Analog-domain operations offer a promising solution to accelerating signal processing and enabling future multiple-input multiple-output (MIMO) communications with thousands of antennas. In Part I of this paper, we have introduced a microwave linear analog computer (MiLAC) as an analog computer that processes microwave signals linearly, demonstrating its potential to reduce the computational complexity of specific signal processing tasks. In Part II of this paper, we extend these benefits to wireless communications, showcasing how MiLAC enables gigantic MIMO beamforming entirely in the analog domain. MiLAC-aided beamforming enables the maximum flexibility and performance of digital beamforming, while significantly reducing hardware costs by minimizing the number of radio-frequency (RF) chains and only relying on low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs). In addition, it eliminates per-symbol operations by completely avoiding digital-domain processing and remarkably reduces the computational complexity of zero-forcing (ZF), which scales quadratically with the number of antennas instead of cubically. It also processes signals with fixed matrices, e.g., the discrete Fourier transform (DFT), directly in the analog domain. Numerical results show that it can perform ZF and DFT with a computational complexity reduction of up to $1.5\times 10^4$ and $4.0\times 10^7$ times, respectively, compared to digital beamforming.

翻译：模拟域操作为加速信号处理及实现未来具有数千天线的多输入多输出（MIMO）通信提供了一种前景广阔的解决方案。在本文第一部分中，我们介绍了微波线性模拟计算机（MiLAC）作为一种线性处理微波信号的模拟计算设备，展示了其在降低特定信号处理任务计算复杂度方面的潜力。在第二部分中，我们将这些优势延伸至无线通信领域，阐明MiLAC如何实现完全在模拟域进行的超大规模MIMO波束成形。MiLAC辅助波束成形既能实现数字波束成形的最大灵活性与性能，又通过最小化射频（RF）链路数量并仅依赖低分辨率模数转换器（ADC）和数模转换器（DAC），显著降低了硬件成本。此外，该方法通过完全避免数字域处理消除了逐符号操作，并大幅降低了迫零（ZF）算法的计算复杂度——其复杂度随天线数量呈二次方而非三次方增长。该系统还能在模拟域直接处理固定矩阵（例如离散傅里叶变换（DFT）矩阵）的信号。数值结果表明，与数字波束成形相比，该系统执行ZF和DFT的计算复杂度分别降低达$1.5\\times 10^4$倍和$4.0\\times 10^7$倍。