Unlocking the Energy-Saving Potential in O-RAN Cell-Free Massive MIMO by Joint Orchestration of Radio, Wireless Fronthaul, and Cloud Resources
Ozan Alp Topal, \"Ozlem Tu\u{g}fe Demir, Emil Bj\"ornson, and Cicek Cavdar

TL;DR
This paper proposes a joint resource orchestration framework for O-RAN cell-free massive MIMO networks that significantly reduces energy consumption by optimizing radio, fronthaul, and cloud resources.
Contribution
It introduces a novel end-to-end power consumption model and develops algorithms for centralized and distributed precoding to maximize energy efficiency.
Findings
End-to-end resource orchestration achieves up to 70% energy savings.
Centralized precoding outperforms distributed precoding.
Distributing antennas reduces power consumption while maintaining high performance.
Abstract
Network virtualization and cloudification in Open Radio Access Networks (O-RAN) enable joint orchestration of the processing and fronthaul resources, which are essential for realizing the energy-saving potential of cell-free massive MIMO networks. To harness this potential, we investigate cell-free massive MIMO deployed over an O-RAN architecture with a wireless fronthaul that removes the need for fiber deployment. We first model the end-to-end power consumption under wireless fronthaul. Then, we propose a joint orchestration framework for radio, fronthaul, and processing resources that minimizes end-to-end power consumption while satisfying user-equipment (UE) rate requirements and wireless-fronthaul constraints. Two algorithms are developed: a scenario-sampling/group-Lasso method for centralized precoding and a block-coordinate descent method for distributed precoding. Numerical…
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