LDPC Hardware Acceleration in 5G Open Radio Access Network Platforms

The Open Radio Access Network (RAN) concept has been gaining wide acceptance in recent network architectures, including 5G New Radio (NR) network deployments. Current Open RAN radio implementation efforts, aim at integrating several white-box hardware elements and executing digital processing on ope...

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Autores principales: Elissaios Alexios Papatheofanous, Dionysios Reisis, Konstantinos Nikitopoulos
Formato: article
Lenguaje:EN
Publicado: IEEE 2021
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Acceso en línea:https://doaj.org/article/7bcf9d7f5dcc469b9665d6080a800ab6
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Sumario:The Open Radio Access Network (RAN) concept has been gaining wide acceptance in recent network architectures, including 5G New Radio (NR) network deployments. Current Open RAN radio implementation efforts, aim at integrating several white-box hardware elements and executing digital processing on open-source software. When building such a software-based, 5G Open RAN platform, challenges include achieving real-time execution times for demanding computational blocks of the 5G NR physical layer processing, such as Low Density Parity Check (LDPC) decoding. In this context, having already identified both the capabilities as well as the challenges that Field-programmable Gate Arrays (FPGAs) offer for accelerating LDPC, we present our novel LDPC FPGA accelerator system. In this paper, we contribute the implementation details of our FPGA accelerator design as well as the process of integrating the accelerator with OpenAirInterface (OAI), the basis for our 5G NR platform. For the first time in the literature, we show an FPGA-based LDPC accelerator fully integrated with a complete software platform, that is able to achieve more than <inline-formula> <tex-math notation="LaTeX">$1.6Gbps$ </tex-math></inline-formula> decoding throughput and up to 13 times faster execution times compared to single core software implementations. Finally, in our results, we show that LDPC encoding is more challenging to accelerate due to lower computational complexity.