Weighted Sum Power Maximization for Intelligent Reflecting Surface Aided SWIPT (1907.05558v4)

Abstract: The low efficiency of far-field wireless power transfer (WPT) limits the fundamental rate-energy (R-E) performance trade-off of the simultaneous wireless information and power transfer (SWIPT) system. To address this challenge, we propose in this letter a new SWIPT system aided by the emerging intelligent reflecting surface (IRS) technology. By leveraging massive low-cost passive elements that are able to reflect the signals with adjustable phase shifts, IRS achieve a high passive beamforming gain, which is appealing for drastically enhancing the WPT efficiency and thereby the R-E trade-off of SWIPT systems. We consider an IRS being deployed to assist a multi-antenna access point (AP) to serve multiple information decoding receivers (IDRs) and energy harvesting receivers (EHRs). We aim to maximize the weighted sum-power received by EHRs via jointly optimizing the transmit precoders at the AP and reflect phase shifts at the IRS, subject to the individual signal-to-interference-plus-noise ratio (SINR) constraints for IDRs. Since this problem is non-convex, we propose efficient algorithms to obtain suboptimal solutions for it. In particular, we prove that it is sufficient to send information signals only at the AP to serve both IDRs and EHRs regardless of their channel realizations. Moreover, simulation results show significant performance gains achieved by our proposed designs over benchmark schemes.

• The paper introduces an IRS-aided SWIPT framework that maximizes weighted sum power for energy harvesting receivers while ensuring SINR requirements for information decoding receivers.
• It employs alternating optimization to jointly adjust transmit precoding and IRS phase shifts, effectively balancing the rate-energy trade-off.
• Numerical simulations reveal significant performance gains over benchmarks, highlighting IRS's potential for energy-efficient wireless communication.

Analysis of "Weighted Sum Power Maximization for Intelligent Reflecting Surface Aided SWIPT"

The examined paper presents a paper on the integration of Intelligent Reflecting Surfaces (IRS) into Simultaneous Wireless Information and Power Transfer (SWIPT) systems. Acknowledging the inherent inefficiencies of wireless power transfer (WPT) at far-field distances, the authors propose an IRS-aided SWIPT framework, aiming to bolster the energy harvesting capabilities while balancing the rate-energy trade-off.

Key Contributions

• IRS-Assisted SWIPT Framework: The paper integrates IRS technology into SWIPT systems, utilizing its ability to alter the phase shift of the transmitted signal with high passive broadcast capability. This setup is designed to enhance WPT efficiency without the need for numerous active transmit RF chains.
• Weighted Sum-Power Maximization: The authors focus on maximizing the weighted sum-power received by energy harvesting receivers (EHRs) while ensuring that information decoding receivers (IDRs) meet their signal-to-interference-plus-noise ratio (SINR) requirements. The problem is notably non-convex, prompting the derivation of suboptimal but effective solution algorithms.
• Absence of Dedicated Energy Beams: An interesting theoretical result derived by the authors is that sending dedicated energy signals is unnecessary when IRS is employed, given there is at least one IDR in the system. This finding extends the conventional SWIPT understanding and has significant implications for energy efficiency optimization.
• Algorithmic Solutions: To tackle the non-convex optimization problem, the paper employs alternating optimization techniques, enabling an efficient trade-off between transmit precoding and IRS-phase adjustments. The algorithms are iteratively solved, proving their convergence and effectiveness through simulation.
• Numerical Insights: The paper's simulations illustrate substantial performance boosts over benchmark methodologies, notably showcasing the IRS's capability to create effectively interference-free zones, thereby increasing the energy harvesting efficiency.

Implications and Future Directions

The integration of IRS into SWIPT architectures, as provided by this research, has significant implications. The capability of IRS to modify the propagation environment passively and constructively can lead to more energy-conservative designs in next-generation wireless networks, such as those required by IoT devices.

Future investigations can be directed towards:

• Scalability: Assessing how scalable the proposed frameworks are for more extensive network topologies with a myriad of EHRs and IDRs.
• Robustness to Imperfect Channel Estimation: As channel state information (CSI) is pivotal to IRS operation, future work could explore the system’s robustness to imperfect CSI.
• Joint Design Approaches: Developing more sophisticated joint optimization frameworks that concurrently consider IRS-induced multidimensional channel effects and user mobility.

Conclusion

The paper furnishes a comprehensive analysis and solution framework for enhancing SWIPT systems using IRS, making meaningful advances in the field of wireless energy transfer. The approach underscores the potential enhancements that IRS can bring to wireless networks, paving the way for more energy-efficient and adaptable communication systems in the future.