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

delete2025-04-29
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PRE
AI
J
Jiawei Xu
Y
Yi Zheng
D
Dimitrios Stathis
R
Ruijia Wang
R
Ruisi Shen
L
Li‐Rong Zheng
Z
Zhuo Zou
A
Ahmed Hemani
DOI:10.1109/TCAD.2025.3565478delete
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Abstract

Abstract

En 中文
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.
Keywords:
Complex matrix vector multiplication (MVM)
memristor crossbar
mixed-signal behavior circuit model
multiple-input-multiple-output (MIMO)
nonidealities

Journal

I
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IF:
2.9
Papers:
564
Citations:
9.6K

Organization

F
fudan university
Scholars:
11.6W
Papers: 7.7W
Citations: 121
K
KTH Royal Institute of Technology
Scholars:
1.3K
Papers: 777
Citations: 2.6W
U
University of Macau
Scholars:
1.1W
Papers: 1.3W
Citations: 2.0W
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