Hybrid Beamfocusing Design for RSMA-Enabled Near-Field Wideband Communications

TL;DR

This paper introduces a novel RSMA-enabled hybrid beamfocusing scheme for wideband near-field communications using true-time-delay architectures, effectively mitigating spatial wideband effects and reducing hardware complexity.

Contribution

It proposes a joint optimization framework and a penalty-based iterative algorithm for hybrid beamfocusing in wideband near-field RSMA systems, extending to sub-connected architectures.

Findings

Effectively compensates for spatial wideband effects.

Achieves performance comparable to full digital beamfocusing.

Provides substantial gains over benchmark schemes.

Abstract

Future wireless networks will utilize extremely large-scale antenna arrays (ELAAs) over high-frequency bands, which, however, produce near-field spherical wavefronts and spatial wideband effects. To exploit and mitigate these, this paper proposes a rate-splitting multiple access (RSMA)-enabled transmit scheme for wideband near-field communications (NFC). Our solution leverages true-time-delay (TTD)-based hybrid beamfocusing architectures to mitigate spatial wideband effect and reduce radio frequency chain requirements. The objective is to maximize the minimum rate by jointly optimizing frequency-dependent analog beamfocusing, frequency-independent analog beamfocusing, digital beamfocusing, and common rate allocation. To solve this complicated non-convex problem, we develop a penalty-based iterative algorithm that partitions the variables into three blocks and then employs block coordinate descent (BCD) to optimize each block alternately. This algorithm is further extended to support the sub-connected TTD-based analog beamfocusing architectures. Comprehensive simulation results indicate that our transmit scheme: 1) effectively compensates for spatial wideband effect, addressing a critical challenge in wideband operation; 2) achieves performance comparable to full digital beamfocusing while maintaining lower hardware complexity; 3) achieves substantial performance gains over the other two benchmarks.