Line-of-Sight MIMO Systems: Near-Field Boundaries and Channel Estimation

Distinguishing the near-field and far-field regions in line-of-sight (LoS) multiple-input multiple-output (MIMO) systems is crucial, as their distinct characteristics significantly impact performance and system design. In this paper, we propose a novel criterion for identifying the near-field and far-field regions based on the number of independent spatial streams. We introduce and derive a closed-form expression of effective degree of freedom (EDoF) for LoS MIMO systems by taking into account both the phase differences and path attenuation. Then, the spatial multiplexing distance (SMD) and resolvable distance (RD) are derived to define the boundary of the near field. Based on these boundaries, we propose a hybrid search-gradient descent (HSGD) algorithm to estimate the near-field channel information, which combines a coarse search through non-uniform step sizes with a precise estimation based on the gradient descent. Our numerical results unveil that i) the EDoF can be accurately calculated using the closed-form expression, ii) the HSGD algorithm achieves at least 28.72% improvement over the polar-domain simultaneous iterative gridless weighted (PSIGW) algorithm and 22.91% improvement over the orthogonal matching pursuit (OMP) algorithm across the different signal-to-noise ratio (SNR), and iii) the HSGD algorithm achieves at least 95.84% improvement over the PSIGW algorithm and 79.83% improvement over the OMP algorithm across varying communication distances.