A Scalable Massive MIMO Uplink Baseband Processing Generator

被引：2

作者：

Dai, Yue ^{[1
]}

LaCaille, Greg ^{[1
]}

Liew, Harrison ^{[1
]}

Dunn, James ^{[1
]}

Nikolic, Borivoje ^{[1
]}

机构：

[1] Univ Calif Berkeley, Dept EECS, Berkeley, CA 94720 USA

来源：

IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021) | 2021年

关键词：

massive MIMO; generator; beamforming; FPGA-emulation; WIRELESS;

D O I：

10.1109/ICC42927.2021.9500566

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

This paper describes a scalable, highly portable, and power-efficient generator for massive multiple-input multiple-output (MIMO) uplink baseband processing. This generator is written in Chisel, and produces hardware instances for the distributed processing in a scalable massive MIMO system. The generator is parameterized in both the MIMO system and hardware datapath elements. The performance of several generator instances with different parameter values are validated by emulation on a field-programmable gate array (FPGA), demonstrating both functionality and scalability, and operation up to 6.4Gb/s data throughput.

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页数：6

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