Integrated sensing and communication (ISAC) is emerging as a critical technology for 5G and beyond wireless networks. Despite the apparent advantages, real-world applications constantly present performance and energy optimization issues. This paper presents a novel method combining low-resolution analog-to-digital converters (L-ADCs) with optimal beamforming strategies for a free-cellular MIMO ISAC system to tackle the energy saving challenge. The proposed system adopts the additive quantization noise model (AQNM) and thereafter examines four different beamforming scenarios based on sensing and/or communication priority schemes. Numerical simulations indicate that the conjugate beamforming (CB) method outperforms the null space beamforming (NS) method across all power allocation ratios and ADC configurations, particularly at low communication power allocation. The large quantity of antennas enhances spatial capacity and mitigates the performance decrease associated with low-resolution ADCs, enabling the system to maintain efficiency while achieving energy conservation advantages. This research addresses the research gap in optimizing non-cellular ISAC MIMO systems with low-resolution ADCs, opening the way for energy-efficient applications.

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Optimizing Beamforming for Cell-Free MIMO ISAC Systems with Low-Resolution ADCs

  • Van Kien Bui,
  • Hieu T. Nguyen,
  • Tuan Anh Nguyen,
  • Trong Minh Hoang,
  • Anh Thu Pham

摘要

Integrated sensing and communication (ISAC) is emerging as a critical technology for 5G and beyond wireless networks. Despite the apparent advantages, real-world applications constantly present performance and energy optimization issues. This paper presents a novel method combining low-resolution analog-to-digital converters (L-ADCs) with optimal beamforming strategies for a free-cellular MIMO ISAC system to tackle the energy saving challenge. The proposed system adopts the additive quantization noise model (AQNM) and thereafter examines four different beamforming scenarios based on sensing and/or communication priority schemes. Numerical simulations indicate that the conjugate beamforming (CB) method outperforms the null space beamforming (NS) method across all power allocation ratios and ADC configurations, particularly at low communication power allocation. The large quantity of antennas enhances spatial capacity and mitigates the performance decrease associated with low-resolution ADCs, enabling the system to maintain efficiency while achieving energy conservation advantages. This research addresses the research gap in optimizing non-cellular ISAC MIMO systems with low-resolution ADCs, opening the way for energy-efficient applications.