Frequency-responsive RCS characteristics and scaling implications for ISAC development

This paper presents an investigation on the Radar Cross-Section (RCS) of various targets, with the objective of analysing how RCS properties vary with frequency. Targets such as an Automated Guided Vehicle (AGV), a pedestrian, and a full-scale car were measured in the frequency bands referred to in industry standards as FR2 and FR3. Measurements were taken in diverse environments, indoors and outdoors, to ensure comprehensive scenario coverage. The methodology employed in RCS extraction performs background subtraction, followed by time-domain gating to isolate the influence of the target. This analysis compares the RCS values and how the points of greatest contribution are distributed across different bands based on the range response of the RCS. Analysis of the results demonstrated how RCS values change with frequency and target shape, providing insights into the electromagnetic behaviour of these targets. Key findings highlight how much scaling RCS values based on frequency and geometry is complex and varies among different types of materials and shapes. These insights are instrumental for advancing sensing systems and enhancing 3GPP channel models, particularly for Integrated Sensing and Communications (ISAC) techniques proposed for 6G standards.

Novel Approach to Dual-Channel Estimation in Integrated Sensing and Communications for 6G

Integrated Sensing and Communication (ISAC) design is crucial for 6G and harmonizes environmental data sensing with communication, emphasizing the need to understand and model these elements. This paper delves into dual-channel models for ISAC, employing channel extraction techniques to validate and enhance accuracy. Focusing on millimeter wave (mmWave) radars, it explores the extraction of the bistatic sensing channel from monostatic measurements and subsequent communication channel estimation. The proposed methods involve interference extraction, module and phase correlation analyses, chirp clustering, and auto-clutter reduction. A comprehensive set-up in an anechoic chamber with controlled scenarios evaluates the proposed techniques, demonstrating successful channel extraction and validation through Root Mean Square Delay Spread (RMS DS), Power Delay Profile (PDP), and Angle of Arrival (AoA) analysis. Comparison with Ray-Tracing (RT) simulations confirms the effectiveness of the proposed approach, presenting an innovative stride towards fully integrated sensing and communication in future networks.

Cell Sensing: Traffic detection

This work presents a passive sensing system for traffic monitoring using ambient Long Term Evolution (LTE) signals as a non-intrusive and scalable alternative to traditional surveillance methods. The approach employs a dual-receiver architecture analyzing Channel State Information (CSI) to isolate differential Doppler shifts induced by moving targets, effectively mitigating hardware-induced phase impairments. Implemented with a Software Defined Radio (SDR) platform and srsRAN software, the system demonstrated over 90% detection accuracy for speeds above 6000 mm/min in controlled indoor tests, and provided reliable speed estimations for pedestrians and vehicles in outdoor evaluations. Despite challenges at low speeds, directional ambiguity, and multipath fading in urban settings, the results validate LTE-based passive sensing as a feasible traffic monitoring method, identifying critical areas for future research such as angle-of-arrival (AoA) integration, machine learning, and real-time embedded system development.