The next generation fronthaul interface (NGFI) architecture has been specified recently in the IEEE P1914.1 standard for packet-based fronthaul transport networks. NGFI is a flexible and cost-effective solution developed for meeting stringent latency and throughput requirements of future centralized and virtualized radio access networks (C-RAN/vRAN) in the 5th generation mobile networks (5G). NGFI allows for splitting baseband processing functions of a radio frequency signal between radio unit (RU), distributed unit (DU), and central unit (CU), where each of these elements may be located at a different site of the network. In the NGFI network, the radio data to be processed is transmitted between the RU, DU, and CU in the form of packets and routed by means of packet switches over a common packet-based fronthaul transport network. In this paper, we address a basic optimization problem in an NGFI network that concerns allocation of transmission resources in network links for the RU–DU and DU–CU data flows assuming quality of service (QoS) requirements related to maximal latency of these flows. To formulate the latency-aware flow allocation (LFA) optimization problem, we apply the mixed integer programming (MIP) approach. To generate solutions to larger LFA problem instances, we develop a meta-heuristic algorithm. To account for latency constraints in both MIP and meta-heuristic, we make use of a worst-case latency estimation model. The results of numerical experiments run in three network topologies for different network instances show the effectiveness of the meta-heuristic method, when compared to the MIP approach. These results also allow us to assess the performance of the NGFI network considered.

在基于分组的前传传输网络的IEEE P1914.1标准中，最近已指定了下一代前传接口（NGFI）体系结构。NGFI是一种灵活且经济高效的解决方案，旨在满足第五代移动网络（5G）中未来的集中式和虚拟化无线接入网络（C-RAN / vRAN）的严格延迟和吞吐量要求。NGFI允许在无线单元（RU），分布式单元（DU）和中央单元（CU）之间拆分射频信号的基带处理功能，其中这些元素中的每个元素可能位于网络的不同站点。在NGFI网络中，要处理的无线电数据以数据包的形式在RU，DU和CU之间传输，并通过数据包交换机通过基于数据包的常见前传传输网络进行路由。在本文中，我们假设服务质量（QoS）要求与这些流的最大延迟相关，我们解决了NGFI网络中的一个基本优化问题，该问题涉及在网络链路中为RU-DU和DU-CU数据流分配传输资源。为了制定延迟感知流分配（LFA）优化问题，我们应用了混合整数规划（MIP）方法。为了生成更大的LFA问题实例的解决方案，我们开发了一种元启发式算法。为了解决MIP和元启发式方法中的延迟约束，我们使用了最坏情况的延迟估计模型。与MIP方法相比，在三种针对不同网络实例的网络拓扑中进行的数值实验结果显示了元启发式方法的有效性。