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Written By:

Andres Garcıa-Saavedra, Vincenzo Sciancalepore and Xavier Costa-Perez

Published: 10 Dec 2021


CTN Issue: December 2021

A note from the editor:

The standardization process conducted by bodies such as 3GPP makes it possible that a device designed by a company communicates seamlessly with infrastructure equipment from a different company. Hence the magic of traveling the world and connecting to networks wherever we go. The importance of this process cannot be overstated, especially to those old enough to remember the times of technology fragmentation. However, if we zoom in on the infrastructure itself, we still find walled-in vendor silos. The network equipment is provided as a hardware and software integrated platform by each vendor, with proprietary hooks and interfaces, and it cannot be mixed with gear from other vendors.

Open Radio Access Networks (O-RAN) aim at breaking those silos and taking us to a new paradigm of vendor interoperability, unified interfaces, and disaggregation of hardware and software. Besides allowing for off-the-shelf hardware and open-source software, mixed and matched from different vendors, O-RAN would also facilitate extending the ongoing process of network virtualization all the way to the radio access edges. The promised land of O-RAN is a place with supply chain diversity, a more vibrant ecosystem, increased competition, and maximum flexibility. And, by lowering the barrier to entry for new participants, unlocked innovation, but even with this promise many challenges remain to get us there.

As there is nothing better than learning directly from experts, we invite you to read the piece below, signed by Andres Garcia-Saavedra, Vincenzo Sciancalepore, and Xavier Costa-Perez, members of the O-RAN team at a major vendor such as NEC. We thank them profusely for contributing to CTN, and you hope you’ll enjoy the article in all its openness.

Angel Lozano, CTN Associate Editor

Open Radio Access Networks (O-RAN): A Beyond-5G Revolution?

Andres Garcia-Saavedra

Andres Garcia-Saavedra

NEC Laboratories Europe GmbH

Vincenzo Sciancalepore

Vincenzo Sciancalepore

NEC Laboratories Europe GmbH

Xavier Costa-Perez

Xavier Costa-Perez

NEC Laboratories Europe GmbH

1. Open Radio Access Networks

The virtualization of radio access networks (a.k.a.  vRAN),  with  the  promise of considerable savings in capital and operating expenses, high flexibility, and openness to foster innovation and competition, is the final milestone in the virtualization of wireless networks and will be a key technology as we move beyond 5G. Extending virtualization to the radio access, however, entails a number of challenges that are the object of study by multiple initiatives such as Rakuten’s greenfield deployment in Japan, Cisco’s open vRAN ecosystem, Facebook Telecom Infra Project’s vRAN, and the  O-RAN  alliance.  Among these efforts, O-RAN is arguably the one with most traction.

O-RAN is a major carrier-led effort to define the next generation of (v)RANs for multi-vendor deployments. It is aimed at disrupting the vRAN ecosystem by breaking vendor lock-ins and opening up a market that has been traditionally dominated by a small set of players. If successful, O-RAN might unleash an unprecedented level of innovation by abating the market entrance barrier to new competitors.

2. O-RAN Alliance

The O-RAN alliance is a worldwide effort to reach new levels of openness in next-generation vRANs [1]. Initially launched by 5 major mobile carriers a couple of years ago, it is nowadays supported by over 160 companies (including 24 mobile operators across 4 continents) representing an outstanding example of how operators and suppliers can constructively collaborate to define novel technical standards.

Its large carrier and vendor support has given it an exceptional momentum, producing over 40 technical specification documents within 2 years and 1.3 million lines of open-source code.

Fig. 1 depicts a high-level view of the O-RAN architecture [1]. Doubtlessly, the most important functional components introduced by O-RAN are the non- real-time (Non-RT) radio intelligent controller (RIC) and the near-RT RIC.  While the former is hosted by the service management and orchestration (SMO) framework, the latter may be co-located with 3GPP gNB functions, namely, O-RAN-compliant central unit (O-CU) and/or distributed unit (O- DU), or fully decoupled from them as long as latency constraints are respected.

Figure 1: O-RAN architecture [1]
Figure 1: O-RAN architecture [1]

Fig. 1 also depicts the O-Cloud, an O-RAN compliant cloud platform that uses hardware acceleration add-ons when needed (e.g., to speed up fast Fourier transform operations or forward error correction tasks). In the following, we detail the jurisdiction and roles of each functional component.

Service Management and Orchestration. The SMO consolidates several orchestration and management services, which may go beyond pure RAN management, say end-to-end network slice management. In the context of O- RAN, the main responsibilities of SMO are (i) fault, configuration, accounting, performance and security (FCAPS) interface to O-RAN network functions; (ii) large timescale RAN optimization; and (iii) O-Cloud management and orchestration via the O2 interface.

Non-RT RAN Intelligent Controller. As mentioned, this logical function resides within the SMO and provides the A1 interface to the Near-RT RIC. Its main goal is to support large timescale RAN optimization (seconds or minutes), including policy computation, ML model management (e.g., training), and other radio resource management functions within this timescale. Data management tasks requested by the Non-RT RIC should be converted into the O1/O2 interface while contextual/enrichment information can be provided to the near-RT RIC via the A1 interface.

Near-RT RAN intelligent Controller. Near-RT RIC is a logical function that enables optimization, control, and data monitoring of O-CU and O-DU nodes, in near-real-time (between 10 ms and 1s). To this end, Near-RT RIC control is steered by the policies and assisted by models computed/trained by the Non-RT RIC. One of the main operations assigned to the near-RT RIC is radio resource management, but near-RT RIC also supports 3rd party applications (so-called xApps).

This architecture inherently enables three independent—yet with sporadic interactions—control loops:

  1. Non-RT RIC control loop: Long timescale operation of the orders of seconds or minutes. The goal is to perform O-RAN specific orchestration decisions such as policy configuration or ML model training.
  2. Near-RT RIC control loop:  Subsecond timescale operation with the goal of performing tasks such as policy enforcement or radio resource management.
  3. O-DU Scheduler control loop: Real-time operation performing legacy radio operations such as HARQ, beamforming or scheduling—out of O- RAN’s scope.

3. O-RAN Disruption Potential

3.1 AI/ML-driven Joint Orchestration of O-RAN Resources

O-RAN’s disposition towards  software-defined  AI-assisted  RAN  control  fosters different degrees of openness, namely, systems comprised of (i) O-RAN- compliant physical network functions exposing and using O-RAN interfaces so different vendors can interplay (lowest degree of openness); (ii) chassis of servers and racks in a cloud shared  among  multiple  vendors  (higher  degree  of  openness); and (iii) one or multiple O-Clouds, a fabric of generic servers and networking infrastructure hosting O-RAN software that is decoupled from the hardware at different layers.

Such openness enables substantial flexibility to deploy each of the logical functions introduced earlier, e.g., O-DU and O-RU can be collocated or not de-pending on the context and particular needs of the operator and these decisions may be changed over time with minimal cost [2].

Despite the potential benefits of RAN virtualization, dynamic resource orchestration becomes more compounded. Specifically, the problem of optimally allocating computing resources and radio resources is now coupled and requires joint management [3]. Moreover, the virtualized base stations sha3re a pool of computing resources and may or may not share radio spectrum as in [4], which further complicates the orchestration problem.

3.2 O-RAN in Shared Computing Platforms

Due to the computing fluctuations inherent to wireless dynamics and resource contention in shared computing infrastructure, the price to migrate from dedicated to shared platforms may be high. vRANs shall rely on cloud platforms comprised of pools of shared computing resources (mostly CPUs, but also hardware accelerators brokered by an abstraction layer), to host virtualized functions such as the PHY [5]. However, while CUs are amenable to virtualization in regional clouds, virtualized DUs (vDUs)—namely, the vPHY therein—require fast and predictable computation in edge clouds [5-7]. Shared computing platforms provide a harsh environment for DUs because they trade off the predictability supplied by dedicated platforms for higher flexibility and cost-efficiency [8, 9].

Indeed, research has shown that resource contention in shared computing infrastructure, even when placing virtual functions on separate cores, may lead to up to 40% of performance degradation compared to dedicated platforms [9, 10]—the so-called noisy neighbor problem. [11] shows that the baseline architecture of a DU collapses upon moments of deficit in computing capacity. Recent solutions to accelerate some signal processing tasks certainly help but do not tackle the core problem: a DU pipeline that requires predictable computing to provide carrier-grade reliability.

Reference [11] shows that a redesign of the baseline DU pipeline can provide carrier-grade reliability in these platforms. More specifically, the use of (i) a two-stage downlink scheduling approach, (ii) predictive or early HARQ, and (iii) congestion control, allows us to decouple compute-intensive data channel processing tasks from less compute-intensive but critical tasks such as processing control channels or scheduling.

3.3 Smart Surfaces towards Open Environments

The advent of smart surfaces is paving the road towards a highly-dense open environment where the signal propagation is properly disciplined. Reconfigurable intelligent surfaces (RISs) represent a new business opportunity to push for the openness revolution. Indeed, RIS components can be designed to be plugged into a shared O-RAN view, as depicted in Fig. 2. A new network segment is envisioned between the RAN elements and the end-users wherein the elements of the RISs can be automatically triggered and configured by the RIS controller within short timescales (milliseconds) to drive the overall efficiency at the network edge. Such a controller will be interfaced to the orchestration layer by means of a new reference point, namely Rx, which instructs transmitter configurations on longer timescales (minutes) for specific environments or given use cases. In parallel, the RIS controller can adjust the RIS configurations based on the received feedback as well as the desired performance indicators. Additionally, a new interface called R2 can be designed to create a direct link between the near-RT RIC and the RIS Controller. This will allow to simultaneously control the RIS configurations and the BS beamforming in very short timescales. The design of an “Open Environment” interface is also envisioned between the RIS elements and the radio units handling the digital front in order to bring flexibility and programmability into the overall improved picture.

Figure 2: Reference architecture for RIS in O-RAN, with the RIS at the bottom left corner [12].
Figure 2: Reference architecture for RIS in O-RAN, with the RIS at the bottom left corner [12].

4. O-RAN Pros and Cons

State-of-the-art vRAN solutions applied today in the market, which rely on dedicated hardware acceleration, jeopardize the very reasons that make virtualization appealing for the RAN in the first place: flexibility and cost-efficiency. First, research has shown that cloud RANs require many more resources than legacy RAN platforms to attain similar performance guarantees in real mobile networks. Second, dedicated accelerators make vDUs more expensive and power-hungry than their legacy counterparts—let alone the fact that the much-longed for hardware/software decoupling is not achieved.

O-RAN’s O-Cloud approach strives to address the above issues: while hard- ware acceleration is still required for specialized, compute-intensive and repetitive tasks, such as fast Fourier transform and forward error coding, O-RAN’s approach is to provide pools of shared accelerators, brokered by an abstraction layer. The goal is to preserve the carrier-grade performance that only hardware accelerators can provide without sacrificing the f flexibility and cost-efficiency of RAN virtualization.

O-RAN does not only target virtualized RAN scenarios, but open RAN deployments overall to enable competition in the RAN, traditionally monopolized by a small set of manufacturers. This should accelerate innovation and help reduce costs. However, according to recent market forecasts [13], O-RAN is expected to cover only about 10% of the overall market by 2025. Thus, despite the new business opportunities opened to small and medium-scale vendors (traditionally alien to large-scale RAN deployments) significant hurdles will need to be overcome to reach the economies of scale of major vendors in the RAN ecosystem in order to be competitive. If O-RAN is successful in delivering on the high promises in RAN openness and innovation, it might be actually becoming the predominant market share deployment solution for future 6G networks.


  1. A. Garcia-Saavedra and X. Costa-Perez, “O-RAN: Disrupting the virtualized RAN ecosystem,” IEEE Commun. Standards Magazine, pp. 1–8, 2021.
  2. A. Garcia-Saavedra, J. X. Salvat, X. Li, and X. Costa-Perez, “Wizhaul: On the centralization degree of cloud RAN next generation fronthaul,” IEEE Trans. Mobile Computing, vol. 17, no. 10, pp. 2452– 2466, 2018.
  3. J. A. Ayala-Romero et al., “vrAIn: A deep learning approach tailoring computing and radio resources in virtualized RANs,” Int’l Conf. Mobile Computing and Networking,” 2019.
  4. J. Mendes et al., “Cellular access multi-tenancy through small-cell virtualization and common RF front-end sharing,” Computer Commun., vol. 133, pp. 59–66, 2019.
  5. O-RAN Alliance, “Cloud architecture and deployment scenarios v02.01 (O-RAN.WG6.CAD-v02.01),” Technical Report, Jul. 2020.
  6. Cisco, Rakuten, Altiostar, “Reimagining the end-to-end mobile network in the 5G era,” White Paper, 2019.
  7. Samsung, “Virtualized radio access network: architecture, key technologies and benefits.” Technical Report, 2019.
  8. P. Kumar et al., “Picnic: Predictable virtualized NIC,” ACM Special Interest Group on Data Commun., ser. SIGCOMM, 2019, p. 351–366.
  9. A.   Tootoonchian, et al., “Resq:       Enabling SLOS in network function virtualization,” USENIX Symp. Netw. Systems Design & Implementation, Apr. 2018, pp.  283–297.  [Online:]
  10. A. Manousis, R. Sharma, V. Sekar, and J. Sherry, “Contention-aware performance prediction for virtualized network functions,” ACM SIGCOMM ’20, p. 270–282.
  11. G. Garcia-Aviles, A. Garcia-Saavedra, M. Gramaglia, X. Costa-Perez, P. Serrano, and A. Banchs, “Nuberu: Reliable RAN virtualization in shared platforms,” Int’l Conf. Mobile Computing and Networking, ser. MobiCom, 2021, p. 749–761. [Online:]
  12. E. Strinati et al., “Reconfigurable, intelligent and sustainable wireless environments for 6G smart connectivity,” IEEE Commun. Mag., 2021
  13. Dell’Oro Group, “Open RAN market expected to approach $10 B, according to Dell’Oro group,” Feb. 2021. [Online:]

Statements and opinions given in a work published by the IEEE or the IEEE Communications Society are the expressions of the author(s). Responsibility for the content of published articles rests upon the authors(s), not IEEE nor the IEEE Communications Society.


Having been in wireless industry on both sides of the isle, and in forefront of new developments through the years, I can not agree more that open RAN in true sense is indeed a game changer for the industry. It has the potential to not only expedites advances in technology, it also optimizes the cost of implementation and operation by considerable amount.

The irony is that the idea has been around for so long and the progress has been so slow. There is no doubt that service providers stand to benefit tremendously from O-RAN. the question is how could O-RAN becomes an attractive prospect for intrenched suppliers who have had a monopoly with their proprietary hardware-for-software framework. Let us hope that there emerge disruptors that would force sluggish legacy suppliers to follow suit and brings this wireless industry panacea to realization.

Submitted by habib.riazi@co… on 14 December 2021

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