A GPU accelerated framework for monitoring LTE/5G interference to DVB-T systems

Mangiatordi, Federica; Pallotti, Emiliano

doi:10.23919/aeit53387.2021.9626937

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…WISCANet easily integrates with hardware accelerators like CUDA GPUs, FPGAs, and RFSoCs to accelerate computation-heavy applications. These accelerators have proven extremely useful in enabling a variety of machine learning (ML) and artificial intelligence (AI) techniques [32][33][34][35].…”

Section: Hardware Integrationmentioning

confidence: 99%

WISCANet: A Rapid Development Platform for Beyond 5G and 6G Radio System Prototyping

Holtom

Herschfelt

Lenz

et al. 2022

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Validating RF applications is traditionally time consuming, even for relatively simple systems. We developed the WISCA Software-Defined Radio Network (WISCANet) to accelerate the implementation and validation of radio applications over-the-air (OTA). WISCANet is a hardwareagnostic control software that automatically configures and controls a software-defined radio (SDR) network. By abstracting the hardware controls away from the user, WISCANet allows a non-expert user to deploy an OTA application by simply defining a baseband processing chain in a high level language. This technology reduces transition time between system design and OTA deployment, accelerates debugging and validation processes, and makes OTA experimentation more accessible to users that are not radio hardware experts. WISCANet emulates real-time RF operations, enabling users to perform real-time experiments without the typical restrictions on processing speed and hardware capabilities. WISCANet also supports multiple RF front-ends (RFFEs) per compute node, allowing sub-6 and mmWave systems to coexist on the same node. This coexistence enables simultaneous baseband processing that simplifies and enhances advanced algorithms and beyond-5G applications. In this study, we highlight the capabilities of WISCANet in several sub-6 and mmWave over-the-air demonstrations. The open source release of this software may be found on the WISCA GitHub page.

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Section: Hardware Integrationmentioning

confidence: 99%