Passive Beamforming and Information Transfer via Large Intelligent Surface

Abstract: Large intelligent surface (LIS) has emerged as a promising new solution to improve the energy and spectrum efficiency of wireless networks. A LIS, composed of a large number of low-cost and energy-efficient reconfigurable passive reflecting elements, enhances wireless communications by reflecting impinging electro-magnetic waves. In this paper, we propose a novel passive beamforming and information transfer (PBIT) technique, in which the LIS simultaneously enhances the primary communication and sends information to the receiver. We develop a passive beamforming method to improve the average receive signal-to-noise ratio (SNR).We also establish a two-step approach at the receiver to retrieve the information from both the transmitter and the LIS. Numerical results show that the proposed PBIT system, especially with the optimized passive beamforming, significantly outperforms the system without LIS enhancement. Furthermore, a tradeoff between the passive-beamforming gain and the information rate of the LIS has been demonstrated.

• The paper introduces a novel Passive Beamforming and Information Transfer (PBIT) technique that uses Large Intelligent Surfaces (LIS) to simultaneously enhance wireless signals and transmit data.
• The PBIT technique enables concurrent data transfer by encoding information in the on/off states of LIS reflecting elements using spatial modulation.
• Numerical simulations demonstrate that systems employing PBIT via LIS achieve significant performance improvements, suggesting potential for enhanced energy and spectrum efficiency.

Passive Beamforming and Information Transfer via Large Intelligent Surface: An Overview

The research paper titled "Passive Beamforming and Information Transfer via Large Intelligent Surface" by Wenjing Yan, Xiaoyan Kuai, and Xiaojun Yuan investigates an innovative technique to enhance wireless communications using large intelligent surfaces (LIS). The focus of this study is on developing a novel method for passive beamforming and information transfer (PBIT) using LIS, which is a promising technology to improve both the energy and spectrum efficiency of wireless networks.

LIS, also known as Intelligent Reflecting Surfaces (IRS), consists of a large array of low-cost and reconfigurable passive reflecting elements. These elements are designed to enhance wireless signals by reflecting incoming electromagnetic waves. The new PBIT technique introduced in this paper enables the LIS to not only boost the primary communication channel but also facilitate data transfer to the receiver.

Key Contributions

1. Passive Beamforming Design: The paper outlines a passive beamforming methodology aimed at maximizing the average receive signal-to-noise ratio (SNR) by intelligently adjusting the phase of the LIS elements.
2. Information Transfer: The proposed PBIT system allows LIS to concurrently transmit data along with enhancing user-to-base station communications. This is realized by using spatial modulation, where LIS data is encoded in the on/off state of LIS reflecting elements.
3. Numerical Validation: Through comprehensive simulations, the researchers demonstrate that systems incorporating the PBIT methodology exhibit significant improvements in performance over those without LIS enhancements. Specifically, a combination of passive beamforming and optimized LIS element control shows superior effectiveness in improving link quality and data transfer rates.
4. Tradeoffs Between Gain and Rate: The paper explores the interplay between passive beamforming gains and the LIS data rate, highlighting the balance required when designing systems for optimal performance.

Implications and Future Directions

The findings of this paper have substantial implications for future wireless networks, encapsulating both theoretical and practical advancements. The research paves the way for the implementation of LIS in terrestrial wireless communications, potentially overcoming hardware cost and energy consumption bottlenecks associated with other advanced wireless technologies like mmWave and MIMO.

Implementing PBIT systems could lead to reduced energy requirements and improved efficiency in dense urban environments or networks with high user demand. The realization of this technology in practical scenarios will depend on continued advancements in real-time control mechanisms and the development of efficient algorithms to handle dynamic environmental conditions.

Conclusion

The paper presents a significant step forward in the research and deployment of LIS-based communication systems. By harnessing the dual capabilities of passive beamforming and information transfer, the proposed PBIT technique provides a robust framework for enhancing next-generation wireless communications. As LIS technology matures, future research might focus on overcoming practical implementation challenges and exploring new applications within the evolving landscape of AI-driven communications systems.