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Title: Cell-Free Massive MIMO in O-RAN: Energy-Aware Joint Orchestration of Cloud, Fronthaul, and Radio Resources
Authors: Demir, O.T.
Masoudi, M.
Bjornson, E.
Cavdar, C.
Keywords: Cell-free massive MIMO; Cloud computing; Computer architecture; end-to-end resource allocation; joint network orchestration; joint transmission; Massive MIMO; Optical network units; Power demand; Resource management; Virtualization; virtualized O-RAN
Cells; Computer architecture; Computing power; Cytology; Electric power utilization; Energy efficiency; Green computing; Light transmission; Network architecture; Radio; Radio access networks; Resource allocation; Spectrum efficiency; Virtual reality; Cell-free; Cell-free massive MIMO; Cloud-computing; End to end; End-to-end resource allocation; Joint network; Joint network orchestration; Joint transmissions; Massive MIMO; Optical network units; Power demands; Radio access networks; Resource management; Resources allocation; Virtualizations; Virtualized open radio access network; Virtualization
Issue Date: 2024
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: For the energy-efficient deployment of cell-free massive MIMO functionality in a practical wireless network, the end-to-end (from radio site to the cloud) energy-aware operation is essential. In line with the cloudification and virtualization in the open radio access networks (O-RAN), it is indisputable to envision prospective cell-free infrastructure on top of the O-RAN architecture. In this paper, we explore the performance and power consumption of cell-free massive MIMO technology in comparison with traditional small-cell systems, in the virtualized O-RAN architecture. We compare two different functional split options and different resource orchestration mechanisms. In the end-to-end orchestration scheme, we aim to minimize the end-to-end power consumption by jointly allocating the radio, optical fronthaul, and virtualized cloud processing resources. We compare end-to-end orchestration with two other schemes: i) “radio-only” where radio resources are optimized independently from the cloud and ii) “local cloud coordination” where orchestration is only allowed among a local cluster of radio units. We develop several algorithms to solve the end-to-end power minimization and sum spectral efficiency maximization problems. The numerical results demonstrate that end-to-end resource allocation with fully virtualized fronthaul and cloud resources provides a substantial additional power saving than the other resource orchestration schemes. IEEE
ISSN: 0733-8716
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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