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：本文考虑开放无线接入网架构下可扩展的无小区大规模多输入多输出网络，该网络由用户设备、射频单元和分布式处理单元构成。用户设备由动态分配的用户中心射频单元集群提供服务。相应的集群处理器（为每个用户实现物理层功能）以软件定义虚拟网络功能的形式部署于分布式处理单元中。与现有文献主要关注无限制前传通信与计算条件下的用户速率表征不同，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。特别地，我们系统性地探讨了前传负载均衡与计算资源联合分配这一新问题。基于我们提出的优化框架，我们展示了具有代表性的数值结果，这些结果揭示了射频单元模数转换过程中存在最优量化比特数的现象。