User Selection in Near-Field Gigantic MIMO Systems with Modular Arrays

Modular Arrays (MAs) are a promising architecture to enable multi-user communications in next-generation multiple-input multiple-output (MIMO) systems based on extra-large (XL) or gigantic MIMO (gMIMO) deployments, trading off an improved spatial resolution with characteristic interference patterns associated to grating lobes. In this work, we analyze whether MAs can outperform conventional collocated deployments, in terms of achievable sum-rate and served users in a multi-user downlink set-up. First, we provide a rigorous analytical characterization of the inter-user interference for modular gMIMO systems operating in the near field. Then, we leverage these results to optimize the user selection and precoding mechanisms, designing two algorithms that largely outperform existing alternatives in the literature, with different algorithmic complexities. Results show that the proposed algorithms yield over 70% improvements in achievable sum-spectral efficiencies compared to the state of the art. We also illustrate how MAs allow to serve a larger number of users thanks to their improved spatial resolution, compared to the collocated counterpart.