Robust Beamforming for Near-Field STAR-RIS-Enabled ISCPT

TL;DR

This paper proposes a robust beamforming framework for near-field STAR-RIS-enabled ISCPT, optimizing harvested power while ensuring security and sensing performance under imperfect channel information.

Contribution

It introduces a novel joint optimization approach using AO, S-procedure, SROCR, and SCA for near-field STAR-RIS-assisted ISCPT systems, addressing non-convex challenges.

Findings

Significant gains in harvested power demonstrated in simulations.

Outperforms conventional baselines in near-field scenarios.

Effectively balances power transfer, security, and sensing constraints.

Abstract

A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided near-field integrated sensing, communication, and power transfer (ISCPT) framework is proposed. We formulate a robust harvested power maximization problem under imperfect cascaded channel state information (CSI), with constraints on required user rate, eavesdropper tolerable rate, and minimum sensing beampattern gain. To address this non-convex problem, we adopt alternating optimization (AO). First, we approximate the semi-infinite inequality constraints using the S-procedure and obtain rank-one active beamforming via sequential rank-one constraint relaxation (SROCR); then we update the passive STAR-RIS coefficients with a penalty-based scheme refined by successive convex approximation (SCA). Simulations in the near field demonstrate notable gains in harvested power while meeting secrecy and beampattern targets, outperforming conventional baselines.