标题： 网络辅助全双工系统的性能分析与优化在低分辨率ADC下 显示英文标题

标题： Performance Analysis and Optimization of Network-Assisted Full-Duplex Systems under Low-Resolution ADCs

摘要： 网络辅助全双工（NAFD）分布式大规模多输入多输出（M-MIMO）在网路层实现了与现有半双工设备的带内全双工，从而显著提高了频谱效率。 本文分析了低分辨率模数转换器（ADCs）对NAFD分布式M-MIMO的影响，并为低分辨率ADCs设计了一种高效的比特分配算法。 波束成形训练机制减轻了信道估计的大量导频开销，通过引导干扰消除和相干检测显著提升了系统性能。 此外，推导出了具有低分辨率ADCs的频谱和能量效率的显式表达式。 通过深度Q网络和非支配排序遗传算法II解决了频谱和能量效率的多目标优化问题（MOOP）。 仿真结果验证了理论推导，并证实了在NAFD分布式M-MIMO系统中引入低分辨率ADCs的有效性。 同时，一组帕累托最优解为ADC精度提供了灵活的指导，有助于在实际的NAFD分布式M-MIMO系统中部署。 显示英文摘要

摘要： Network-assisted full-duplex (NAFD) distributed massive multiple input multiple output (M-MIMO) enables the in-band full-duplex with existing half-duplex devices at the network level, which exceptionally improves spectral efficiency. This paper analyzes the impact of low-resolution analog-to-digital converters (ADCs) on NAFD distributed M-MIMO and designs an efficient bit allocation algorithm for low-resolution ADCs. The beamforming training mechanism relieves the heavy pilot overhead for channel estimation, which remarkably enhances system performance by guiding the interference cancellation and coherence detection. Furthermore, closed-form expressions for spectral and energy efficiency with low-resolution ADCs are derived. The multi-objective optimization problem (MOOP) for spectral and energy efficiency is solved by the deep Q network and the non-dominated sorting genetic algorithm II. The simulation results corroborate the theoretical derivation and verify the effectiveness of introducing low-resolution ADCs in NAFD distributed M-MIMO systems. Meanwhile, a set of Pareto-optimal solutions for ADC accuracy flexibly provide guidelines for deploying in a practical NAFD distributed M-MIMO system.