposed to find the optimal price, energy harvesting time, and power allocation for the PB to maximize its revenue. Finally, simulation results show the effectiveness of the proposed algorithm.

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“…A dynamic hybrid-access control framework was defined in [ 18 ] exploiting the mentioned game. For energy harvesting schemes [ 19 , 20 ], some secure Stackelberg games have been provided to keep the quality of service.…”

Section: Introductionmentioning

confidence: 99%

A Newly Secure Solution to MIMOME OFDM-Based SWIPT Frameworks: A Two-Stage Stackelberg Game for a Multi-User Strategy

Zamanipour¹

2018

Entropy

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Abstract:The paper technically proposes a newly secure scheme for simultaneous wireless power and information transfer (SWIPT) frameworks. We take into account an orthogonal frequency division multiplexing (OFDM)-based game which is in relation to a multi-input multi-output multi-antenna Eavesdropper (MIMOME) strategy. The transceiver is generally able to witness the case imperfect channel state information (ICSI) at the transmitter side. Transferring power and information are conducted via orthogonally provided sub-carriers. We propose a two-step Stackelberg game to optimise the Utility Functions of both power and information parts. The price for the first stage (in connection with information) is the total power of the other sub-carriers over which the energy is supported. In this stage, the sum secrecy rate should be essentially maximised. The second level of the proposed Stackelberg game is in association with the energy part. In this stage, the price essentially is the total power of the other sub-carriers over which the information is transferred. In this stage, additionally, the total power transferred is fundamentally maximised. Subsequently, the optimally and near-optimally mathematical solutions are derived, for some special cases such as ICSI one. Finally, the simulations validate our scheme as well, authenticating our contribution's tightness and efficiency.

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Robust Energy Harvesting Based on a Stackelberg Game

Cited by 20 publications

References 11 publications

Incentive Mechanism Design for Wireless Energy Harvesting-Based Internet of Things

Incentive Mechanism Design for Wireless Energy Harvesting-Based Internet of Things

Price-Based Resource Allocation in Wireless Power Transfer-Enabled Massive MIMO Networks

A Newly Secure Solution to MIMOME OFDM-Based SWIPT Frameworks: A Two-Stage Stackelberg Game for a Multi-User Strategy

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