Inverse Scattering-Enabled Integration of Sensing, Identification, and Backscatter Communication for Near-Field Driven 6G Networks

Near-field integrated sensing and backscatter communication (ISAC) has emerged as a key technology for Sixth Generation (6G) networks, offering efficient utilization of spectral and spatial resources. However, the transition from 5G to 6G introduces significant challenges, including increased energy demand and exponential growth in connectivity requirements, particularly for battery-constrained devices. Backscatter communication facilitates battery-free data transmission by harvesting energy from incident radio frequency (RF) signals and reflecting modulated data, making it a promising solution for energy-efficient communication. Meanwhile, inverse scattering technology exploits the principle of electromagnetic wave reflection to solve inverse scattering problems (ISPs), enabling precise and robust sensing. By integrating backscatter communication with inverse scattering techniques, ISAC can enhance both sensing and communication performance, paving the way for a novel paradigm in cost-effective and energy-efficient near-field ISAC networks. In this article, we propose a unified system that seamlessly combines backscatter communication and inverse scattering methods to realize simultaneous sensing, identification, and reliable backscatter communication. We begin by introducing the fundamental principles of backscatter communication and inverse scattering, emphasizing their complementary advantages. Subsequently, we present the architecture and operational mechanism of the proposed integrated sensing, identification, and backscatter communication (ISIABC) system. Furthermore, we provide a case study to evaluate the performance of the proposed system and validate its effectiveness through simulations and experimental results. Last but not least, we discuss key insights into the potential of the ISIABC system and outline several promising directions for future research.

© 2025 IEEE. All rights reserved, including rights for text and data mining.