Cell-free multi-user multiple input multiple output networks are a promising alternative to classical cellular architectures, since they have the potential to provide uniform service quality and high resource utilisation over the entire coverage area of the network. To realise this potential, previous works have developed radio resource management mechanisms using various optimisation engines. In this work, we consider the problem of overall ergodic spectral efficiency maximisation in the context of uplink-downlink data power control in cell-free networks. To solve this problem in large networks, and to address convergence-time limitations, we apply scalable multi-objective Bayesian optimisation. Furthermore, we discuss how an intersection of multi-fidelity emulation and Bayesian optimisation can improve radio resource management in cell-free networks.
翻译:无细胞多用户多输入多输出输出网络是传统细胞结构的一个大有希望的替代办法,因为它们有可能在整个网络覆盖区提供统一的服务质量和高资源利用。为了实现这一潜力,先前的工程利用各种优化引擎开发了无线电资源管理机制。在这项工作中,我们考虑到在无细胞网络上行链-下行链路数据功率控制方面全面实现电子光谱效率最大化的问题。为了在大型网络中解决这一问题,并解决趋同时间的限制,我们采用了可扩展的多目标巴耶斯优化。此外,我们讨论了多纤维模擬和巴耶斯优化的交叉如何改善无细胞网络中的无线电资源管理。