Nonlinear power harvesting through $$\alpha$$ α -fair resource allocation in SWIPT

Nonlinear power harvesting through $$\alpha$$ α -fair resource allocation in SWIPT

Abstract The concurrent nature of multiuser (MU) simultaneous wireless information and power transfer (SWIPT), coupled with the complexity of orthogonal frequency division multiplexing (OFDM) and precoding, poses a challenging non-convex resource allocation problem. While conventional methods like s...

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Bibliographic Details
Main Authors: Richard Ketcham, Marc Moonen
Format: Article
Language:English
Published: SpringerOpen 2025-03-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Energy harvesting
Fairness
Multiuser
Multicarrier
Multiantenna
Nonlinear
Online Access:https://doi.org/10.1186/s13638-025-02427-2
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Summary:Abstract The concurrent nature of multiuser (MU) simultaneous wireless information and power transfer (SWIPT), coupled with the complexity of orthogonal frequency division multiplexing (OFDM) and precoding, poses a challenging non-convex resource allocation problem. While conventional methods like subcarrier assignment or interference suppression can enhance tractability, they are not always optimal. Recent work has proposed leveraging hidden convexity in multicarrier systems to bypass these suboptimal methods, instead utilizing a multiple access channel (MAC)-broadcast channel (BC) duality for a near-optimal linear precoder design. However, this novel strategy relies on a linear power harvesting model, disregarding the nonlinear character of power harvesting in SWIPT networks. This paper addresses this issue by incorporating nonlinear power harvesting effects through a power harvesting model based on sigmoidal-like functions. Sigmoidal-like functions, being neither convex nor concave, typically necessitate transformation for tractability, a challenge compounded by the MAC-BC duality. We propose an alternate approach in which a parameterized class of utility functions known as $$\alpha$$ α -fairness is used to generalize the SWIPT resource allocation problem and concavify the nonlinear power harvesting model. This methodology simplifies optimization and facilitates the integration of nonlinear effects across a broad spectrum of fairness values.
ISSN:1687-1499

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