GPU Accelerated High Capacity, AI-Ready 5G/6G Reference Design and Verification Methodology

The demands from wireless connectivity continue to grow, placing greater emphasis in designing efficient wireless networks and even greater emphasis on end-to-end (E2E) system verification. Next generation Telecom networks need to enable the proliferation of artificial intelligence (AI) in wireless communications, in addition to expanding traditional road map items (such as throughput, latency, user capacity, etc.). We provide a 5G network architecture reference design and present a methodology to evaluate and validate the 5G stand-alone (SA) network. The methodology consists of three levels. First is the O-RAN fronthaul (FH) connection (called eCPRI), providing the ability to validate FH protocol functionality, server utilization, cell throughput, user capacity, and so on. The second level is called RF Cabled and includes the impact of an O-RAN radio unit (O-RU) in an RF-controlled environment to evaluate performance. Lastly, over-the-air (OTA) is presented to introduce commercially available user equipment and mobility, as well as to experience real-world testing. We show how each level is used to include application-level testing to confirm the end-user experience.

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Publication Details

Journal
IEEE Wireless Communications
Published
2025-06-02
DOI
https://doi.org/10.1109/mwc.004.2500023
Citations
1
Primary Topic
Telecommunications and Broadcasting Technologies
Type
article
Field-Weighted Citation Impact
1.14
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article

GPU Accelerated High Capacity, AI-Ready 5G/6G Reference Design and Verification Methodology

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1 citations
IEEE Wireless Communications
Telecommunications and Broadcasting Technologies
1.14
article

GPU Accelerated High Capacity, AI-Ready 5G/6G Reference Design and Verification Methodology

P. Marini, M. Adamczyk, S.S. Lin, Nicholas Hedberg, Qian Wang, Joseph Boccuzzi, Sonali Sarpotdar, Rohan Chavan, Ravi Lekhwani, Michael Hoang, Sashidhar Samala
article en
1 citations

Abstract

The demands from wireless connectivity continue to grow, placing greater emphasis in designing efficient wireless networks and even greater emphasis on end-to-end (E2E) system verification. Next generation Telecom networks need to enable the proliferation of artificial intelligence (AI) in wireless communications, in addition to expanding traditional road map items (such as throughput, latency, user capacity, etc.). We provide a 5G network architecture reference design and present a methodology to evaluate and validate the 5G stand-alone (SA) network. The methodology consists of three levels. First is the O-RAN fronthaul (FH) connection (called eCPRI), providing the ability to validate FH protocol functionality, server utilization, cell throughput, user capacity, and so on. The second level is called RF Cabled and includes the impact of an O-RAN radio unit (O-RU) in an RF-controlled environment to evaluate performance. Lastly, over-the-air (OTA) is presented to introduce commercially available user equipment and mobility, as well as to experience real-world testing. We show how each level is used to include application-level testing to confirm the end-user experience.

IEEE Wireless CommunicationsVol. 32(6)
Keysight Technologies (United States) (US), Nvidia (United States) (US)
Affordable and clean energy
Openalex Percentile: Top 20%
Telecommunications and Broadcasting Technologies
1.14
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