Title of paper: Multi-Functional Reconfigurable Intelligent Surfaces for a Multi-Functional System: Integrating Sensing, Communication, and Wireless Power Transfer
Authors: Ahmed Magbool, Vaibhav Kumar, Ahmad Bazzi, Mark F Flanagan and Marwa Chafii
Link to the paper: https://ieeexplore.ieee.org/abstract/document/10720877
What’s this paper about?
Communication networks are evolving from solely emphasising communication to facilitating multiple functionalities. In this regard, Integrated Sensing, Communication, and Powering (ISCAP) provides an efficient way of enabling data transmission, radar sensing, and wireless power transfer simultaneously. Such a multi-functional network requires a multi-functional architectural solution. Toward this end, Sensor-Aided Zero-Energy Reconfigurable Intelligent Surfaces (SAZE-RISs) offer an energy-efficient solution for ISCAP by meeting the requirements of the end users as well as supplying power for the RIS. This paper explores the use of SAZE-RIS within the ISCAP framework. First, we present the general system architecture, operational protocols, and main application scenarios for employing SAZE-RIS in ISCAP. Next, we discuss methods for managing the conflicting requirements of communication, sensing, and powering within ISCAP and the role of SAZE-RIS in this process. We then provide a detailed case study complete with simulation results, offering valuable insights into the design choices and trade-offs that come into play when adopting this technology. Furthermore, we discuss the related challenges and open research avenues, highlighting areas that require further exploration to fully realize the potential of SAZE-RIS within this ISCAP framework.
What have you discovered?
Our study delves into the system architecture, operational protocols, and key application scenarios of SAZE-RIS in ISCAP networks, focusing on managing the competing requirements of communication, sensing, and powering. A detailed case study, supported by simulation results, highlights critical design considerations and the trade-offs involved. Additionally, we discuss challenges and potential research directions, emphasizing the need for further investigation to maximize SAZE-RIS effectiveness in ISCAP applications.
Fig. 1 illustrates the general system architecture and transmission protocols for SAZE-RIS-assisted ISCAP. In this setup, a multiple-input multiple-output (MIMO) base station (BS) transmits an ISCAP signal with the aim of simultaneously transmitting data to a cluster of users, sensing multiple targets, and supplying power to a number of energy receivers with the assistance of a SAZE-RIS. The SAZE-RIS consists of multiple elements, each capable of fulfilling one or more of three primary functions.
- Reflecting elements to redirect the signal towards the receivers, either with or without amplitude amplification.
- Radar sensors: to sense the reflected echoes from radar targets. These echo signals are then forwarded to a processing unit for further analysis. Due to the randomness in communication data that might reduce the accuracy of echo processing, the presence of a backhaul link between the BS and the SAZE-RIS is essential. This link could be established either wirelessly or through wired means.
- Energy harvesting (EH) elements to partially absorb the energy of the incident signal(s) and store it in a battery to power the SAZE-RIS.
To facilitate the operation of SAZE-RIS, one of three protocols can be adopted.
- Element-splitting (ES) protocol: In the ES protocol, SAZE-RIS elements are divided into three distinct groups: reflecting elements, EH elements, and sensor elements, which operate simultaneously. This segmentation simplifies circuit design by assigning each element a specific task. It also eliminates the need to fine-tune the division parameters for each transmission. However, this approach offers limited flexibility in adapting to changing system conditions. Optimal division can still be achieved by prioritizing certain functionalities based on statistical models that account for the behavior and locations of communication users, radar targets, and energy receivers.
- Time-splitting (TS) protocol: The TS protocol alternates the function of a set of SAZE-RIS elements between reflecting and EH roles in different time slots, while a separate group remains as dedicated sensor elements. This approach provides greater flexibility compared to the ES protocol, allowing for optimization of instantaneous performance metrics for communication and SAZE-RIS powering. However, it requires a more complex hardware design, with switches needed to connect elements to one of two circuits.
- Power-splitting (PS) protocol: In the PS protocol, SAZE-RIS elements split the energy of the incoming signals from the BS, with part of the signal absorbed for EH and the rest reflected to the receivers. This setup allows the energy harvesting and reflecting elements to work simultaneously, while the sensor elements operate in an ES mode. The division of tasks is controlled by a PS parameter, which can be adjusted to optimize specific performance metrics, offering flexibility similar to the TS approach. However, the PS protocol introduces challenges, including increased hardware complexity due to the need for splitting, reflecting, and EH circuits for each element, and added complexity in solving resource allocation problems when incorporating the PS parameter.
Figure 2 shows how the splitting factor (in all the three protocols) affects the average transmit power needed for the system. When the number of transmit antennas (Nt) increases, the average transmit power requirement decreases, thanks to enhanced beamforming at the base station. There’s an optimal value of the splitting factor for each protocol, which needs to be set correctly for the best performance. For the PS protocol, a low splitting factor means that only a small part of the signal power received by the RIS is used for reflection, with most of it harvested for RIS operation. As the splitting factor increases, more power goes toward signal reflection, reducing the average transmit power needed. However, if the splitting factor becomes too high, very little power is left for harvesting, which limits performance and leads to a higher transmit power requirement. The system behaves similarly with the TS and ES protocols.
So what?
One key lesson learned from this research is that as communication networks are expanding to handle multiple functions beyond data transmission—such as radar sensing and wireless power transfer—they require innovative and integrated architectural solutions like ISCAP . The study highlights that SAZE-RISs are promising for addressing the power and efficiency needs of these multi-functional networks. By incorporating SAZE-RIS, ISCAP can effectively balance the demands of communication, sensing, and powering, providing a scalable and energy-efficient approach that meets end-user requirements while also supporting the power needs of the RIS itself.
Additionally, the findings underscore the importance of carefully managing the design trade-offs involved in ISCAP systems. The case study and simulations presented reveal that while SAZE-RIS can significantly enhance system performance, it also brings specific challenges, such as balancing signal reflection and power harvesting, which must be optimized for each protocol used. This study highlights the need for further research into these optimization strategies and points out key areas for improvement, particularly in developing protocols that effectively manage these trade-offs. This groundwork establishes a path for future exploration to fully harness the potential of SAZE-RIS in achieving energy-efficient, multi-functional networks.
The implementation of SAZE-RIS for ISCAP has significant implications for real-world applications, particularly in terms of energy savings, cost reduction, and carbon neutrality. By optimizing signal reflection and energy harvesting, SAZE-RIS systems can enhance wireless network efficiency, reducing overall power demand and operational costs despite potential higher initial manufacturing expenses. The transition to such technology can lower the carbon footprint of telecommunications by integrating renewable energy sources and minimizing reliance on traditional power grids. However, careful management of design trade-offs is essential, particularly in balancing signal reflection and energy harvesting, to ensure optimal performance. Future research into adaptive protocols that effectively navigate these trade-offs will be crucial for fully harnessing the potential of SAZE-RIS, contributing to the development of more sustainable and cost-effective communication networks that align with global initiatives for reduced carbon emissions.