The shift from conventional radio access network (RAN) architectures to Open RAN (O-RAN) has ignited interest for its principles of open interfaces, virtualization, cloudification, and AI/ML-driven automation. Recent advancements in cell-free massive MIMO (CM-mMIMO) technology, one of promising 6G candidates, mark a new era in wireless communication by incorporating ultra-dense networks with joint transmission (JT) and streamlined linear processing. This paper delves into energy-efficient operations for mmWave-based CF-mMIMO within the cloudified O-RAN framework. We propose on/off schemes based on RF-beamformed large-scale propagation gain between distributed radio units (RUs) and users, evaluating the decrease in user transmission rate with inactive RUs. Our model considers power consumption across radio sites, fronthaul, and cloud, deriving network energy savings (NES) from RU on/off and adaptive cloud resource allocation. We compare O-RAN NES with functional split options 7-2a and 7-2b. Extensive simulations, considering rician channel modeling and pilot contamination, validate the superiority of our approach through comparison with other methods.
KSP Keywords
Adaptive cloud, Channel modeling, Cloud resource allocation, Energy saving, Joint transmission, Large-scale propagation, Power Consumption, Propagation gain, Radio Access Network(RAN), Rician channel, Switching scheme
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