Sounding-Based Evaluation of Multi-Sensor ISAC Networks for Drone Applications: Measurement and Simulation Perspectives

With the upcoming multitude of commercial and public applications envisioned in the mobile 6G radio landscape using unmanned aerial vehicles (UAVs), integrated sensing and communication (ISAC) plays a key role to enable the detection and localization of passive objects with radar sensing, while optimizing the utilization of scarce resources. To explore the potential of future ISAC architectures with UAVs as mobile nodes in distributed multi-sensor networks, the system's fundamental capability to detect static and dynamic objects that reveal themselves by their bi-static back-scattering needs to be evaluated. Therefore, this paper addresses simulation- and measurement based data acquisition methods to gather knowledge about the bistatic reflectivity of single objects including their Micro-Doppler signature for object identification as well as the influence of multipath propagation in different environments on the localization accuracy and radar tracking performance. We show exemplary results from simulation models, bi-static reflectivity measurements in laboratory environment and real-flight channel sounding experiments in selected scenarios showcasing the potential of synthetic and measured data sets for development and evaluation of ISAC algorithms. The presented measurement data sets are publicly available to encourage the academic RF community to validate future algorithms using realistic scenarios alongside simulations models.

Accelerating Innovation in 6G Research: Real-Time Capable SDR System Architecture for Rapid Prototyping

The next global mobile communication standard 6G strives to push the technological limits of radio frequency (RF) communication even further than its predecessors: Data rates beyond 100 Gbit/s, RF bandwidths above 1 GHz, and sub-millisecond latency necessitate very high performance development tools to enable the extent of innovation required for 6G's likely features. We propose a new SDR firmware and software architecture designed explicitly to meet these challenging requirements. It relies on Ethernet and commercial off-the-shelf network and server components to maximize flexibility and to reduce costs. We analyze state-of-the-art solutions (USRP X440 and other RFSoC-based systems), derive architectural design goals, explain resulting design decision in detail, and exemplify our architecture's implementation on the XCZU48DR RFSoC. Finally, we prove its performance via measurements and outline how the architecture surpasses the state-of-the-art with respect to sustained RF recording while maintaining high Ethernet bandwidth efficiency. Building a micro-Doppler radar example, we demonstrate its real-time and rapid application development capabilities.

Static Reflectivity and Micro-Doppler Signature of Drones for Distributed ICAS

The integration of wireless communication and radar sensing is now getting a huge interest from researchers of two big societies, wireless communication and radar. The road map to the final goal and individual solutions to the challenges might differ in developing the Integrated Communication and Sensing (ICAS) system. However, the electromagnetic signature of the targets will be still valid for all variants of the ICAS system because the detection, localization and classification of the targets are involved. Therefore, this paper presents a study on static reflectivity and micro-Doppler signatures of drones together. To acquire the required data, the state-of-the-art measurement system, BiRa, is used.

Modelling Micro-Doppler Signature of Drone Propellers in Distributed ISAC

Integrated Sensing and Communication (ISAC) comprises detection and analysis of non-cooperative targets by exploiting the resources of the mobile radio system. In this context, micro-Doppler is of great importance for target classification, in order to distinguish objects with local movements. For developing algorithms for target classification, it is necessary to have a large amount of target signatures. Aiming to generate these data, this paper proposes a mathematical model for the micro-Doppler of drone rotating propellers, and validate the proposed model by comparing it to measured micro-Doppler. Results show that the proposed mathematical model can generate micro-Doppler data very similar to those from measurement data.

Receiver Bandwidth Extension Beyond Nyquist Using Channel Bonding

Current and upcoming communication and sensing technologies require ever larger bandwidths. Channel bonding can be utilized to extend a receiver's instantaneous bandwidth beyond a single converter's Nyquist limit. Two potential joint front-end and converter design approaches are theoretically introduced, realized and evaluated in this paper. The Xilinx RFSoC platform with its 5 GSa/s analog to digital converters (ADCs) is used to implement both a hybrid coupler based in-phase/quadrature (I/Q) sampling and a time-interleaved sampling approach along with channel bonding. Both realizations are demonstrated to be able to reconstruct instantaneous bandwidths of 5 GHz with up to 49 dB image rejection ratio (IRR) typically within 4 to 8 dB the front-ends' theoretical limits.

Measurement Testbed for Radar and Emitter Localization of UAV at 3.75 GHz

This paper presents an experimental measurement platform for the research and development of unmanned aerial vehicles (UAVs) localization algorithms using radio emission and reflectivity. We propose a cost-effective, flexible testbed made from commercial off-the-shelf (COTS) devices to allow academic research regarding the upcoming integration of UAV surveillance in existing mobile radio networks in terms of integrated sensing and communication (ISAC). The system enables nanosecond-level synchronization accuracy and centimeter-level positioning accuracy for multiple distributed sensor nodes and a mobile UAV-mounted node. Results from a real-world measurement in a 16 km2 urban area demonstrate the system's performance with both emitter localization as well as with the radar setup.

Low-Latency Analog-to-Analog Signal Processing using PC Hardware and USRPs

In this paper, we implement a low-latency rapid-prototyping platform for signal processing based on software-defined radios (SDRs) and off-the-shelf PC hardware. This platform allows to evaluate a wide variety of algorithms in real-time environments, supporting new developments in the fields of classical, AI-based, and hybrid signal processing. To accomplish this, the streaming protocol of the used USRP X310 devices is implemented using the Data Plane Development Kit (DPDK), which allows to handle network communication in userspace only. This bypasses the kernel and thus avoids the latencies caused by interrupt handling, scheduling, and context switches. It allows signal processing to be performed on isolated processor cores that are protected from interrupts to a great extent. To validate our approach, linear time-invariant channel emulation has been implemented. For this, an analog-to-analog latency of 31 microseconds was achieved, demonstrating that our PC-based approach enables the implementation of rapid-prototyping systems with low latency.