Beamforming Design for Integrated Sensing and Wireless Power Transfer Systems

Abstract

This letter proposes a new concept of integrated sensing and wireless power transfer (ISWPT), where radar sensing and wireless power transfer functions are integrated into one hardware platform. ISWPT provides several benefits from the integrating operation such as system size, hardware cost, power consumption, and spectrum saving, which is envisioned to facilitate future 6G wireless networks. As the initial study, we aim to characterizing the fundamental trade-off between radar sensing and wireless power transfer, by optimizing transmit beamforming vectors. We first propose a semi-definite relaxationbased approach to solve the corresponding optimization problem globally optimal, and then provide a low-complexity sub-optimal solution. Finally, numerical results verify the effectiveness of our proposed solutions, and also show the trade-off between radar sensing and wireless power transfer.Index terms-Radar sensing, wireless power transfer, integrated sensing and wireless power transfer (ISWPT).

Optimal transmit beamforming for near-field integrated sensing and wireless power transfer systems

“…In this subsection, we aim to solve the non-convex problem (9) globally optimally. To this end, we first introduce a new auxiliary variable and then transform Formula (9) into the equivalent form 15) is non-convex with respect to optimization variables .…”

“…Inspired by the idea of dual-functional radar communication (DFRC) where both radar and communication functionalities are jointly designed and implemented using the same hardware platform [8,9] , the authors in Ref. [10] proposed a novel concept of integrated sensing and wireless power transfer (ISWPT).…”

Resource Allocation for Large IRS-Assisted SWIPT Systems with Non-linear Energy Harvesting Model

“…The integration of ISAC with SWIPT has seen its applications. In [12]- [14], the authors considered the integrated sensing, communication, and powering system. Zeng et al [12] proposed a difference-of-convex-based algorithm to minimize the beampattern error while satisfying the requirements of the EHR and the CUs.…”

“…Chen et al [13] investigated the tradeoff between sensing, communication, and powering in the multifunctional multiple-input multiple-output (MIMO) system by characterizing the achievable CRB-rate-energy region and its Pareto boundary. Yang et al [14] studied the intelligent reflecting surfaces (IRS)-assisted SWIPT service, where the transmit beamforming at the BS and the passive beamforming at the IRS were jointly optimized. However, existing works assumed static EHR and the location uncertainty caused by mobile EHR has not been tackled.…”