Enhanced Fluid Index Modulation for Integrated Data and Energy Transfer

2026-06-03

AI Summary

This work addresses the challenge of simultaneously achieving reliable communication and efficient energy transfer in low-power wireless networks by proposing an integrated data and energy transmission scheme based on Fluid Index Modulation (FIM). For the first time, FIM is introduced into this domain, leveraging a two-dimensional fluid antenna system combined with a power-splitting receiver architecture to convey information jointly through modulation symbols and antenna indices. The scheme maximizes average harvested power under bit error rate and data rate constraints by jointly optimizing port selection, precoding vectors, and power splitting ratios. A low-complexity near-optimal optimization framework is developed using the Riemannian augmented Lagrangian method and block coordinate descent algorithm. Experimental results demonstrate that the proposed approach significantly outperforms existing methods in rate–energy tradeoff performance while exhibiting substantially lower computational complexity than exhaustive search.

Abstract

Integrated data and energy transfer (IDET) is a promising technique for supporting sustainable low-power wireless networks. To improve both communication reliability and energy transfer efficiency, this paper investigates a fluid index modulation (FIM) assisted IDET system, where the base station employs a two-dimensional fluid antenna system (FAS) and the receiver adopts a power-splitting architecture. In FIM, the information bits are delivered not only from the modulation symbols, but also the index of antenna position. Under finite-alphabet signaling, the average harvested power, bit error rate (BER), and achievable data rate are derived in closed form. A joint optimization problem is formulated to maximize the average harvested power subject to BER and achievable rate constraints by jointly optimizing the port selection, precoding vector, and power splitting ratio. An alternating optimization framework is developed, where the precoding vector and port selection are obtained via a Riemannian augmented Lagrangian method (RALM) and block coordinate descent (BCD) algorithm, respectively. Simulation results demonstrate that the proposed scheme achieves a superior rate-energy trade-off over benchmark schemes, while the proposed algorithm attains near-optimal performance with significantly lower complexity than exhaustive search.

Problem

• Integrated Data and Energy Transfer
• Fluid Index Modulation
• Energy Harvesting
• Bit Error Rate
• Rate-Energy Trade-off

Innovation

• Fluid Index Modulation
• Integrated Data and Energy Transfer
• Riemannian Augmented Lagrangian Method
• Power-Splitting Receiver
• Alternating Optimization