Integrated Sensing and Communication With mmWave Massive MIMO: A Compressed Sampling Perspective

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) Specifically, provide a compressed sampling (CS) perspective to facilitate processing, which can not only recover the high-dimensional channel state information or/and radar imaging information, but also significantly reduce pilot overhead. First, energy-efficient widely spaced array (WSA) architecture is tailored receiver, enhances angular resolution of at cost ambiguity. Then, frame structure time-varying systems considering different timescales. The waveforms are judiciously designed by taking into account both CS theories hardware constraints induced hybrid beamforming (HBF) architecture. Next, design dedicated dictionary WSA that serves as building block formulating sparse signal recovery problems. orthogonal matching pursuit with support refinement (OMP-SR) algorithm proposed effectively solve problems in existence We estimating Doppler frequencies during payload data transmission guarantee performances. Simulation results demonstrate good performances communications under framework.