Cell-Free Massive MIMO-Aided ISAC

The performance of cell-free massive multiple-input multiple-output (MIMO)-aided integrated sensing and communication (ISAC) is investigated. Each transmit access point (AP) sends a superimposed ISAC waveform from which the users are able to decode data, while the reflected echos off a target are used at the receive APs to perform sensing functionalities. Each transmit AP adopts a local conjugate precoder, which is designed based on the locally acquired channel state information (CSI) via user pilots. This approach reduces the implementation complexity as it does not necessitate CSI exchanges. An efficient transmit power optimization is also proposed to construct the superimposed ISAC waveform. The performance is evaluated by deriving the achievable user rates and quantifying the two-dimensional MUltiple SIgnal Classification (MUSIC) spectrum function at the receive APs. Our performance analysis captures practical impairments, including erroneously estimated CSI, spatially correlated Rician fading, and clutter interference. Our analytical and numerical results demonstrate the potential of our proposed cell-free massive MIMO aided ISAC systems.