GreenRAN: A Channel-Aware Green O-RAN Framework for NextG Mobile Systems

Green communications have always been a target for Open Radio Access Network (O-RAN), given the exploding infrastructures and data in 5G and beyond cellular networks (NextG). Existing research either explores the sleeping mode or workload consolidation of the RAN components, radio units (RUs), distributed units (DUs), and centralized units (CUs). However, current research on green O-RAN scenarios rarely takes into account the channel qualities between user equipment (UEs) and base stations (BSs), more precisely, between UEs and RUs. A cyclic dependency between the inter-RU and intra-RU resource schedulers makes it challenging to incorporate channel awareness at both levels. Armed with this insight, in this paper, we propose GreenRAN, a channel-aware O-RAN framework that executes two power-saving steps: channel-aware RU switching ON/OFF and then CU-DU workload consolidation. The two algorithms act as an add-on rApp, Channel-Aware RU ON/OFF controller (CARC), and an add-on xApp, CU-DU Placement Module (CDPM), in the O-RAN framework, respectively. The output of CARC serves as the input of CDPM, minimizing the power consumption of GreenRAN while providing Quality-of-Service (QoS) guarantees to UEs. Extensive experiments verify the effectiveness of GreenRAN in power saving and the feasibility of deploying the proposed algorithms within the O-RAN architecture” compared with other baselines.