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Javier Lorca Hernando

Publications and source records attributed to Javier Lorca Hernando.

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Compressed Sensing-Driven Near-Field Localization Exploiting Array of Subarrays

Near-field localization for ISAC requires large-aperture arrays, making fully-digital implementations prohibitively complex and costly. While sparse subarray architectures can reduce cost, they introduce severe estimation ambiguity from grating lobes. To address both issues, we propose SHARE (Sparse Hierarchical Angle-Range Estimation), a novel two-stage sparse recovery algorithm. SHARE operates in two stages. It first performs coarse, unambiguous angle estimation using individual subarrays to resolve the grating lobe ambiguity. It then leverages the full sparse aperture to perform a localized joint angle-range search. This hierarchical approach avoids an exhaustive and computationally intensive two-dimensional grid search while preserving the high resolution of the large aperture. Simulation results show that SHARE significantly outperforms conventional one-shot sparse recovery methods, such as Orthogonal Matching Pursuit (OMP), in both localization accuracy and robustness. Furthermore, we show that SHARE's overall localization accuracy is comparable to or even surpasses that of the fully-digital 2D-MUSIC algorithm, despite MUSIC having access to the complete, uncompressed data from every antenna element. SHARE therefore provides a practical path for high-resolution near-field ISAC systems.

eess.SP

Advanced Closed-Loop Method with Limited Feedback for ISAC

6G wireless networks are poised to seamlessly integrate communication, computing, localization, and sensing functionalities, ensuring high reliability and trustworthiness. This paper introduces Smart Sensing Feedback (SSF), a limited-feedback framework designed to enhance sensing capabilities while maintaining communication performance. SSF adapts the concept of retransmission from communication to sensing. Specifically, we focus on downlink (DL) bistatic sensing, where the User Equipment (UE) performs measurements from reflected sensing signals and provides feedback to the network (NW). In sensing services, UE reporting can vary significantly due to dynamic factors such as target characteristics, environmental conditions, and UE status. Our results demonstrate that SSF significantly improves sensing quality while preserving communication efficiency. Additionally, it enhances key performance metrics such as probability of detection, latency, and power consumption. These improvements underscore SSF's ability to deliver robust, low-overhead feedback and adaptability to support a wide range of ISAC applications.

eess.SP

Integrating Sensing and Communications in 6G? Not Until It Is Secure to Do So

Integrated Sensing and Communication (ISAC) is emerging as a cornerstone technology for forthcoming 6G systems, significantly improving spectrum and energy efficiency. However, the commercial viability of ISAC hinges on addressing critical challenges surrounding security, privacy, and trustworthiness. These challenges necessitate an end-to-end framework to safeguards both communication data and sensing information, particularly in ultra-low-latency and highly connected environments. Conventional solutions, such as encryption and key management, often fall short when confronted with ISAC's dual-functional nature. In this context, the physical layer plays a pivotal role: this article reviews emerging physical-layer strategies, including artificial noise (AN) injection, cooperative jamming, and constructive interference (CI), which enhance security by mitigating eavesdropping risks and safeguarding both communication data and sensing information. We further highlight the unique privacy issues that ISAC introduces to cellular networks and outline future research directions aimed at ensuring robust security and privacy for efficient ISAC deployment in 6G.

cs.IT