BeGREEN: Beyond 5G Energy Efficient Networking by Hardware Acceleration and AI-Driven Management of Network Functions
This paper presents a technical overview of BeGREEN project and is intended to describe BeGREEN's technical scope and objectives. These objectives aim at improving energy efficiency of the beyond 5G (B5G) networks. BeGREEN technical agenda includes analysis of the combined energy and spectrum efficiency of the B5G networks, based on massive multiple-input-multiple-output (mMIMO) scenarios. The project proposes a novel architecture that includes several innovative solutions. An offloading engine is used for hardware acceleration that is a solution for compute-heavy physical layer processing in 5G new radio (5G NR) mMIMO and beyond to improve the processing performance and energy efficiency. The architecture also includes joint communication and sensing (JCAS) for improving energy efficiency of the physical layer functions by, e.g., efficient beam-search and beam tracking, and uses reconfigurable intelligent surfaces (RIS) as an enabler for JCAS. BeGREEN proposes an artificial intelligence (AI)-assisted energy-aware "Intelligent Plane" as an additional plane along with user plane and data plane, that allows the data, model, and inference to be seamlessly exchanged between network functions. The project also proposes an AI Engine that is consist of an execution environment that can host AI models and will manage their lifecycle and access to data.
Mir Ghoraishi (Gigasys Solutions), Miguel Catalan-Cid (i2CAT), Vladica Sark (IHP), Jesus Gutierrez Teran (IHP), Jose Oriol Sallent (UPC), Guillermo Bielsa (TSA), Juan-Francisco Esteban-Rivas (TSA), Simon Pryor (Acceleran)