Per-User Dynamic Controllable Waveform Design for Dual Function Radar- Communication System
Dongxu An, Jun Liu, Kai Zhong, Jinfeng Hu, Haoran Yao, Huiyong Li, Fulvio Gini
Abstract
The waveform design with constant-modulus (CM) constraint is a key issue in the dual function radar-communication (DFRC) systems. Usually, existing methods optimize DFRC waveform by considering radar signal to interference plus noise ratio (SINR) and communication multiuser interference (MUI). We have noticed that existing methods ignore MUI in the time or per-user dimension, resulting in dynamically uncontrollable communication quality-of-service (QoS). To this end, a per-user dynamically controllable waveform design is proposed. We jointly design waveforms and filters to enhance radar detection under the per-user dynamic controllable communication QoS constraint. The problem is nonconvex and NP-hard due to the CM constraint and waveform-filter coupling. Existing methods tackle it via relaxation and matrix inversion, leading to degraded performance and computational complexity. We observe that the problem is separable in time and user dimensions, and therefore propose a stacked-product Riemannian manifold (S-PRM) space to satisfy CM and per-user dynamic controllable communication QoS constraint. Then, we propose a stacked-product Riemannian manifold penalty (S-PRMP) method without relaxation and matrix inversion. Compared to existing works, the proposed method offers the following contributions: 1) computational burden reduction by over $80 \%$ while improving radar SINR by 0.83 dB and reducing MUI by one order of magnitude; 2) more reliable per-user dynamically controllable communication QoS.