Despite the success of the O-RAN Alliance in developing a set of interoperable interfaces, development of unique Radio Access Network (RAN) deployments remains challenging. This is especially true for military communications, where deployments are highly specialized with limited volume. The construction and maintenance of the RAN, which is a real time embedded system, is an ill-defined NP problem requiring teams of specialized system engineers, with specialized knowledge of the hardware platform. In this paper, we introduce a RAN Domain Specific Language (RDSL(TM)) to formally describe use cases, constraints, and multi-vendor hardware/software abstraction to allow automation of RAN construction. In this DSL, system requirements are declarative, and performance constraints are guaranteed by construction using an automated system solver. Using our RAN system solver platform, Gabriel(TM) we show how a system engineer can confidently modify RAN functionality without knowledge of the underlying hardware. We show benefits for specific system requirements when compared to the manually optimized, default configuration of the Intel FlexRAN(TM), and conclude that DSL/automation driven construction of the RAN can lead to significant power and latency benefits when the deployment constraints are tuned for a specific case. We give examples of how constraints and requirements can be formatted in a "Kubernetes style" YAML format which allows the use of other tools, such as Ansible, to integrate the generation of these requirements into higher level automation flows such as Service Management and Orchestration (SMO).

翻译：尽管O-RAN联盟在开发可互操作接口集方面取得了成功，但构建独特的无线接入网（RAN）部署方案仍然具有挑战性。对于军事通信而言尤其如此，因为这类部署具有高度专业化且规模有限的特点。RAN作为实时嵌入式系统，其构建与维护是一个定义不明确的NP难题，需要由掌握硬件平台专门知识的专业系统工程师团队来完成。本文提出一种RAN领域特定语言（RDSL™），通过形式化描述用例、约束条件以及多厂商硬件/软件抽象，实现RAN构建的自动化。在该领域特定语言中，系统需求采用声明式表述，性能约束通过自动化系统求解器在构建过程中予以保证。利用我们的RAN系统求解平台Gabriel™，我们展示了系统工程师如何在无需了解底层硬件的情况下可靠地修改RAN功能。相较于英特尔FlexRAN™手动优化的默认配置，我们展示了特定系统需求下的性能优势，并得出结论：当部署约束针对具体场景进行调整时，基于领域特定语言/自动化的RAN构建方式能带来显著的功耗与延迟优化。我们通过示例说明了如何采用"Kubernetes风格"的YAML格式来规范约束条件和需求描述，这使得Ansible等其他工具能够将这些需求的生成过程集成到服务管理与编排（SMO）等更高层级的自动化流程中。