Microwave linear analog computers (MiLACs) have recently emerged as a promising solution for future gigantic multiple-input multiple-output (MIMO) systems, enabling beamforming with greatly reduced hardware and computational cost. However, channel estimation for MiLAC-aided systems remains an open problem. Conventional least squares (LS) and minimum mean square error (MMSE) estimation rely on intensive digital computation, which undermines the benefits offered by MiLACs. In this letter, we propose efficient LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems. By designing training precoders and combiners implemented by MiLACs, both LS and MMSE estimation are performed fully in the analog domain, achieving identical performance to their digital counterparts while significantly reducing computational complexity, transmit RF chains, analog-to-digital/digital-to-analog converters (ADCs/DACs) resolution requirements, and peak-to-average power ratio (PAPR). Numerical results verify the effectiveness and advantages of the proposed schemes.

翻译：微波线性模拟计算机（MiLAC）近年来已成为未来超大规模多输入多输出（MIMO）系统的一种有前景的解决方案，能够以大幅降低的硬件和计算成本实现波束成形。然而，MiLAC辅助系统的信道估计仍是一个待解决的问题。传统的最小二乘（LS）和最小均方误差（MMSE）估计依赖于密集的数字计算，这削弱了MiLAC带来的优势。本文提出针对MiLAC辅助MIMO系统的高效LS和MMSE信道估计方案。通过设计由MiLAC实现的训练预编码器和组合器，LS和MMSE估计均在模拟域中完全执行，在保持与数字方案相同性能的同时，显著降低了计算复杂度、发射射频链数量、模数/数模转换器（ADC/DAC）分辨率要求以及峰均功率比（PAPR）。数值结果验证了所提方案的有效性和优越性。