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NetMod: Toward Accelerating Cloud RAN Distributed Unit Modulation Within Programmable Switches

delete2025-02-01
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PRE
AI
A
Abdulbary Naji
X
Xingfu Wang
A
Ammar Hawbani *
A
Aiman Ghannami
L
Liang Zhao
X
Xiaohua Xu *
W
Wei Zhao
DOI:10.1109/TC.2024.3500379delete
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Abstract

Abstract

En 中文
Radio Access Networks (RAN) are anticipated to gradually transition towards Cloud RAN (C-RAN), leveraging the full advantages of the cloud-native computing model. While this paradigm shift offers a promising architectural evolution to improve scalability, efficiency, and performance, significant challenges remain in managing the massive computing requirements of physical layer (PHY) processing. To address these challenges and meet the stringent Service Level Objectives (SLOs) in 5G networks, hardware acceleration technologies are essential. In this paper, we aim to mitigate this challenge by offloading 5G modulation mapping, a critical yet demanding function to encode bits into IQ symbols, directly onto the switch ASICs. Specifically, we introduce NetMod, a 5G New Radio (NR) standard-compliant in-network modulation mapper accelerator. NetMod leverages the capabilities of new-generation programmable switches within the C-RAN infrastructure to offload and accelerate PHY modulation functions. We implemented a NetMod prototype on a real-world platform using the Intel Tofino programmable switch and commodity servers running the Data Plane Development Kit (DPDK). Through extensive experiments, we demonstrate that NetMod achieves modulation mapping at switch line rate using minimal switch resources, thereby preserving ample space for traditional switching tasks. Furthermore, comparisons with a GPU-based 5G modulation mapper show that NetMod is 2.2x to 3.3x faster using only a single switch port. These results highlight the potential of in-network acceleration to enhance 5G network performance and efficiency.
Keywords:
Modulation
Symbols
5G mobile communication
Servers
Protocols
Payloads
Hardware acceleration
Throughput
Open RAN
Computers
Hardware accelerators
cloud RAN
in-network computing
DPDK
data plane programming
P4
5G NR
O-RAN
modulation

Journal

IEEE Transactions on Computers cover
IEEE Transactions on Computers
IF:
3.8
Papers:
5.4K
Citations:
9.8K

Organization

U
university of science & technology of china, cas
Scholars:
3.2W
Papers: 2.7W
Citations: 74
S
Shenyang Aerospace University
Scholars:
3.1K
Papers: 1.9K
Citations: 2.0K
E
Eindhoven University of Technology
Scholars:
1.6W
Papers: 1.5W
Citations: 2.2W
C
chinese academy of sciences
Scholars:
56.7W
Papers: 45.0W
Citations: 704
researcher View more organizations
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