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The performance of integrated sensing and communications (ISAC) empowered intelligent reflecting surface (IRS)aided massive multiple-input multiple-output (MIMO) systems operating over spatially correlated Rician fading is investigated. Computationally-efficient linear precoders are used to construct the ISAC signal by invoking the maximal ratio transmission (MRT) criterion into the composite channels containing both direct and IRS reflected channels. The uplink communication channels are estimated based on the linear minimum mean square error criterion and used to construct user precoders. The IRS phase-shifts are optimized based on the statistical channel knowledge to maximize the minimum average power gains of the composite communication channels subject to an average power threshold for the reflected sensing channel. The communication performance is evaluated by deriving the achievable user rates, while the sensing performance is studies by locating the target via the 2D MUltiple SIgnal Classification (MUSIC) algorithm. Our numerical results are used to study the trade-off between the communication and sensing performance metrics in IRS-aided massive MIMO systems with MRT-based linear precoders. 

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.