Hybrid Physical and Virtual Array Based OFDM-ISAC with Sparse MIMO for Dense Users and Targets

In this paper, we investigate orthogonal frequency division multiplexing (OFDM)-integrated sensing and communication (ISAC) based on sparse multi-input multi-output (MIMO), where the conventional compact uniform linear array (ULA) is deployed at the transmitter while sparse ULA is deployed at the receiver. To enhance both sensing degrees of freedom (DoFs) and communication spectral efficiency, we propose the novel framework of hybrid array processing for ISAC, namely virtual array based sensing and physical array based communication. Specifically, we first develop an effective sensing approach based on the virtual array technology by applying sum or sum-difference co-array of sparse MIMO. We show that with the inter-antenna spacing of receive sparse ULA being same or about twice as the aperture size of the transmit compact ULA, hole-free virtual array can be formed for sensing improvement. Then, the ISAC beamforming is performed for communication precoding and its corresponding null-space matrix for radar precoding, which improves communication spectral efficiency while maintaining sensing DoFs. Extensive simulation results are provided to verify the superiority of sparse MIMO for ISAC as compared with the benchmarking compact MIMO, especially for densely-located users and targets.