Cooperative Transmission of Energy-Constrained IoT Devices in Wireless-Powered Communication Networks

Jeong, Cheol; Son, Hyukmin

doi:10.1109/jiot.2020.3027101

Cited by 18 publications

(13 citation statements)

References 42 publications

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“…Therefore, OLA networks with amalgamation of energy harvesting also features an interesting dimension where a part of the incoming energy can be harvested for increasing the network lifetime, whereas the rest of the energy can be used for signal decoding/detection. Recently, References [82,83] have addressed a similar problem, where CT is used in energyconstrained devices for wireless-powered communications. The concepts can be further extended for OLA networks to study the effects of energy harvesting in each hop and the effects of cumulative energy savings can be studied in a multi-hop network.…”

Section: Cooperation and Wireless-powered Networkmentioning

confidence: 99%

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Nawaz

Kumar

Hassan

et al. 2021

Sensors

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Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

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Section: Cooperation and Wireless-powered Networkmentioning

confidence: 99%

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Nawaz

Kumar

Hassan

et al. 2021

Sensors

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“…Compared with the conventional battery solution, there is no need to replace the batteries and the EH technology effectively enhances the sustainability of nodes in the WPCN. Some researchers study the WPCN scenario where the nodes harvest the energy from the RF signal of the hybrid access point (HAP) in the downlink and store it in their batteries and transmit data to the HAP in the uplink when the nodes need to communicate and have the sufficient energy [10][11][12]. To be specific, according to the joint optimization of energy and time allocation, Lee et al [10] maximized the throughput of the WPCN based on a dynamic time division multiple access (TDMA) approach; Song et al [11] maximized the throughput of the WPCN based on the nonorthogonal multiple access (NOMA) transmission.…”

Section: Introductionmentioning

confidence: 99%

“…To be specific, according to the joint optimization of energy and time allocation, Lee et al [10] maximized the throughput of the WPCN based on a dynamic time division multiple access (TDMA) approach; Song et al [11] maximized the throughput of the WPCN based on the nonorthogonal multiple access (NOMA) transmission. By designing the transmit covariance matrices for both wireless information transmission (WET) and wireless information transmission (WIT), Jeong and Son [12] maximized the uplink capacity based on the Lagrangian method.…”

Section: Introductionmentioning

confidence: 99%

Robustness-Based Transmission Strategy for Wireless-Powered Communication Networks

Liu

Wang

et al. 2022

Wireless Communications and Mobile Computing

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In the wireless powered communication network (WPCN), the deployed nodes that harvest energy from the power station (PS) and then transmit data to the access point (AP) may waste wireless information transmission (WIT) opportunities due to the suffered faults. Confronting this dilemma, we propose a novel metric robustness, defined as the number of available nodes for WIT, and evaluate its impact on the throughput. To optimize the tradeoff between the throughput and robustness, we design an energy threshold approach, where the robustness decreases with the energy threshold and the throughput first increases and then decreases with it due to the tradeoff between the WIT rate and WIT opportunities. In the designed approach, we formulate the nodes with different energy states as Markov chain processes and prove the existence of steady-state probability distribution. Moreover, in the scenario with high robustness by the designed approach, we select the nodes with higher energy for WIT by the improved k -means++ algorithm, in order to increase the throughput. Finally, simulations validate the theoretical analysis of the throughput and robustness performances under the improved k -means++ algorithm and show that, compared with the comparison algorithms, the improved k -means++ algorithm achieves similar throughput and robustness performances with low computational complexity.

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“…To sustain long-term communication, an optimized energy usage based on energy-cooperative technique has been developed. The concept of energy cooperation is not a new idea and is addressed by a number of researchers [4]- [7] , where an energyrich device shares a portion of its energy to another energy-hungry device . This sustains the long service lifetime of devices and improves the overall system performance, despite some energy losses incurred during energy transfer.…”

Section: Introductionmentioning

confidence: 99%

“…The authors in [6] studied a Partially Observed Markov Decision Process (POMDP) based energy cooperative transmission policy for multiple access model which maximizes the long term system throughput. Recently, the authors in [7] studied cooperative transmission of Energy-Constrained IoT Devices where IoT devices share signals with other devices and cooperate to transmit the signals to the destination using the harvested energy.…”

Section: Introductionmentioning

confidence: 99%

Energy Cooperative Transmission Policy for Energy Harvesting Tags

Mulatu¹,

Dlamini²,

Shongwe³

et al. 2021

Preprint

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To sustain communication reliability and use the harvested energy effectively, it is crucial to consider energy sharing between energy harvesting tags (EHT) in a multiple access network, which are basic building blocks for the internet of things (IoT) applications. This technique also achieves higher throughput compared with the non-cooperative strategies despite energy losses occurred during energy transfer. We propose an energy cooperative communication strategy for a multiple access network of tags that depends on the harvested battery energy. We develop an optimal transmission policy for EHTs that maximises the long-term joint average throughput using a Markov decision process (MDP) model. Simulation results show that the proposed energy cooperative policy produces improved performance than traditional policies.

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Cooperative Transmission of Energy-Constrained IoT Devices in Wireless-Powered Communication Networks

Cited by 18 publications

References 42 publications

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Opportunistic Large Array Propagation Models: A Comprehensive Survey

Robustness-Based Transmission Strategy for Wireless-Powered Communication Networks

Energy Cooperative Transmission Policy for Energy Harvesting Tags

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