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The emergence of Centralized-RAN (C-RAN) has revolutionized mobile network infrastructure, offering streamlined cell-site engineering and enhanced network management capabilities. As C-RAN gains momentum, the focus shifts to optimizing fronthaul links. While fiber fronthaul guarantees performance, wireless alternatives provide cost efficiency and scalability, making them preferable in densely urbanized areas. However, wireless fronthaul often requires expensive over-dimensioning to overcome the challenging atmospheric attenuation typical of high frequencies. We propose a framework designed to continuously align radio access capacity with fronthaul link quality to overcome this rigidity. By gradually adapting radio access capacity to available fronthaul capacity, the framework ensures smooth degradation rather than complete service loss. Various strategies are proposed, considering factors like functional split and beamforming technology and exploring the tradeoff between adaptation strategy complexity and end-to-end system performance. Numerical evaluations using experimental rain attenuation data illustrate the framework's effectiveness in optimizing radio access capacity under realistically variable fronthaul link quality, ultimately proving the importance of adaptive capacity management in maximizing C-RAN efficiency.

The spectrum crunch challenge poses a vital threat to the progress of cellular networks and recently prompted the inclusion of millimeter wave (mmWave) and Upper 6GHz (U6G) in the 3GPP standards. These two bands promise to unlock a large portion of untapped spectrum, but the harsh propagation due to the increased carrier frequency might negatively impact the performance of urban Radio Access Network (RAN) deployments. Within the span of a year, two co-located 5G networks operating in these frequency bands were deployed at Politecnico di Milano, Milan, Italy, entirely dedicated to the dense urban performance assessment of the two systems. This paper presents an in-depth analysis of the measurement campaigns conducted on them, with the U6G campaign representing the first of its kind. A benchmark is provided by ray-tracing simulations. The results suggest that networks operating in these frequency bands provide good indoor and outdoor coverage and throughput in urban scenarios, even when deployed in the macro base station setup common to lower frequencies. In addition, a comparative performance analysis of these two key technologies is provided, offering insights on their relative strengths, weaknesses and improvement margins and informing on which bands is better suited for urban macro coverage.

The heterogeneity of use cases that next-generation wireless systems need to support calls for flexible and programmable networks that can autonomously adapt to the application requirements. Specifically, traffic flows that support critical applications (e.g., vehicular control or safety communications) often come with a requirement in terms of guaranteed performance. At the same time, others are more elastic and can adapt to the resources made available by the network (e.g., video streaming). To this end, the Open Radio Access Network (RAN) paradigm is seen as an enabler of dynamic control and adaptation of the protocol stack of 3rd Generation Partnership Project (3GPP) networks in the 5th Generation (5G) and beyond. Through its embodiment in the O-RAN alliance specifications, it introduces the Ran Intelligent Controllers (RICs), which enable closed-loop control, leveraging a rich set of RAN Key Performance Measurements (KPMs) to build a representation of the network and enforcing dynamic control through the configuration of 3GPP-defined stack parameters. In this paper, we leverage the Open RAN closed-loop control capabilities to design, implement, and evaluate multiple data-driven and dynamic Service Level Agreement (SLA) enforcement policies, capable of adapting the RAN semi-persistent scheduling patterns to match users requirements. To do so, we implement semi-persistent scheduling capabilities in the OpenAirInterface (OAI) 5G stack, as well as an easily extensible and customizable version of the Open RAN E2 interface that connects the OAI base stations to the near-real-time RIC. We deploy and test our framework on Colosseum, a large-scale hardware-in-the-loop channel emulator. Results confirm the effectiveness of the proposed Open RAN-based solution in managing SLA in near-real-time.

Vehicular communications integrated with the Radio Access Network (RAN) are envisioned as a breakthrough application for the 6th generation (6G) cellular systems. However, traditional RANs lack the flexibility to enable sophisticated control mechanisms that are demanded by the strict performance requirements of the vehicle-to-everything (V2X) environment. In contrast, the features of Open RAN (O-RAN) can be exploited to support advanced use cases, as its core paradigms represent an ideal framework for orchestrating vehicular communication. Although the high potential stemming from their integration can be easily seen and recognized, the effective combination of the two ecosystems is an open issue. Conceptual and architectural advances are required for O-RAN to be capable of facilitating network intelligence in V2X. This article pioneers the integration of the two strategies for seamlessly incorporating V2X control within O-RAN ecosystem. First, an enabling architecture that tightly integrates V2X and O-RAN is proposed and discussed. Then, a set of key V2X challenges is identified, and O-RAN-based solutions are proposed, paired with extensive numerical analysis to support their effectiveness. Results showcase the superior performance of such an approach in terms of raw throughput, network resilience, and control overhead. Finally, these results validate the proposed enabling architecture and confirm the potential of O-RAN in support of V2X communications.

Millimeter wave (mmWave) communications has been recently standardized for use in the fifth generation (5G) of cellular networks, fulfilling the promise of multi-gigabit mobile throughput of current and future mobile radio network generations. In this context, the network densification required to overcome the difficult mmWave propagation will result in increased deployment costs. Integrated Access and Backhaul (IAB) has been proposed as an effective mean of reducing densification costs by deploying a wireless mesh network of base stations, where backhaul and access transmissions share the same radio technology. However, IAB requires sophisticated control mechanisms to operate efficiently and address the increased complexity. The Open Radio Access Network (RAN) paradigm represents the ideal enabler of RAN intelligent control, but its current specifications are not compatible with IAB. In this work, we discuss the challenges of integrating IAB into the Open RAN ecosystem, detailing the required architectural extensions that will enable dynamic control of 5G IAB networks. We implement the proposed integrated architecture into the first publicly-available Open-RAN-enabled experimental framework, which allows prototyping and testing Open-RAN-based solutions over end-to-end 5G IAB networks. Finally, we validate the framework with both ideal and realistic deployment scenarios exploiting the large-scale testing capabilities of publicly available experimental platforms

Advances in the automotive industry and the ever-increasing demand for Connected and Autonomous Vehicles (CAVs) are pushing for a new epoch of networked wireless systems. Vehicular communications, or Vehicle-to-Everything (V2X), are expected to be among the main actors of the future beyond 5G and 6G networks. However, the challenging application requirements, the fast variability of the vehicular environment, and the harsh propagation conditions of high frequencies call for sophisticated control mechanisms to ensure the success of such a disruptive technology. While traditional Radio Access Networks (RAN) lack the flexibility to support the required control primitives, the emergent concept of Open RAN (O-RAN) appears as an ideal enabler of V2X communication orchestration. However, effectively integrating the two ecosystems is still an open issue. This paper discusses possible integration strategies, highlighting the challenges and opportunities of leveraging O-RAN to enable real-time V2X control. Additionally, we enrich our discussion with potential research directions stemming from the current state-of-the-art, and we provide preliminary simulation results that validate the effectiveness of the proposed integration.

The introduction of the mm-Wave spectrum into 5G NR promises to bring about unprecedented data throughput to future mobile wireless networks but comes with several challenges. Network densification has been proposed as a viable solution to increase RAN resilience, and the newly introduced Integrated-Access-and-Backhaul (IAB) is considered a key enabling technology with compelling cost-reducing opportunities for such dense deployments. Reconfigurable Intelligent Surfaces (RIS) have recently gained extreme popularity as they can create Smart Radio Environments by EM wave manipulation and behave as inexpensive passive relays. However, it is not yet clear what role this technology can play in a large RAN deployment. With the scope of filling this gap, we study the blockage resilience of realistic mm-Wave RAN deployments that use IAB and RIS. The RAN layouts have been optimised by means of a novel mm-Wave planning tool based on MILP formulation. Numerical results show how adding RISs to IAB deployments can provide high blockage resistance levels while significantly reducing the overall network planning cost., Comment: 2022 IEEE Wireless Communications and Networking Conference (WCNC) (IEEE WCNC 2022)

With the capability to support gigabit data rates, millimetre-wave (mm-Wave) communication is unanimously considered a key technology of future cellular networks. However, the harsh propagation at such high frequencies makes these networks quite susceptible to failures due to obstacle blockages. Recently introduced Reconfigurable Intelligent Surfaces (RISs) can enhance the coverage of mm-Wave communications by improving the received signal power and offering an alternative radio path when the direct link is interrupted. While several works have addressed this possibility from a communication standpoint, none of these has yet investigated the impact of RISs on large-scale mm-Wave networks. Aiming to fill this literature gap, we propose a new mathematical formulation of the coverage planning problem that includes RISs. Using well-established planning methods, we have developed a new optimization model where RISs can be installed alongside base stations to assist the communications, creating what we have defined as Smart Radio Connections. Our simulation campaigns show that RISs effectively increase both throughput and coverage of access networks, while further numerical results highlight additional benefits that the simplified scenarios analyzed by previous works could not reveal.

Edge computing has been recently introduced as a way to bring computational capabilities closer to end users of modern network-based services, in order to support existent and future delay-sensitive applications by effectively addressing the high propagation delay issue that affects cloud computing. However, the problem of efficiently and fairly manage the system resources presents particular challenges due to the limited capacity of both edge nodes and wireless access networks, as well as the heterogeneity of resources and services' requirements. To this end, we propose a techno-economic market where service providers act as buyers, securing both radio and computing resources for the execution of their associated end users' jobs, while being constrained by a budget limit. We design an allocation mechanism that employs convex programming in order to find the unique market equilibrium point that maximizes fairness, while making sure that all buyers receive their preferred resource bundle. Additionally, we derive theoretical properties that confirm how the market equilibrium approach strikes a balance between fairness and efficiency. We also propose alternative allocation mechanisms and give a comparison with the market-based mechanism. Finally, we conduct simulations in order to numerically analyze and compare the performance of the mechanisms and confirm the theoretical properties of the market model., Comment: Corrected typos and figure orientation. in IEEE Transactions on Mobile Computing