Joint planning and operation for sustainable user-centric cell-free mMIMO networks

User Equipment (UE)-centric Cell-Free massive Multiple-Input Multiple-Output (CF mMIMO) has emerged as a key enabling architecture for sixth-generation (6G) networks, offering a favorable trade-off between performance gains, cost and energy-efficiency. However, optimizing Access Point (AP) deployment and hardware provisioning in UE-centric CF mMIMO remains a challenging task, because planning decisions are tightly coupled with complex operational decisions such as the dynamic AP-UE clustering. In this paper, we address the joint planning-and-operation problem for UE-centric CF mMIMO networks under realistic cost, energy and performance-related models and constraints. We propose a hierarchical optimization framework in which a novel Deployment Evolutionary Algorithm (DEA) iteratively refines AP locations and heterogeneous hardware configurations, while a Weight-driven Greedy Round-Robin (WG-RR) algorithm acts as an operational oracle, performing UE-centric AP–UE clustering during the operational phase in a manner consistent with operator-defined business intents (i.e. objective weights). To ensure robust and realistic network dimensioning, candidate deployments are evaluated over multiple traffic demand-oriented snapshots that capture UE mobility and spectral-efficiency demand fluctuations. Extensive multi-objective and multi-snapshot evaluations reveal significant spectral-efficiency diminishing returns with increasing deployment and cooperation density, exposing practical operating points that substantially reduce CAPEX and operational power with negligible performance loss. The results further demonstrate that heterogeneous AP deployments enable superior planning decisions, thereby supporting the gradual and sustainable integration of UE-centric CF mMIMO into existing multi-cell infrastructures.