论文标题
低分辨率ADC下的网络辅助全双工系统的性能分析和优化
Performance Analysis and Optimization of Network-Assisted Full-Duplex Systems under Low-Resolution ADCs
论文作者
论文摘要
网络辅助全双工（NAFD）分布式大量多重输入多重输出（M-MIMO）可以在网络级别具有现有半双链设备的带内全双工，从而极大地提高了光谱效率。本文分析了低分辨率类似于数字转换器（ADC）对NAFD分布式M-MIMO的影响，并为低分辨率ADC设计了有效的位分配算法。波束形成的训练机制可缓解沉重的飞行员开销，以供通道估计，从而通过引导干扰取消和相干检测来显着提高系统性能。此外，得出了低分辨率ADC的光谱和能源效率的封闭形式表达式。用于光谱和能源效率的多目标优化问题（MOOP）通过深Q网络和非主导的排序遗传算法II解决。模拟结果证实了理论推导并验证在NAFD分布式M-MIMO系统中引入低分辨率ADC的有效性。同时，一组用于ADC准确性的帕累托最佳解决方案灵活地提供了在实用的NAFD分布式M-MIMO系统中部署的准则。
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.
