Radio hardware virtualization for software-defined wireless networks

Software-Defined Network (SDN) is a promising architecture for next generation Internet. SDN can achieve Network Function Virtualization much more efficiently than conventional architectures by splitting the data and control planes. Though SDN emerged first in wired network, its wireless counterpart Software-Defined Wireless Network (SDWN) also attracted an increasing amount of interest in the recent years. Wireless networks have some distinct characteristics compared to the wired networks due to the wireless channel dynamics. Therefore, network controllers present some extra degrees of freedom, such as taking measurements against interference and noise, or adapting channels according to the radio spectrum occupation. These specific characteristics bring about more challenges to wireless SDNs. Currently, SDWN implementations are mainly using customized firmware, such as OpenWRT, running on an embedded application processor in commercial WiFi chips, and restricted to layers above lower Media Access Control. This limitation comes from the fact that radio hardware usually require specific drivers, which have a proprietary implementation by various chipset vendors. Hence, it is difficult, if not impossible, to achieve virtualization on the radio hardware. However, this status has been changing as Software-Defined Radio (SDR) systems open up the entire radio communication stack to radio hobbyists and researchers. The bridge between SDR and SDN will make it possible to bring the softwarization and virtualization of wireless networks down to the physical layer, which will unlock the full potential of SDWN. This paper investigates the necessity and feasibility of extending the virtualization of wireless networks towards the radio hardware. A SDR architecture is presented for radio hardware virtualization in order to facilitate SDWN design and experimentation. We do believe that by adopting the virtualization-oriented hardware accelerator design presented here, an all-layer end-to-end high performance SDWN can be achieved

Toward Open Integrated Access and Backhaul with O-RAN

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 publiclyavailable 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

FPGA-Based Testbed for Synchronization on Ethernet Fronthaul with Phase Noise Measurements

Cloud radio access network (C-RAN) is a recent trend of RAN architecture positioned to help the operators to address challenges of new wireless services, such as emerging 4G and 5G mobile networks. C-RAN uses baseband processing units in a central server which connects to the radio front-ends at cell sites via the so-called fronthaul network. The fronthaul infrastructure is currently provided by CPRI (Common Public Radio Interface) and OBSAI (Open Basestation Architecture Initiative) industry standards which use dedicated optical links with high deployment costs. An alternative is to use Ethernet technology aiming to reuse of network infrastructure available in many commercial buildings. However, in contrast to the traditional synchronous fronthaul, Ethernet suffers with packet delay variation (PDV) and challenging synchronization recovery. This work presents a complete and flexible testbed to evaluate Ethernet-based fronthaul. The system is validated via extensive measurements that show the effects of synchronization procedures and network impairments on regenerated clock phase noise

AI Testing Framework for Next-G O-RAN Networks: Requirements, Design, and Research Opportunities

Openness and intelligence are two enabling features to be introduced in next generation wireless networks, e.g. Beyond 5G and 6G, to support service heterogeneity, open hardware, optimal resource utilization, and on-demand service deployment. The open radio access network (O-RAN) is a promising RAN architecture to achieve both openness and intelligence through virtualized network elements and well-defined interfaces. While deploying artificial intelligence (AI) models is becoming easier in O-RAN, one significant challenge that has been long neglected is the comprehensive testing of their performance in realistic environments. This article presents a general automated, distributed and AI-enabled testing framework to test AI models deployed in O-RAN in terms of their decision-making performance, vulnerability and security. This framework adopts a master-actor architecture to manage a number of end devices for distributed testing. More importantly, it leverages AI to automatically and intelligently explore the decision space of AI models in O-RAN. Both software simulation testing and software-defined radio hardware testing are supported, enabling rapid proof of concept research and experimental research on wireless research platforms.Comment: To be published in IEEE Wireless Communications Magazin

A baseband wireless spectrum hypervisor for multiplexing concurrent OFDM signals

The next generation of wireless and mobile networks will have to handle a significant increase in traffic load compared to the current ones. This situation calls for novel ways to increase the spectral efficiency. Therefore, in this paper, we propose a wireless spectrum hypervisor architecture that abstracts a radio frequency (RF) front-end into a configurable number of virtual RF front ends. The proposed architecture has the ability to enable flexible spectrum access in existing wireless and mobile networks, which is a challenging task due to the limited spectrum programmability, i.e., the capability a system has to change the spectral properties of a given signal to fit an arbitrary frequency allocation. The proposed architecture is a non-intrusive and highly optimized wireless hypervisor that multiplexes the signals of several different and concurrent multi-carrier-based radio access technologies with numerologies that are multiple integers of one another, which are also referred in our work as radio access technologies with correlated numerology. For example, the proposed architecture can multiplex the signals of several Wi-Fi access points, several LTE base stations, several WiMAX base stations, etc. As it able to multiplex the signals of radio access technologies with correlated numerology, it can, for instance, multiplex the signals of LTE, 5G-NR and NB-IoT base stations. It abstracts a radio frequency front-end into a configurable number of virtual RF front ends, making it possible for such different technologies to share the same RF front-end and consequently reduce the costs and increasing the spectral efficiency by employing densification, once several networks share the same infrastructure or by dynamically accessing free chunks of spectrum. Therefore, the main goal of the proposed approach is to improve spectral efficiency by efficiently using vacant gaps in congested spectrum bandwidths or adopting network densification through infrastructure sharing. We demonstrate mathematically how our proposed approach works and present several simulation results proving its functionality and efficiency. Additionally, we designed and implemented an open-source and free proof of concept prototype of the proposed architecture, which can be used by researchers and developers to run experiments or extend the concept to other applications. We present several experimental results used to validate the proposed prototype. We demonstrate that the prototype can easily handle up to 12 concurrent physical layers