🤖 AI Summary
This work addresses the challenges of low spectral and spatial resource efficiency, pronounced beam-split effects, and insufficient energy efficiency in terahertz ultra-dense communications. To overcome these limitations, we propose a dynamic frequency–position fluid antenna array architecture that jointly optimizes tunable local oscillators, reconfigurable antenna placement, and near-field beam-split mitigation for the first time. Our approach employs a two-stage beam-split-aware spectrum allocation and beam multiplexing strategy, integrated with a minimum dominating set–based user grouping scheme and a distance-aware antenna selection mechanism. Antenna positions and precoders are co-designed via particle swarm optimization. The proposed scheme achieves 2.3× the sum rate of conventional phase-shifter-based subarray architectures and 95% of that attained by true time-delay architectures, while improving energy efficiency by 2.8×. Among its variants, the fully connected FPFA configuration yields the highest energy efficiency.
📝 Abstract
To support ultra-dense connectivity in terahertz (THz) communications, this paper proposes a dynamic frequency-position-fluid antenna (D-FPFA) architecture. Frequency-tunable local oscillators (LOs) are integrated into the RF chains to access different sub-bands, thereby expanding the total bandwidth of the system and providing frequency-domain diversity. To exploit spatial diversity, the base station employs movable subarrays, and each user is equipped with a movable antenna. We first develop a two-phase beam-split-aware frequency allocation strategy. In the first phase, we divide users into disjoint sub-bands according to their channel correlation coefficients to mitigate the interference. In the second phase, we investigate the wideband near-field beam-split effect for planar arrays and reveal an astigmatism phenomenon, in which the beam at a non-central subcarrier cannot be perfectly refocused at a single spatial point. Then, we establish a beam split multiplexing strategy, where we formulate the user grouping task as a minimum dominating set problem. To maximize the sum rate, we introduce a switch network along with a distance-based antenna selection strategy to account for the near-field channel gain variations, followed by a particle swarm optimization-based algorithm that jointly optimizes the antenna positions and precoders. Numerical results show that, the proposed D-FPFA achieves approximately 2.3 times the sum rate of a conventional phase-shifter (PS)-based array-of-subarrays (AoSA) architecture. It also attains 95% of the sum rate of its TTD counterpart while providing approximately 2.8 times its energy efficiency (EE). Moreover, the fully connected variant of D-FPFA, i.e., FPFA, achieves the highest EE among all considered architectures.