发表机构
King’s College London; CNRS and CentraleSupélec, Institute of Electronics and Digital Technologies (IETR)（伦敦国王学院; 法国国家科学研究中心与中央理工-高等电力学院，电子与数字技术研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文研究SLM、TLM、HDM三种MiLAC架构的能效，构建能效最大化问题并提出高效求解算法，发现其在有限天线体制下能效优于传统波束形成架构。
AI 中文摘要
微波线性模拟计算机（MiLAC）凭借可调阻抗网络将信号处理从数字域转移到模拟域，已成为实现高能效无线通信的有前景架构。近期已提出多种MiLAC架构，包括单层MiLAC（SLM）、双层MiLAC（TLM）以及混合数字-MiLAC（HDM）。本文研究这些架构的能效（EE），具体针对SLM、TLM和HDM架构，在发射功率、用户速率及架构特定约束下，构建能效最大化问题，并开发结合 successive convex approximation（SCA）的降维技术算法，以高效求解所得非凸问题。我们进一步推导了一种计算高效的能效最大化解决方案，仅需对（K+1）个闭式候选解进行搜索（K为用户数），并在量化噪声可忽略的大规模天线体制下分析渐近能效。分析表明，SLM、TLM和HDM架构的能效缩放规律为ln(N)/N²，而传统数字波束形成（DBF）的缩放规律为ln(N)/N（N为发射天线数）。尽管缩放规律不同，但基于MiLAC的架构能效更快衰减仅在天线尺寸极大（通常涉及数千根天线）时才显现，在实际相关的有限天线体制下仍保持更优能效。最后，我们推导了各架构达到最大能效所需天线数的近似值及对应能效。仿真结果显示，在实际相关的天线体制下，基于MiLAC的架构比传统全数字及混合数模波束形成实现显著更高的能效。
英文摘要
Microwave linear analog computers (MiLACs) have emerged as a promising architecture for energy-efficient wireless communications by shifting signal processing from the digital to the analog domain using tunable impedance networks. Several MiLAC architectures have recently been proposed, including the single-layer MiLAC (SLM), two-layer MiLAC (TLM), and hybrid digital-MiLAC (HDM). In this paper, we investigate the energy efficiency (EE) of these architectures. Specifically, we formulate EE maximization problems for the SLM, TLM, and HDM architectures under transmit power, user rate, and architecture-specific constraints, and develop a dimensionality reduction technique with successive convex approximation (SCA)-based algorithms to efficiently solve the resulting non-convex problems. We further derive a computationally efficient solution for EE maximization based on a search over only $(K+1)$ closed-form candidate solutions, where $K$ is the number of users, and analyze the asymptotic EE in the large-antenna regime under negligible quantization noise. Our analysis shows that the EE of the SLM, TLM, and HDM architectures scales as $\ln(N)/N^2$, whereas conventional digital beamforming (DBF) scales as $\ln(N)/N$, where $N$ denotes the number of transmit antennas. Despite these different scaling laws, the faster EE decay of MiLAC-based architectures becomes relevant only at very large antenna dimensions, typically involving thousands of antennas, while they maintain superior EE over practically relevant finite antenna regimes. Finally, we derive an approximation of the number of antennas required to achieve the maximum EE for each architecture and the corresponding EE. Simulation results show that, over practically relevant antenna regimes, MiLAC-based architectures achieve substantially higher EE than conventional fully digital and hybrid analog-digital beamforming.
CommentsSubmitted to the IEEE for possible publication
