Power allocation for wireless powered MIMO transmissions with non-linear RF energy conversion models

Shi, Liqin; Zhao, Liqiang; Liang, Kai

doi:10.1109/cc.2017.7868175

“…So, the linear model is considered with two conversion efficiencies: the maximum one ζ = 1 and a more realistic one ζ = 0.4. The number of transmit antennas at all the nodes is equal to 4 and the noise variances at the relay and destination are equal to −40 dB [9]. In all figures, the value of E max corresponds to maximum harvested energy Ψ max varying with the EH model considered either linear or nonlinear (sigmoidal or heuristic).…”

Section: Numerical Resultsmentioning

confidence: 99%

“…In [8], a new practical nonlinear EH model was proposed and its relevance was verified through the comparison with some experimental data results. In [9], a heuristic practical nonlinear EH model was considered in studying the power allocation algorithm of MIMO Systems. In [10], a rate-energy tradeoff region of SWIPT was studied for MIMO system considering the nonlinear EH model studied in [8].…”

Section: Introductionmentioning

confidence: 99%

Practical Nonlinear Energy Harvesting Model in MIMO DF Relay System with Channel Uncertainty

Benkhelifa

¹

,

Alouini

²

2018

2018 IEEE Global Communications Conference (GLOBECOM)

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In this paper, we aim to maximize the end-toend achievable rate of multiple-input multiple-output (MIMO) decode-and-forward (DF) where the relay is an energy harvesting (EH) node using the time switching (TS) scheme. The relay first harvests the energy from the source, then uses its harvested energy to forward the information carrying signal from the source to the destination. The EH model at the relay is a nonlinear model. Also, we assume that the channel knowledge is imperfect at the relay and destination. We propose the structure of the optimal covariance matrices at the source (during EH and information decoding periods), the optimal covariance matrix at the relay and the optimal EH time ratio. Through the simulation results, we compare between different linear/nonlinear EH models and we show the gain/loss performance of the linear model compared to other nonlinear EH models. Index Terms-Multiple-input multiple-output (MIMO), decode-and-forward (DF), radio frequency energy harvesting (EH), time switching (TS), nonlinear EH model, imperfect channel state information (CSI).

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“…For moderate to high powers, the practical energy harvesting model is approximated by the nonlinear model until it saturates at a certain point [30]. There are different nonlinear energy harvesting models in the literature: sigmoidal model [31], multi-sine model [32], heuristic model [33], etc. To generalize our energy harvesting model and take into consideration either linearity or nonlinearity, we consider a general function Ψ (•) modelling the relationship between P r and P H at each IoT device as…”

Section: A Stochastic Geometry Analysismentioning

confidence: 99%

Recycling Cellular Energy for Self-Sustainable IoT Networks: A Spatiotemporal Study

Benkhelifa

¹

,

ElSawy

²

,

McCann

³

et al. 2020

IEEE Trans. Wireless Commun.

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This paper investigates the self-sustainability of an overlay Internet of Things (IoT) network that relies on harvesting energy from a downlink cellular network. Using stochastic geometry and queueing theory, we develop a spatiotemporal model to derive the steady state distribution of the number of packets in the buffers and energy levels in the batteries of IoT devices given that the IoT and cellular communications are allocated disjoint spectrum. Particularly, each IoT device is modelled via a two-dimensional discrete-time Markov Chain (DTMC) that jointly tracks the evolution of the data buffer and energy battery. In this context, stochastic geometry is used to derive the energy generation at the batteries and the packet transmission success probability from buffers taking into account the mutual interference from other active IoT devices. To this end, we show the Pareto-Frontiers of the sustainability region, which define the network parameters that ensure stable network operation and finite packet delay. Furthermore, the spatially averaged network performance, in terms of transmission success probability, average queueing delay, and average queue size are investigated. For self-sustainable networks, the results quantify the required buffer size and packet delay, which are crucial for the design of IoT devices and time critical IoT applications.

show abstract

“…For moderate to high powers, the practical energy harvesting model is approximated by the nonlinear model until it saturates at a certain point [30]. There are different nonlinear energy harvesting models in the literature: sigmoidal model [31], multi-sine model [32], heuristic model [33], etc. To generalize our energy harvesting model and take into consideration either linearity or non-linearity, we consider a general function Ψ (·) modelling the relationship between P r and P H at each IoT device as…”

Section: ) Packet Transmissionmentioning

confidence: 99%

Recycling Cellular Energy for Self-Sustainable IoT Networks: A Spatiotemporal Study

Benkhelifa¹

2020

Preprint

0

View full text Add to dashboard Cite

This paper investigates the self-sustainability of an overlay Internet of Things (IoT) network that relies on harvesting energy from a downlink cellular network. Using stochastic geometry and queueing theory, we develop a spatiotemporal model to derive the steady state distribution of the number of packets in the buffers and energy levels in the batteries of IoT devices given that the IoT and cellular communications are allocated disjoint spectrum. Particularly, each IoT device is modelled via a two-dimensional discrete-time Markov Chain (DTMC) that jointly tracks the evolution of the data buffer and energy battery. In this context, stochastic geometry is used to derive the energy generation at the batteries and the packet transmission success probability from buffers taking into account the mutual interference from other active IoT devices. To this end, we show the Pareto-Frontiers of the sustainability region, which define the network parameters that ensure stable network operation and finite packet delay. Furthermore, the spatially averaged network performance, in terms of transmission success probability, average queueing delay, and average queue size are investigated. For self-sustainable networks, the results quantify the required buffer size and packet delay, which are crucial for the design of IoT devices and time critical IoT applications.

show abstract

Power allocation for wireless powered MIMO transmissions with non-linear RF energy conversion models

Cited by 15 publications

References 0 publications

Practical Nonlinear Energy Harvesting Model in MIMO DF Relay System with Channel Uncertainty

Practical Nonlinear Energy Harvesting Model in MIMO DF Relay System with Channel Uncertainty

Recycling Cellular Energy for Self-Sustainable IoT Networks: A Spatiotemporal Study

Recycling Cellular Energy for Self-Sustainable IoT Networks: A Spatiotemporal Study

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