Abstract
Integrated sensing and communications (ISAC) is a key enabling technology for 6G, leveraging shared resources to combine communication and radar-like sensing capabilities. In the near-field (NF) region, where spherical wavefronts dominate, higher precision sensing and more efficient communication can be achieved. This paper presents a comprehensive performance analysis and estimator design for NF wideband ISAC systems based on colocated multiple-input multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) architectures. Addressing the unique challenges of NF scenarios, we propose a reduced-complexity sensing algorithm to jointly estimate the 3D position and radial velocity of targets. Closed-form expressions for the Fisher Information Matrix (FIM) and Cramér-Rao lower bound (CRLB) are derived to establish fundamental performance benchmarks. Additionally, a model mismatch analysis based on the Misspecified Cramér-Rao lower bound (MCRLB) is performed to assess the impact of using simplified far-field (FF) models instead of the true NF model. To further enhance ISAC performance, a communication-sensing trade-off precoding optimization problem is formulated, incorporating metrics for sum-rate communication and 2D beam similarity and cross-correlation for sensing. Simulation results validate the theoretical findings, showcasing the potential of NF ISAC systems for achieving accurate target localization and efficient communication in 6G networks.