Sphere Precoding for Robust Near-Field Communications

TL;DR

This paper tackles robustness of near-field precoding in massive MIMO under user mobility by introducing a mobility-aware one-sphere channel model and a corresponding sphere precoding strategy. The method derives a covariance-based representation using eigenstructure to shape beams within a target spherical zone while nulling interference in other zones, and solves a relaxed convex problem to maximize the minimum SINR satisfaction probability across mobile users. Key contributions include the one-sphere channel model, the sphere precoding optimization, and a practical operation framework that leverages radar or multi-modal sensing, validated by simulations showing enhanced SINR stability and high data rates. The work enables robust near-field communications with large arrays in dynamic environments, combining mobility resilience with efficient interference management.

Abstract

Near-field communication with large antenna arrays promises significant beamforming and multiplexing gains. These communication links, however, are very sensitive to user mobility as any small change in the user position may suddenly drop the signal power. This leads to critical challenges for the robustness of these near-field communication systems. In this paper, we propose \textit{sphere precoding}, which is a robust precoding design to address user mobility in near-field communications. To gain insights into the spatial correlation of near-field channels, we extend the one-ring channel model to what we call one-sphere channel model and derive the channel covariance considering user mobility. Based on the one-sphere channel model, a robust precoding design problem is defined to optimize the minimum signal-to-interference-plus-noise ratio (SINR) satisfaction probability among mobile users. By utilizing the eigen structure of channel covariance, we further design a relaxed convex problem to approximate the solution of the original non-convex problem. The low-complexity solution effectively shapes a sphere that maintains the signal power for the target user and also nulls its interference within spheres around the other users. Simulation results highlight the efficacy of the proposed solution in achieving robust precoding yet high achievable rates in near-field communication systems.

Figures (4)

• Figure 1: This figure illustrates the considered near-field scenario, where a base station is equipped with an extremely large array to serve mobile users. The precoding design depends on users speed and surrounding scatterers, which provides both beam focusing and interference nulling with robustness.
• Figure 2: Sphere Precoding
• Figure 3: This figure shows a comparison between the beamforming patterns of zero-forcing and sphere precoding. The base station is at the origin, the target user is marked by a red square, and the other (non-target) users are marked by black square. User mobility is assumed to be 0.056 m. In Figure (b), sphere precoding effectively focuses/nullifies beam power around the spherical region of target/non-target users. This leads to more robust communication performance against user mobility.
• Figure 4: The evaluation of the proposed solution. In (a), the average SINR of the proposed solution is compared with the benchmark methods with varying mobility assumption, i.e., moving distance. In (b), the CDF of SINR at the moving distance of $0.139$ m is presented.