Carrier Aggregation Enabled Integrated Sensing and Communication Signal Design and Processing

TL;DR

This paper introduces a carrier aggregation-based ISAC signal design that combines high and low-frequency bands to enhance sensing accuracy, employing compressed sensing techniques and deriving bounds to validate performance improvements.

Contribution

It proposes a novel CA-based ISAC signal structure with multiple pilot configurations and an FISTA-based processing algorithm to improve sensing performance in spectrum-fragmented environments.

Findings

CA improves range and velocity estimation accuracy

The proposed algorithm effectively reconstructs sensing signals

CRLBs validate the theoretical performance bounds

Abstract

The future mobile communication systems will support intelligent applications such as Internet of Vehicles (IoV) and Extended Reality (XR). Integrated Sensing and Communication (ISAC) is regarded as one of the key technologies satisfying the high data rate communication and highly accurate sensing for these intelligent applications in future mobile communication systems. With the explosive growth of wireless devices and services, the shortage of spectrum resources leads to the fragmentation of available frequency bands for ISAC systems, which degrades sensing performance. Facing the above challenges, this paper proposes a Carrier Aggregation (CA)-based ISAC signal aggregating high and low-frequency bands to improve the sensing performance, where the CA-based ISAC signal can use four different aggregated pilot structures for sensing. Then, an ISAC signal processing algorithm with Compressed Sensing (CS) is proposed and the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) is used to solve the reconfiguration convex optimization problem. Finally, the Cram'er-Rao Lower Bounds (CRLBs) are derived for the CA-based ISAC signal. Simulation results show that CA efficiently improves the accuracy of range and velocity estimation.