论文标题
双功能雷达通信系统由智能反射表面提供帮助
Dual-Function Radar-Communication System Aided by Intelligent Reflecting Surfaces
论文作者
论文摘要
我们提出了一个在智能反射表面（IRS）帮助的双功能雷达通信（DFRC）系统的新型设计。我们考虑一个具有一个目标和多个通信接收器的方案，其中雷达和目标之间没有视线。雷达预编码矩阵和IRS权重的最佳设计是为了最大程度地提高雷达接收器的信噪比（SNR）的加权总和，而通信接收器处的SNR受到了IRS权重的功率约束和恒定模量约束。该问题被解耦到两个子问题，即波形设计和IRS重量设计，并通过交替优化解决。以前的子问题是通过线性编程解决的，而后者则通过具有四分之一的多项式物镜通过歧管优化解决。本文的关键贡献在于解决IRS权重设计子问题，该问题基于IRS权重中四分之一的目标函数的优化，并受到IRS权重的单位模量构成。提供了仿真结果，以显示在不同系统配置下所提出的算法的收敛行为，以及使用IRS改善雷达和通信性能的有效性。
We propose a novel design of a dual-function radar communication (DFRC) system aided by an Intelligent Reflecting Surface (IRS). We consider a scenario with one target and multiple communication receivers, where there is no line-of-sight between the radar and the target. The radar precoding matrix and the IRS weights are optimally designed to maximize the weighted sum of the signal-to-noise ratio (SNR) at the radar receiver and the SNR at the communication receivers subject to power constraints and constant modulus constraints on the IRS weights. The problem is decoupled into two sub-problems, namely, waveform design and IRS weight design, and is solved via alternating optimization. The former subproblem is solved via linear programming, and the latter via manifold optimization with a quartic polynomial objective. The key contribution of this paper lies in solving the IRS weight design sub-problem that is based on the optimization of a quartic objective function in the IRS weights, and is subject to unit modulus-constraint on the IRS weights. Simulation results are provided to show the convergence behavior of the proposed algorithm under different system configurations, and the effectiveness of using IRS to improve radar and communication performance.
