OpenAirInterface Platform Research Articles

Radio Frequency Fingerprint Identification for 5G Mobile Devices Using DCTF and Deep Learning.

The fifth-generation (5G) mobile cellular network is vulnerable to various security threats. Radio frequency fingerprint (RFF) identification is an emerging physical layer authentication technique which can be used to detect spoofing and distributed denial of service attacks. In this paper, the performance of RFF identification is studied for 5G mobile phones. The differential constellation trace figure (DCTF) is extracted from the physical random access channel (PRACH) preamble. When the database of all 64 PRACH preambles is available at the gNodeB (gNB), an index-based DCTF identification scheme is proposed, and the classification accuracy reaches 92.78% with a signal-to-noise ratio of 25 dB. Moreover, due to the randomness in the selection of preamble sequences in the random access procedure, when only a portion of the preamble sequences can be trained, a group-based DCTF identification scheme is proposed. The preamble sequences generated from the same root value are grouped together, and the untrained sequences can be identified based on the trained sequences within the same group. The classification accuracy of the group-based scheme is 89.59%. An experimental system has been set up using six 5G mobile phones of three models. The 5G gNB is implemented on the OpenAirInterface platform.

A study on mobile telecommunication systems using OpenAirInterface platform

Significant progress has been made in deploying 5G mobile networks in the last few years, providing rapid connectivity and low-latency communications. This study thoroughly analyzes the deployment of 5G networks utilizing the Open Air Interface (OAI), a free and open-source wireless communication technology. The survey gives a general overview of OAI's various fields and applications. It then looks at numerous uses and industries where OAI-based networks for 5G have been effectively implemented. The paper includes in-depth discussions of OAI's technical features and information on how it supports creating software-defined radio (SDR) platforms for 5G networks. It emphasizes OAI's versatility and flexibility, allowing researchers and developers to test various network setups and protocols. The survey's results show how OAI is becoming increasingly crucial to designing and rolling out 5G networks in various sectors. Researchers and professionals can investigate fresh applications and services that make the most of 5G technology by utilizing the capabilities of OAI. The taxonomy is designed and developed by categorizing the existing proposed solutions using OAI to easily deploy mobile telecommunication networks cost-effectively and flexibly to support various features and functionalities. Each category in the developed taxonomy is discussed and compared regarding multiple parameters.

Real-time Coordinated Scheduling for Cloud Radio Access Networks in a Software-only Environment using the OpenAirInterface Platform

The objective of this paper is to extend into the OpenAirInterface platform the Coordinated Scheduling (CS) technique to allocate resource blocks among User Equipment (UE) in a wisely way and to control the energy efficiency, the throughput, and the inter-cell interference for Cloud Radio Access Networks (C-RANs). It is achieved by modifying the OpenAirInterface scheduler code, increasing the Remote Radio Unit (RRU) scalability, and employing some component carriers of the Radio Cloud Center (RCC), each one them with one or more UEs. The hardware utilized is composed of general-purpose processors and fast Ethernet transport ports, and the software is recent frequency-domain methodologies in a software-only environment where the use of radio units are not required. However, the USRP B200 mini-i radio unit and the UE (Samsung Galaxy S8) were considered only for validation purposes. The emulations using frequency-domain methodologies, compatible with fourth and fifth-generation cellular systems, allowed real-time emulations and reduced 10-fold the multipath channel’s signal processing complexity compared to time-domain methodologies. The results show we can emulate a real-time static coordinated scheduling proof-of-concept for one C-RAN composed of one RCC, three RRUs, and three UEs. In the end, it is evaluated the reproducibility and the scalability of synthetic networks composed of one RRU and at least one UE, without using software-defined radio units, reducing prototyping uncertainties of the physical hardware and the total price of the experiment.

Zero On-Site Testing Strategies for Wireless TCMS

TCMS is a key element for smart railway operation and maintenance. In order to reduce costs and train weight, EU-funded projects are working on the development of wireless TCMS. The data exchanges between trains and ground will be based on wireless technology such as WiFi or Long Term Evolution. First prototypes are available at the European level. To facilitate the testing of the TCMS interface to ground systems, it is important to develop tools able to represent railway environments without going on tracks (zero on-site testing). In this context, we present two strategies to simulate and emulate a complete wireless network (including the core network), based on the Riverbed Modeler and OpenAirInterface platform, able to take into account various train-to-ground contexts (environment, communication and railway networks load). This work considers LTE technology but can be transposed to other types of technology if representative system models are available. As a proof of concept of the test environment, we present results in terms of delay and delivery rates considering TCMS traffic and various railway scenarios such as train speed and wireless network load.

Autonomous Self-Backhauled LTE Mesh Network With QoS Guarantee

Public safety communication systems are currently evolving due to emergence of long term evolution (LTE) as a mature solution to replace the legacy ones while providing new services. However, LTE is initially designed for commercial cellular network and needs to be furthermore evolved to tackle the substantial requirements of public safety use cases. For instance, opportunistic deployments require modifications to enable the autonomous operation and meshing of moving base stations while satisfying heterogeneous frequency band availability. In this article, we present a novel radio access network infrastructure architecture that enables multi-hop LTE mesh networking for nomadic and autonomous base stations via in-band self-backhauling. Furthermore, we investigate the coordination and orchestration functionality within the proposed architecture and propose a hierarchical resource scheduling algorithm in order to efficiently meet quality of service (QoS) requirements for real-time traffic while maximizing the throughput for elastic flows. To demonstrate the feasibility and reliability of our proposed architecture, we implement the corresponding self-backhauling air-interface based on OpenAirInterface platform and compare it with the legacy LTE air-interface. Finally, we evaluate the efficiency and adaptability of our proposed resource scheduling algorithm in various network topology and heterogeneous traffic flows with QoS requirements.

Design and implementation of spatial interweave LTE-TDD cognitive radio communication on an experimental platform

Cognitive radio, which enables smart use of wireless resources, is a key ingredient to achieve high spectral efficiency. LTE, the latest evolution of cellular standards, is widely adopted and also targets high spectral efficiency. Hence, to enable wide adoption of cognitive radio, using LTE as the physical layer is a natural choice. Targeting a real-time implementation of LTE-based cognitive radio, we focus on spatial interweave cognitive radio, in which a secondary user uses an antenna array to perform null-beamforming in the primary user's direction, hence reusing the spectrum spatially. To allow this, without any help from the primary system, we use the time-division duplex mode and take advantage of the channel reciprocity. However, this reciprocity is jeopardized by the mismatch between the RF front-ends. Hence, we design a calibration protocol to restore it. A key contribution is that this cognitive system calibration does not require cooperation from the primary user. The whole system is implemented and evaluated on EURECOM's experimental OpenAirInterface platform. Performance results are presented, showing the feasibility of spatial interweave cognitive radio on a real-time platform.

Design and Implementation of a Single-Frequency Mesh Network Using OpenAirInterface

OpenAirInterface is an experimental open-source real-time hardware and software platform for experimentation in wireless communications and signal processing. With the help of OpenAirInterface, researchers can demonstrate novel ideas quickly and verify them in a realistic environment. Its current implementation provides a full open-source software modem comprising physical and link layer functionalities for cellular and mesh network topologies. The physical (PHY) layer of the platform targets fourth generation wireless networks and thus uses orthogonal frequency division multiple access (OFDMA) together with multiple-input multiple-output (MIMO) techniques. The current hardware supports 5 MHz bandwidth and two transmit/receive antennas. The media access (MAC) layer of the platform supports an abundant two-way signaling for enabling collaboration, scheduling protocols, as well as traffic and channel measurements. In this paper, we focus on the mesh topology and show how to implement a single-frequency mesh network with OpenAirInterface. The key ingredients to enable such a network are a dual-stream MIMO receiver structure and a distributed network synchronization algorithm. We show how to implement these two algorithms in real-time on the OpenAirInterface platform. Further more, we provide results from field trials and compare them to the simulation results.