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.

The advent of wireless technologies has led to the development of novel services for end-users, with stringent needs and requirements. High availability, very high throughput, low latency, and reliability are all of them crucial performance parameters. To address these demands, emerging technologies, such as non-terrestrial networks or millimeter wave (mmWave), are being included in 5G and Beyond 5G (B5G) specifications. mmWave enables massive data transmissions, at the expense of a more hostile propagation, typical for high frequency bands. Consequently, the inherent instability of the physical channel significantly affects the upper layers of the protocol stack, resulting in congestion and data losses, which might strongly hinder the overall communication performance. These challenges can be addressed not only at the link layer, but at any affected layer. QUIC is a new transport protocol designed to reduce communications latency in many ways. Among other features, it enables the use of multiple streams to effectively manage data flows sent through its underlying UDP socket. This paper introduces an implementation of priority-based stream schedulers along with the design of a flexible interface. Exploiting the proposed approach, applications are able to set the required scheduling scheme, as well as the stream priorities. The feasibility of the proposed approach is validated through an extensive experiment campaign, which combines Docker containers, the ns-3 simulator and the Mahimahi framework, which is exploited to introduce realistic mmWave channel traces. The results evince that an appropriate stream scheduler can indeed yield lower delays for time-sensitive applications by up to 36% under unreliable conditions.

We analyze the performance of QUIC over Non-Terrestrial-Networks (NTN). The presence of this transport protocol has strongly increased since it was originally proposed, but its behavior over wireless networks is still an open question. We focus on NTN, which will play a key role in forthcoming cellular systems, and whose underlying connectivity exhibits a highly variable behavior. We show that using multiple streams, which is one of the most relevant advantages of QUIC, yields performance improvements. We then propose a delay-based scheduler, based on dynamic queuing control, and we compare its behavior with that exhibited by legacy solutions. We carry out an extensive experiment campaign exploiting a novel methodology that combines virtualization techniques, real QUIC implementation, and ns-3 to model NTN links. The results show that the proposed scheduling policies fairly distribute the delay between streams, without jeopardizing the throughput, even under very high load situations.

We study the performance exhibited by the transport protocols, Transport Control Protocol (TCP) and QUIC, over realistic satellite networks. We propose a novel methodology, which combines real implementation (exploiting virtualization techniques) and simulation, to carry out systematic and repetitive experiments. We modify the default operation of the ns-3 framework and we integrate the dynamism that characterizes satellite communication links, particularly Low Earth Orbit (LEO). We carry out a thorough assessment over different setups, changing the operating frequency band and packet buffer lengths. In addition, we ascertain the impact of using the multi-streaming feature that QUIC integrates. The results show that QUIC yields lower delays than TCP, although it might suffer from higher jitter in particular setups. In addition, the results evince that using multiple streams in QUIC does not yield a relevant gain for the default Round-Robin (RR) scheduler. We propose more appropriate scheduling strategies, which are able to yield better performances with unbalanced traffic. Even if the behavior of transport protocols over non-terrestrial-networks might not be always appropriate, the obtained results evince that QUIC can definitively bring benefits when compared to TCP. Furthermore, we have shown that optimal scheduling policies yields a fairer performance when using multiple flows, having unbalanced traffic loads.