MIMO Systems Aided by Microwave Linear Analog Computers: Capacity-Achieving Architectures with Reduced Circuit Complexity
Matteo Nerini, Bruno Clerckx

TL;DR
This paper introduces a graph-theoretic approach to design low-complexity, capacity-achieving microwave linear analog computers for scalable massive MIMO systems, significantly reducing circuit complexity.
Contribution
It proposes stem-connected MiLAC architectures with linear complexity scaling and provides a closed-form capacity-achieving optimization solution.
Findings
Stem-connected MiLACs maintain capacity while reducing complexity.
Circuit complexity scales linearly with the number of antennas.
Numerical simulations confirm theoretical capacity achievement.
Abstract
To meet the demands of future wireless networks, antenna arrays must scale from massive multiple-input multiple-output (MIMO) to gigantic MIMO, involving even larger numbers of antennas. To address the hardware and computational cost of gigantic MIMO, several strategies are available that shift processing from the digital to the analog domain. Among them, microwave linear analog computers (MiLACs) offer a compelling solution by enabling fully analog beamforming through reconfigurable microwave networks. Prior work has focused on fully-connected MiLACs, whose ports are all interconnected to each other via tunable impedance components. Although such MiLACs are capacity-achieving, their circuit complexity, given by the number of required impedance components, scales quadratically with the number of antennas, limiting their practicality. To solve this issue, in this paper, we propose a…
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