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Integrating Sensing, Communication, and Power Transfer: From Theory to Practice

Xiaoyang Li, Zidong Han, Guangxu Zhu, Yuanming Shi, Jie Xu, Yi Gong, Qinyu Zhang, Kaibin Huang, Khaled B. Letaief

TL;DR

ISCPT extends ISAC and SWIPT by enabling simultaneous sensing, communication, and power transfer in the same band. The authors define a theoretical boundary via a multi-objective Pareto region, using $CRB_{\text{angle}}$, $CRB_{\mathrm{TRM}}$, achievable rate $R$, and harvested energy $E_H$ as coordinates. They propose three core technologies—spatial multiplexing, multi-target detection, and resource allocation—and validate the concept on an experimental platform at 2.45 GHz with 100 MHz bandwidth, demonstrating joint sensing, data transmission, and wireless power transfer. The work highlights nonlinear tradeoffs among sensing accuracy, data rate, and harvested energy, and provides a foundation for practical ISCPT deployments in 6G IoT.

Abstract

To support the development of internet-of-things applications, an enormous population of low-power devices are expected to be incorporated in wireless networks performing sensing and communication tasks. As a key technology for improving the data collection efficiency, integrated sensing and communication (ISAC) enables simultaneous data transmission and radar sensing by reusing the same radio signals. In addition to information carriers, wireless signals can also serve as energy delivers, which enables simultaneous wireless information and power transfer (SWIPT). To improve the energy and spectrum efficiency, the advantages of ISAC and SWIPT are expected to be exploited, leading to the emerging technology of integrating sensing, communication, and power transfer (ISCPT). In this article, a timely overview of ISCPT is provided with the description of the fundamentals, the characterization of the theoretical boundary, the discussion on the key technologies, and the demonstration of the implementation platform.

Integrating Sensing, Communication, and Power Transfer: From Theory to Practice

TL;DR

ISCPT extends ISAC and SWIPT by enabling simultaneous sensing, communication, and power transfer in the same band. The authors define a theoretical boundary via a multi-objective Pareto region, using , , achievable rate , and harvested energy as coordinates. They propose three core technologies—spatial multiplexing, multi-target detection, and resource allocation—and validate the concept on an experimental platform at 2.45 GHz with 100 MHz bandwidth, demonstrating joint sensing, data transmission, and wireless power transfer. The work highlights nonlinear tradeoffs among sensing accuracy, data rate, and harvested energy, and provides a foundation for practical ISCPT deployments in 6G IoT.

Abstract

To support the development of internet-of-things applications, an enormous population of low-power devices are expected to be incorporated in wireless networks performing sensing and communication tasks. As a key technology for improving the data collection efficiency, integrated sensing and communication (ISAC) enables simultaneous data transmission and radar sensing by reusing the same radio signals. In addition to information carriers, wireless signals can also serve as energy delivers, which enables simultaneous wireless information and power transfer (SWIPT). To improve the energy and spectrum efficiency, the advantages of ISAC and SWIPT are expected to be exploited, leading to the emerging technology of integrating sensing, communication, and power transfer (ISCPT). In this article, a timely overview of ISCPT is provided with the description of the fundamentals, the characterization of the theoretical boundary, the discussion on the key technologies, and the demonstration of the implementation platform.
Paper Structure (14 sections, 6 figures)

This paper contains 14 sections, 6 figures.

Figures (6)

  • Figure 1: ISCPT framework.
  • Figure 2: Theoretical boundary of ISCPT chen2022isac.
  • Figure 3: Spatial multiplexing for ISCPT li2023multi.
  • Figure 4: Multi-targets detection via ISCPT zeng2022beamforming.
  • Figure 5: Resource allocation for ISCPT li2022wirelessly.
  • ...and 1 more figures