Integrated sensing and communication (ISAC) has opened up numerous game-changing opportunities for realizing future wireless systems. In this paper, we propose an ISAC processing framework relying on millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Specifically, we provide a compressed sampling (CS) perspective to facilitate ISAC processing, which can not only recover the large-scale channel state information or/and radar imaging information, but also significantly reduce pilot overhead. First, an energy-efficient widely spaced array (WSA) architecture is tailored for the radar receiver, which enhances the angular resolution of radar sensing at the cost of angular ambiguity. Then, we propose an ISAC frame structure for time-variant ISAC systems considering different timescales. The pilot waveforms are judiciously designed by taking into account both CS theories and hardware constraints. Next, we design the dedicated dictionary for WSA that serves as a building block for formulating the ISAC processing as sparse signal recovery problems. The orthogonal matching pursuit with support refinement (OMP-SR) algorithm is proposed to effectively solve the problems in the existence of the angular ambiguity. We also provide a framework for estimating and compensating the Doppler frequencies during payload data transmission to guarantee communication performances. Simulation results demonstrate the good performances of both communications and radar sensing under the proposed ISAC framework.
翻译:综合遥感和通信(ISAC)为未来无线系统开辟了许多改变游戏的机会。在本文件中,我们提议建立一个依靠毫米波(mmWave)大规模多投入多产出(MIMO)系统的ISAC处理框架。具体地说,我们提供一个压缩取样(CS)视角,以便利ISAC处理,不仅能够恢复大型频道国家信息或/和雷达成像信息,而且能够大大减少试点间接费用。首先,为雷达接收器专门设计一个节能广空阵列结构,它能以角模糊的代价增强雷达遥感的角分辨率。然后,我们提出一个ISAC框架结构,用于考虑不同时间尺度的时间变化性ISAC系统。试点波形设计明智地考虑到CS理论和硬件限制。我们为ISA设计了专门的词典,作为将ISAC处理发展成微小信号恢复问题的一个构件。我们提议对雷达接收和辅助改进的“OMP-SR”算法进行骨质匹配,以有效解决存在时间变异式ISAC系统的问题,同时考虑不同的时间尺度。我们还在SISADRDRA中提出一个最佳性表现框架。