Waveform Design for Communication-Assisted Sensing in 6G Perceptive Networks

TL;DR

This paper introduces a waveform design framework for communication-assisted sensing in 6G networks, optimizing sensing quality through novel transmission schemes and demonstrating significant performance improvements.

Contribution

It proposes a dual-functional waveform design for CAS in 6G networks, addressing the gap in sensing-assisted communication research and optimizing sensing QoS under practical constraints.

Findings

Dual-functional waveform scheme outperforms separated design by ~25%

Power allocation and water-filling schemes reveal key trade-offs

Numerical results validate the effectiveness of the proposed algorithms

Abstract

The integrated sensing and communication (ISAC) technique has the potential to achieve coordination gain by exploiting the mutual assistance between sensing and communication (S&C) functions. While the sensing-assisted communications (SAC) technology has been extensively studied for high-mobility scenarios, the communication-assisted sensing (CAS) counterpart remains widely unexplored. This paper presents a waveform design framework for CAS in 6G perceptive networks, aiming to attain an optimal sensing quality of service (QoS) at the user after the target's parameters successively ``pass-through'' the S$\&$C channels. In particular, a pair of transmission schemes, namely, separated S&C and dual-functional waveform designs, are proposed to optimize the sensing QoS under the constraints of the rate-distortion and power budget. The first scheme reveals a power allocation trade-off, while the latter presents a water-filling trade-off. Numerical results demonstrate the effectiveness of the proposed algorithms, where the dual-functional scheme exhibits approximately 25% performance gain compared to its separated waveform design counterpart.