MemMIMO: A Simulation Framework for Memristor-Based Massive MIMO Acceleration

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Jiawei Xu, Yi Zheng, Dimitrios Stathis, Ruijia Wang, Ruisi Shen, Lirong Zheng, Zhuo Zou, Ahmed Hemani

Published: 2025, Last Modified: 26 Jan 2026IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Memristor-based crossbar architectures have proven highly effective for matrix vector multiplication (MVM) operations, making them a promising solution for accelerating the MVMs widely used in precoding algorithms for multiple-input-multiple-output (MIMO) wireless communication systems. However, real-world implementation of memristor-based computing systems face challenges due to common nonidealities in both the devices and the peripheral circuits. To facilitate a rapid design flow and investigate the impact of nonidealities, an integrated open-source simulation framework MemMIMO is developed. The simulation framework estimates the accuracy and hardware performance of the computing system, offering a variety of flexible design options. MemMIMO integrates a behavioral model of the mix-signal architecture with a digital front-end. There are three major building blocks in MemMIMO: 1) the device fitting block; 2) the mapping block; and 3) the performance estimation block. These blocks work together to map the complex MVMs in precoding algorithms for MIMO systems to crossbar-based architectures that incorporate memristor models characterized by physical device behavior. Using two typical use cases targeting six-generation (6G) massive MIMO communication as case studies, MemMIMO is used to model different memristor devices, explore the impact of nonidealities on system accuracy, and benchmark circuit-level performance metrics, including area, speed, and power.