Open Radio Access Network (O-RAN) fosters a new networking paradigm that supports flexible and open architectures, while enabling the functional disaggregation of traditional, monolithic, base stations. Specifically, the Lower-Layer Split (LLS) option 7.2x divides the PHY layer into Low-PHY at Open -Radio Unit (O-RU) and High-PHY at Open -Distributed Unit (O-DU), leveraging the so-called open fronthaul network, which imposes stringent latency requirements. In this work, we introduce and thoroughly examine the time window relationships that define the latency budget allocated to the open fronthaul network. Additionally, we propose a novel methodology to analyze the delay experienced by a realistic traffic pattern over a spine-leaf topology, accounting for various O-DU locations and site pools. To address the increased traffic load introduced by the fronthaul, we present a theoretical model to characterize the average delay across different priority levels when open fronthaul traffic coexists with flows from other Radio Access Technologies (RATs). This model is then validated and broadened through ns-3 simulations. Our findings show the applicability of the proposed methodology, which could be exploited by network operators in the planning phase, evincing its suitability to obtain benchmark delay values, offering a reliable tool for performance evaluation in open fronthaul networks.

The Open-Fronthaul (O-FH) is a Time Sensitive Network (TSN) segment within the Open-RAN (O-RAN) architecture, where the legacy base station is disaggregated following the 7.2x functional split. One of the strategic objectives sought by network operators is to foster the centralization of the Open - Distributed Unit (O-DU), to serve multiple remote sites. Hence, ensuring an accurately modeling of the fronthaul performance becomes critical, due to its stringent timing requirements. In this work, we propose a novel modeling methodology, based on Generalized Jackson Networks (GJN), to derive key performance metrics such as waiting time and utilization. Additionally, we apply Kingman’s approximation to evaluate delay percentiles under high traffic load conditions. This analytical method allows for fast and scalable performance evaluation, avoiding the need for extensive packet-level simulations, which become computationally prohibitive as traffic load steadily increases. Our results evince that under sensible operating situations, the proposed approach yields rather precise results, providing an upper performance bound.

During the last years we have witnessed a growing trend towards the deployment of disaggregated Radio Access Network (RAN) networks. In this context, the Open-RAN (ORAN) architecture is one of the most relevant approaches for 5G/6G networks, and it is believed to be a key element of forthcoming deployments. The performance of the so called Open - Fronthaul ($\mathrm{O}-\text{FH}$) segment is of the utmost importance to ensure an appropriate overall system performance. In this sense, the overall delay of the communication between nodes within the O-RAN fronthaul needs to be kept at very low values, to fulfill the requirements of the corresponding technologies. In this paper we propose exploiting queuing theory to model the O-FH performance, including a realistic traffic characterization. In particular, we present a theoretical framework based on Open Jackson Networks to model the one-way end-to-end delay, and we compare it with a that obtained by a realistic simulation setup. The results show that the theoretical model provides a reasonably accurate behavior under certain conditions, setting in all cases a tight upper bound for the end-to-end delay, which we identify as a key performance indicator.