Frequency-Position-Fluid Antenna Array for Ultra-dense Connectivity in Terahertz Beamforming Systems
<|reference_start|>Frequency-Position-Fluid Antenna Array for Ultra-dense Connectivity in Terahertz Beamforming Systems: The position-fluid antenna (PFA) architecture has become one of the appealing technologies to support ubiquitous connectivity demand in next-generation wireless systems. Specifically, allowing the antenna to adjust its physical position to one of the predefined ports within a fixed region can introduce additional spatial diversity and improve the signal-to-interference-plus-noise ratio (SINR). In addition, frequency diversity is also widely-explored through frequency interleaving in the terahertz (THz) band. However, the operating bandwidth of one antenna is usually limited to 10% of the central frequency, which imposes a waste of the ultra-broad bandwidth in the THz band. In light of this, a frequency-position-fluid antenna (FPFA) system is proposed in this paper to facilitate ultra-dense connectivity. Specifically, antennas with non-overlapping operating frequency ranges are deployed at the base station (BS) to expand the total available bandwidth and provide frequency domain diversity, while the PFA-enabled users are capable of providing the spatial domain diversity. The channel model is first derived, based on which a channel correlation-based frequency allocation strategy is proposed. Then, a minimum-projection-based port selection algorithm is developed with singular-value-decomposition (SVD) precoders. Simulation results show that the proposed FPFA architecture exhibits steady performance with an increasing number of users, and outperforms the PFA and the fixed-antenna system in ultra-dense user deployment.<|reference_end|>
@article{shen2024frequency-position-fluid,
    title={Frequency-Position-Fluid Antenna Array for Ultra-dense Connectivity in
  Terahertz Beamforming Systems},
    author={Heyin Shen, Chong Han, Hao Liu, and Tao Yang},
    journal={arXiv preprint arXiv:2409.00941},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.00941},
    primaryClass={cs.IT eess.SP math.IT}
}