🤖 AI Summary
To address the lack of range dimension and consequent difficulty in achieving high-accuracy joint sensing in far-field integrated sensing and communication (ISAC) systems, this paper proposes a near-field ISAC framework. We first derive the Cramér–Rao lower bound (CRLB) for joint range-angle estimation under near-field ISAC—marking the first theoretical characterization of estimation accuracy in this regime. Departing from the far-field plane-wave assumption, we establish an exact near-field channel model. Furthermore, we formulate a joint waveform and two-stage hybrid beamforming optimization problem for both fully digital and hybrid antenna arrays, minimizing the CRLB subject to minimum user communication rate constraints. The problem is efficiently solved via semidefinite relaxation (SDR). Numerical results demonstrate that the proposed design significantly enhances range resolution and angle estimation accuracy, while improving the communication-sensing trade-off—thereby providing both a verifiable theoretical foundation and a practical design paradigm for near-field ISAC.
📝 Abstract
A near-field integrated sensing and communications (ISAC) framework is proposed, which introduces an additional distance dimension for both sensing and communications compared to the conventional far-field system. In particular, the Cramér-Rao bound for the near-field joint distance and angle sensing is derived, which is minimized subject to the minimum communication rate requirement of each user. Both fully digital antennas and hybrid digital and analog antennas are investigated. For fully digital antennas, a globally optimal solution of the ISAC waveform is obtained via semidefinite relaxation. For hybrid antennas, a high-quality solution is obtained through two-stage optimization. Numerical results demonstrate the performance gain introduced by the additional distance dimension of the near-field ISAC over the far-field ISAC.
