arrow
返回

Toward Software-Based, MIMO, Open-RAN PHY Architectures with Both Linear and Non-Linear Processing

delete2024-08-01
delete0
PRE
AI
K
Konstantinos Nikitopoulos *
G
George N. Katsaros
M
Marcin Filo
C
Chathura Jayawardena
R
Rahim Tafazolli
DOI:10.1109/MCOM.001.2300572delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Multi-user multiple-Input, multiple-Output (MU-MIMO), and massive-MIMO (mMIMO) have been central technologies to the evolution of the latest mobile generations since they promise substantial throughput increase and enhanced connectivity capabilities. Still, the type of signal processing that will unlock the full potential of MU-MIMO developments, has not yet been determined. Existing realizations typically employ linear processing that, despite its practical benefits, can leave capacity and connectivity gains unexploited. On the other hand, traditional non-linear processing solutions (e.g., sphere decoders) promise improved throughput and connectivity capabilities but can be computationally impractical, with exponentially increasing computational complexity, and with their implementability in 5G-NR systems still being unverified. At the same time, emerging new open radio access network (Open-RAN) designs call for physical layer (PHY) processing solutions that are also practical in terms of realization, even when implemented purely on software. In this work, we present a first, purely software-based, Open-RAN compliant, 5G-NR MIMO PHY that operates in real-time and over-the-air, encompassing both linear and non-linear MIMO processing, and achieving support for eight concurrently transmitted MIMO streams at a 10MHz bandwidth with just twelve processing cores. Here, we not only demonstrate that implementing non-linear processing is feasible in software within the stringent real-time latency requirements of 5G-NR, but we also compare it side-by-side in a real-time and over-the-air environment against traditional linear methods. We show that the gains of non-linear processing include substantially enhanced throughput with insignificant computational power overhead, the halving of the base-station antennas without performance degradation, and overloading factors of up to 300 percent.
Keyword:
Degradation
Wireless networks
Open RAN
Signal processing
Throughput
Physical layer
Real-time systems
MIMO

期刊

IEEE Communications Magazine 封面图
IEEE Communications Magazine
IF:
8.2
论文数:
6.9K
被引数:
2.2W

机构

U
University of Surrey
学者数:
1.2W
论文数: 1.3W
被引数: 22
引用论文

引用论文

Guidelines for the Management of Children and Adolescent with COVID-19: protocol for an update
err2021-01-01
err0
errOAAI
errQi Zhou; Weiguo Li; Siya Zhao; Qinyuan Li; Qianling Shi; Zijun Wang; Hui Liu; Xiao Liu; Janne Estill; Zhengxiu Luo; Qiu Li; Kehu Yang; Enmei Liu; Yaolong Chen
err分享
err收藏
An Assessment of Deep Learning Versus Massively Parallel, Non-Linear Methods for Highly-Efficient MIMO Detection
err2023-01-01
err3
errOAAI
errDucoing, J. C. De Luna; Jayawardena, Chathura; Nikitopoulos, Konstantinos
err分享
err收藏
Occurrence and spatial distribution of Toggenburg Orbivirus in Switzerland
err2010-10-01
err0
PREAI
errValérie Chaignat; Heinzpeter Schwermer; Simona Casati; Jeannette Planzer; Gabriella Worwa; Tullio Vanzetti; Carrie Batten; Martin Hofmann; Barbara Thür
err分享
err收藏
err分享
err收藏
Massively Parallel Tree Search for High-Dimensional Sphere Decoders
err2019-10-01
err21
errOAAI
errNikitopoulos, Konstantinos; Georgis, Georgios; Jayawardena, Chathura; Chatzipanagiotis, Daniil; Tafazolli, Rahim
err分享
err收藏
学者 查看更多内容