We consider scalable cell-free massive multiple-input multiple-output networks under an open radio access network paradigm comprising user equipments (UEs), radio units (RUs), and decentralized processing units (DUs). UEs are served by dynamically allocated user-centric clusters of RUs. The corresponding cluster processors (implementing the physical layer for each user) are hosted by the DUs as software-defined virtual network functions. Unlike the current literature, mainly focused on the characterization of the user rates under unrestricted fronthaul communication and computation, in this work we explicitly take into account the fronthaul topology, the limited fronthaul communication capacity, and computation constraints at the DUs. In particular, we systematically address the new problem of joint fronthaul load balancing and allocation of the computation resource. As a consequence of our new optimization framework, we present representative numerical results highlighting the existence of an optimal number of quantization bits in the analog-to-digital conversion at the RUs.

翻译：在开放无线接入网络架构下，我们考虑可扩展的无蜂窝大规模多输入多输出网络，该网络包含用户设备、射频单元和分布式处理单元。用户设备由动态分配的用户中心化射频单元簇提供服务。相应的簇处理器（实现每个用户的物理层功能）以软件定义虚拟网络功能的形式托管在分布式处理单元上。不同于当前主要关注无约束前传通信与计算条件下用户速率特性的文献，本研究明确考虑了前传拓扑结构、有限的前传通信容量以及分布式处理单元的计算约束。具体而言，我们系统性地解决了联合前传负载均衡与计算资源分配这一新问题。通过提出的优化框架，我们展示了代表性数值结果，揭示了射频单元模数转换中存在最优量化比特数。