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Abstract The development of quantum computers poses a risk to the cryptographic algorithms utilized by current public key infrastructure (PKI). High performance computing (HPC), inter- and intra-datacenter communications, and governmental communications are particularly vulnerable to security attacks by quantum computers. In response, there are on-going efforts on implementing post-quantum cryptography (PQC) despite the considerable overhead involved in processing PQC encrypted data packets in comparison with their classical counterparts. This work aims to help with the transition to quantum resistant cryptographic schemes by means of providing a thorough experimental performance comparison of the four algorithms selected by the National Institute of Standards and Technology (NIST) for standardization when implemented in a data processing unit (DPU). The experiments are conducted at line-rate, demonstrating for the first time operation at almost 100 Gbit/s and hence suitability for high-capacity data center environments.

Flexi-grid technology has revolutionized optical networking by enabling Elastic Optical Networks (EONs) that offer greater flexibility and dynamism compared to traditional fixed-grid systems. As data traffic continues to grow exponentially, the need for efficient and scalable solutions to the routing and spectrum assignment (RSA) problem in EONs becomes increasingly critical. The RSA problem, being NP-Hard, requires solutions that can simultaneously address both spatial routing and spectrum allocation. This paper proposes a novel quantum-based approach to solving the RSA problem. By formulating the problem as a Quadratic Unconstrained Binary Optimization (QUBO) model, we employ the Quantum Approximate Optimization Algorithm (QAOA) to effectively solve it. Our approach is specifically designed to minimize end-to-end delay while satisfying the continuity and contiguity constraints of frequency slots. Simulations conducted using the Qiskit framework and IBM-QASM simulator validate the effectiveness of our method. We applied the QAOA-based RSA approach to small network topology, where the number of nodes and frequency slots was constrained by the limited qubit count on current quantum simulator. In this small network, the algorithm successfully converged to an optimal solution in less than 30 iterations, with a total runtime of approximately 10.7 s with an accuracy of 78.8%. Additionally, we conducted a comparative analysis between QAOA, integer linear programming, and deep reinforcement learning methods to evaluate the performance of the quantum-based approach relative to classical techniques. This work lays the foundation for future exploration of quantum computing in solving large-scale RSA problems in EONs, with the prospect of achieving quantum advantage as quantum technology continues to advance.

In the near future, commercially accessible quantum computers are anticipated to revolutionize the world as we know it. These advanced machines are predicted to render traditional cryptographic security measures, deeply ingrained in contemporary communication, obsolete. While symmetric cryptography methods like AES can withstand quantum assaults if key sizes are doubled compared to current standards, asymmetric cryptographic techniques, such as RSA, are vulnerable to compromise. Consequently, there is a pressing need to transition towards post-quantum cryptography (PQC) principles in order to safeguard our privacy effectively. A challenge is to include PQC into existing protocols and thus into the existing communication structure. In this work, we report on the first experimental IPsec tunnel secured by the PQC algorithms Falcon, Dilithium, and Kyber. We deploy our IPsec tunnel in two scenarios. The first scenario represents a high-performance data center environment where many machines are interconnected via high-speed networks. We achieve an IPsec tunnel with an AES-256 GCM encrypted east–west throughput of 100 Gbit/s line rate. The second scenario shows an IPsec tunnel between a wireless NVIDIA Jetson and the cloud that achieves a 0.486 Gbit/s AES-256 GCM encrypted north–south throughput. This case represents a mobile device that communicates securely with applications running in the cloud.

Abstract Adaptive analog beamforming is a key technology to enable spatial control of millimeter-wave wireless signals radiated from phased array antennas (PAAs) which is essential to maximize the capacity of future mobile networks and to ensure efficient usage of scarce spectrum. Intermediate frequency-over-fiber (IFoF), on the other hand, is a promising technology for the millimeter-wave (mm-wave) mobile fronthaul due to its low complexity, high optical spectral efficiency, and low latency. The combination of IFoF and PAA is key to implement mm-wave mobile communications in a scalable, centralized, efficient, and reliable manner. This work presents, for the first time to the best of the authors’ knowledge, an extensive outdoor measurement campaign where an experimental IFoF mm-wave wireless setup is evaluated by using PAAs with adaptive beamforming on the transmitter and receiver sides. The configuration of the experimental setup is according to 5G standards, transmitting signals wirelessly at 27 GHz central frequency in the n258 band. The employed PAAs are composed of 8-by-8 patch antenna arrays, allowing beam steering in the azimuth and elevation angles. Furthermore, different end-user locations, antenna configurations, and wireless scenarios are tested in the outdoor experiment, showing excellent EVM performance and achieving 64-QAM transmission over up to 165.5 m at up to 1.88 Gbit/s. The experimental results enable optimization of the experimental setup for different scenarios and prove the system’s reliability in different wireless conditions. In addition, the results of this work prove the viability and potential of IFoF combined with PAA to be part of the future 5G/6G structure.

The sixth generation (6G) of mobile networks will adopt on-demand self-reconfiguration to fulfill simultaneously stringent key performance indicators and overall optimization of usage of network resources. Such dynamic and flexible network management is made possible by Software Defined Networking (SDN) with a global view of the network, centralized control, and adaptable forwarding rules. Because of the complexity of 6G networks, Artificial Intelligence and its integration with SDN and Quantum Computing are considered prospective solutions to hard problems such as optimized routing in highly dynamic and complex networks. The main contribution of this survey is to present an in-depth study and analysis of recent research on the application of Reinforcement Learning (RL), Deep Reinforcement Learning (DRL), and Quantum Machine Learning (QML) techniques to address SDN routing challenges in 6G networks. Furthermore, the paper identifies and discusses open research questions in this domain. In summary, we conclude that there is a significant shift toward employing RL/DRL-based routing strategies in SDN networks, particularly over the past 3 years. Moreover, there is a huge interest in integrating QML techniques to tackle the complexity of routing in 6G networks. However, considerable work remains to be done in both approaches in order to accomplish thorough comparisons and synergies among various approaches and conduct meaningful evaluations using open datasets and different topologies.

In this paper, we propose a novel hybrid network solution using optical code-division multiple-access and free-space optics (OCDMA-FSO) to support multiple data rates and quality-of-service according to user requirements. The proposed OCDMA-FSO network classifies users into diverse classes based on their requirements and allows for signal transmission in a fully asynchronous manner. The new hybrid network employs 2-D OCDMA codes as well as a variable aperture FSO receiver together with an equal gain combining (EGC) technique. We derive completely new analytical formalisms to evaluate the network performance in terms of average bit error rate (ABER), outage probability, effective data rate during outages, and ergodic capacity. The derived ABER expressions are validated via Monte-Carlo simulations. These new analytical formalisms are derived considering several atmospheric turbulence conditions such as uncorrelated, totally correlated, and partially correlated turbulence. To model this atmospheric turbulence, we derive the gamma-gamma (GG) distribution, which allows us to consider both the scintillation effect and the EGC technique. Finally, we carry out a comprehensive performance evaluation of the proposed hybrid network. Analytical results show that as the number of FSO receiver apertures increases, there is an improvement in overall performance levels. However, the ergodic capacity exhibits minimal improvement even as the number of FSO receiver apertures increases, regardless of the user requirements and turbulence conditions. The proposed network is a potential solution for scenarios that demand flexibility in bandwidth and data rate allocation.

Abstract The sixth generation (6G) mobile systems will create new markets, services, and industries making possible a plethora of new opportunities and solutions. Commercially successful rollouts will involve scaling enabling technologies, such as cloud radio access networks, virtualization, and artificial intelligence. This paper addresses the principal technologies in the transition towards next generation mobile networks. The convergence of 6G key-performance indicators along with evaluation methodologies and use cases are also addressed. Free-space optics, Terahertz systems, photonic integrated circuits, softwarization, massive multiple-input multiple-output signaling, and multi-core fibers, are among the technologies identified and discussed. Finally, some of these technologies are showcased in an experimental demonstration of a mobile fronthaul system based on millimeter 5G NR OFDM signaling compliant with 3GPP Rel. 15. The signals are generated by a bespoke 5G baseband unit and transmitted through both a 10 km prototype multi-core fiber and 4 m wireless V-band link using a pair of directional 60 GHz antennas with 10° beamwidth. Results shown that the 5G and beyond fronthaul system can successfully transmit signals with both wide bandwidth (up to 800 MHz) and fully centralized signal processing. As a result, this system can support large capacity and accommodate several simultaneous users as a key candidate for next generation mobile networks. Thus, these technologies will be needed for fully integrated, heterogeneous solutions to benefit from hardware commoditization and softwarization. They will ensure the ultimate user experience, while also anticipating the quality-of-service demands that future applications and services will put on 6G networks.

Abstract This article presents an experimental demonstration of a high-capacity millimeter-wave 5G NR signal transmission with analog radio-over-fiber (ARoF) fronthaul over multi-core fiber and full real-time processing. The demonstration validates the core of the blueSPACE fronthaul architecture which combines ARoF fronthaul with space division multiplexing in the optical distribution network to alleviate the fronthaul capacity bottleneck and maintain a centralized radio access network with fully centralized signal processing. The introduction of optical beamforming in the blueSPACE architecture brings true multi-beam transmission and enables full spatial control over the RF signal. The proposed ARoF architecture features a transmitter that generates the ARoF signal and an optical signal carrying a reference local oscillator employed for downconversion at the remote unit from a single RF reference at the central office. A space division multiplexing based radio access network with multi-core fibre allows parallel transport of the uplink ARoF signal and reference local oscillator at the same wavelength over separate cores. A complete description of the real-time signal processing and experimental setup is provided and system performance is evaluated. Transmission of an 800 MHz wide extended 5G NR fronthaul signal over a 7-core fibre is shown with full real-time signal processing, achieving 1.4 Gbit/s with a bit error rate $$

In this paper we report the implementation and experimental evaluation of a proposed hybrid communication ecosystem for CCAM applications such as cooperative adaptive cruise control (CACC) and smart intersections. Three wireless technologies have been suggested for communications between vehicles and intelligent traffic lights and are evaluated in this work: ITS-G5 based on IEEE 802.11p and LTE sidelink with PC5 air interface for direct short range links, and regular mobile LTE with LTE Uu air interface for long range or indirect links. The applications used are independent of the communication channel, to enable a comparison on the application level of the different communication technologies. Field experiments were carried out with two CACC-equipped vehicles and three intelligent traffic lights in two field test locations under ideal, i.e., no-traffic, conditions and with real traffic. Experimental results related to CACC show that the best performance in terms of latency is achieved by the ITS-G5 system, while LTE PC5 and LTE Uu links show a penalty of 20 and 50 ms respectively. However, experimental results show that all three communication technologies were still able to guarantee string stable performance of the vehicle platoon. Regarding the smart intersections, an analysis based on field measurements and comparison between long- and short-range solutions is proposed; the analysis includes the impact of each channel on the applications such as speed advisory and green light prediction. The reported experimental evaluation shows the potential of current mobile technologies for CCAM use cases and highlights the way for further CCAM applications based on 5G and beyond mobile networks.

Despite the progress in the development of automated vehicles in the last decade, reaching the level of reliability required at large-scale deployment at an economical price and combined with safety requirements is still a long road ahead. In certain use cases, such as automated shuttles and taxis, where there is no longer even a steering wheel and pedals required, remote driving could be implemented to bridge this gap; a remote operator can take control of the vehicle in situations where it is too difficult for an automated system to determine the next actions. In logistics, it could even be implemented to solve already more pressing issues such as shortage of truck drivers, by providing more flexible working conditions and less standstill time of the truck. An important aspect of remote driving is the connection between the remote station and the vehicle. With the current roll-out of 5G mobile technology in many countries throughout the world, the implementation of remote driving comes closer to large-scale deployment. 5G could be a potential game-changer in the deployment of this technology. In this work, we examine the remote driving application and network-level performance of remote driving on a recently deployed sub-6-GHz commercial 5G stand-alone (SA) mobile network. It evaluates the influence of the 5G architecture, such as mobile edge computing (MEC) integration, local breakout, and latency on the application performance of remote driving. We describe the design, development (based on Hardware-in-the-Loop simulations), and performance evaluation of a remote driving solution, tested on both 5G and 4G mobile SA networks using two different vehicles and two different remote stations. Two test cases have been defined to evaluate the application and network performance and are evaluated based on position accuracy, relative reaction times, and distance perception. Results show the performance of the network to be sufficient for remote driving applications at relatively low speeds (

Fifth-generation (5G) and beyond networks are envisioned to serve multiple emerging applications having diverse and strict quality of service (QoS) requirements. To meet ultra-reliable and low latency communication, real-time data processing and massive device connectivity demands of the new services, network slicing and edge computing, are envisioned as key enabling technologies. Network slicing will prioritize virtualized and dedicated logical networks over common physical infrastructure and encourage flexible and scalable networks. On the other hand, edge computing offers storage and computational resources at the edge of networks, hence providing real-time, high-bandwidth, low-latency access to radio network resources. As the integration of two technologies delivers network capabilities more efficiently and effectively, this paper provides a comprehensive study on edge-enabled network slicing frameworks and potential solutions with example use cases. In addition, this article further elaborated on the application of machine learning in edge-sliced networks and discussed some recent works as well as example deployment scenarios. Furthermore, to reveal the benefits of these systems further, a novel framework based on reinforcement learning for controller synchronization in distributed edge sliced networks is proposed.

This paper studied the constraint mechanism for power device design based on perovskite quantum dots pumped by an electron beam. Combined with device designing, an experimental system of self-saturation luminescence and aging failure was designed for CsPbBr3 films. On this basis, we further completed the self-saturation luminescence and aging failure experiment and constructed a model of self-saturation luminescence and aging failure for CsPbBr3 device designing. Three constraints were proposed after analyzing and discussing the experimental data. Firstly, too high of a pumping current density makes it difficult to effectively promote the enhancement of luminescence efficiency. Secondly, radiation decomposition and aging failure of CsPbBr3 films are mainly related to the polarized degree of CsPbBr3 nanocrystals. Thirdly, by increasing the pumping electric field, the pumping energy can be effectively and widely delivered to the three-dimensional quantum dots film layer space, and there is a nonlinear relationship between the attenuation of the pumping energy density and the increment of the pumping electric field, which will effectively avoid the local high-energy density of instantaneous optical pumping.

Three convergent processes are likely to shape the future of the internet beyond-5G: The convergence of optical and millimeter wave radio networks to boost mobile internet capacity, the convergence of machine learning solutions and communication technologies, and the convergence of virtualized and programmable network management mechanisms towards fully integrated autonomic network resource management. The integration of network virtualization technologies creates the incentive to customize and dynamically manage the resources of a network, making network functions, and storage capabilities at the edge key resources similar to the available bandwidth in network communication channels. Aiming to understand the relationship between resource management, virtualization, and the dense 5G access and fronthaul with an emphasis on converged radio and optical communications, this article presents a review of how resource management solutions have dealt with optimizing millimeter wave radio and optical resources from an autonomic network management perspective. A research agenda is also proposed by identifying current state-of-the-art solutions and the need to shift all the convergent issues towards building an advanced resource management mechanism for beyond-5G.

This article presents the experimental demonstration of synchronization of two integrated semiconductor distributed Bragg reflector lasers, fabricated with a generic multiproject wafer platform, by means of injection locking. Substantial linewidth reduction and frequency stabilization of the lasers were shown during locking of the lasers to an optical frequency comb. Phase noise was measured for different injected powers and different laser cavities. For a generation of millimeter-wave signals up to 80 GHz, two lasers were simultaneously locked to the comb. Fine-tuning was performed by tuning the repetition rate of the comb and coarse-tuning was carried out by switching to another comb line. A suppression ratio of 37 dB was achieved for unwanted comb lines. The achieved signal purity, phase noise, and suppression of unwanted components demonstrate the viability of injection locking for the generation of high-quality signals at sub-THz and THz frequencies and with substantial tunability.

Abstract A new and generalized statistical model, called Málaga or simply ℳ ${\mathcal {M}}$ distribution, has been derived recently to characterize the irradiance fluctuations of an unbounded optical wavefront propagating through a turbulent medium under all irradiance fluctuation conditions. The aforementioned model extends and unifies in a simple analytical closed-form expression most of the proposed statistical models for free-space optical (FSO) communications widely employed until now in the scientific literature. Based on that ℳ ${\mathcal {M}}$ model, we have studied some important features associated to its fade statistics and expressed in terms of the expected number of fades per second. The derived expressions become relevant for many aspects in a FSO system, especially those ones related to determine the optimum threshold in a receiver based on a direct detection scheme employing a fixed detection threshold.

In this paper, new analytical formalisms to evaluate the packet throughput of multiservice multirate slotted ALOHA optical code-division multiple-access (OCDMA) networks are proposed. The proposed formalisms can be successfully applied to 1-D and 2-D OCDMA networks with any number of user classes in the system. The bit error rate (BER) and packet correct probability expressions are derived, considering the multiple-access interference as binomially distributed. Packet throughput expressions, on the other hand, are derived considering Poisson, binomial, and Markov chain approaches for the composite packet arrivals distributions, with the latter defined as benchmark. A throughput performance evaluation is carried out for two distinct user code sequences separately, namely, 1-D and 2-D multiweight multilength optical orthogonal code (MWML-OOC). Numerical results show that the Poisson approach underestimates the throughput performance in unacceptable levels and incorrectly predicts the number of successfully received packets for most offered load values even in favorable conditions, such as for the 2-D MWML-OOC OCDMA network with a considerably large number of simultaneous users. On the other hand, the binomial approach proved to be more straightforward, computationally more efficient, and just as accurate as the Markov chain approach.

5G mobile networks aim to support a large variety of services with different and demanding requirements. To achieve this, analog radio over fiber (ARoF) fronthaul along with millimeter-wave (mmWave) cells is a strong candidate to be part of the 5G architecture. Very high throughput can be achieved by using mmWave signals due to the large available bandwidths, which combines well with the advantages of employing ARoF technology. Nevertheless, combined mmWave and ARoF systems face a particular challenge as the impacts of both channels—such as high free-space path loss, phase noise, chromatic dispersion, and other degrading effects—affect the signal without the possibility for intermediate restoration. The selection of the signal waveforms plays an important role in reducing these defects. In addition, waveforms are one of the keys in the physical layer available towards satisfying the requirements for 5G and beyond. In this manuscript, several key requirements are presented to determine the merit of candidate waveform formats to fulfill the 5G requirements in the mmWave ARoF architecture. An overview of the different suitable waveforms for this architecture is provided, discussing their advantages and disadvantages. Moreover, a comprehensive comparison in terms of different requirements is also presented in this paper.

In this paper, we demonstrate a photonic up-converted 25 Gbit/s fiber-wireless quadrature phase shift-keying (QPSK) data transmission link at the W-band (75-110 GHz). By launching two free-running lasers spaced at 87.5 GHz into a standard single-mode fiber (SSMF) at the central office, a W-band radio-over-fiber (RoF) signal is generated and distributed to the remote antenna unit (RAU). One laser carries 12.5 Gbaud optical baseband QPSK data, and the other acts as a carrier frequency generating laser. The two signals are heterodyne mixed at a photodetector in the RAU, and the baseband QPSK signal is transparently up-converted to the W-band. After the wireless transmission, the received signal is first down-converted to an intermediate frequency (IF) at 13.5 GHz at an electrical balanced mixer before being sampled and converted to the digital domain. A digital-signal-processing (DSP)-based receiver is employed for offline digital down-conversion and signal demodulation. We successfully demonstrate a 25 Gbit/s QPSK wireless data transmission link over a 22.8 km SSMF plus up to 2.13 m air distance with a bit-error-rate performance below the 2 × 10-3 forward error correction (FEC) limit. The proposed system may have the potential for the integration of the in-building wireless networks with the fiber access networks, e.g., fiber-to-the-building (FTTB).

In this paper, a novel and simple scheme to realize flexible access for gigabit wireline and impulse radio ultrawideband (IR-UWB) wireless services is proposed. The UWB signals are generated by multi-carrier upconverting and reshaping the baseband signals. The proposed system was experimentally demonstrated with the performances of 2.0-Gb/s data in both baseband and UWB formats after 46-km single mode fiber transmission and further 0.5-m wireless for UWB data. The flexibility of the system is confirmed by investigating the system performance at different data rates including 1.0 and 1.6 Gb/s. Optical wavelength independency and data-rate variability of UWB signal generation makes the system attractive for potential wireline and wireless applications in existing wavelength division multiplexing (WDM)-passive optical network (PON) systems.

Space division multiplexing (SDM) is a promising technology that aims to overcome the capacity crunch of optical communications. In this paper, we introduce the multiple-input multiple-output (MIMO) Stokes Space Algorithm (SSA) implemented in frequency domain, a novel equalization technique for space division multiplexing (SDM). Although different papers have been published about the SSA and its MIMO implementation, we provide for the first time an analysis of the of the convergence speed and frequency offset of the SSA compared to the least mean square (LMS). SSA algorithm can deal with higher frequency offsets and linewidths than LMS, being suitable for optical communications with higher phase noise. SSA does not need pre-compensation of frequency offset, which can be compensated after equalization without penalties. On the other hand, due to reduced convergence speed, SSA requires longer training sequences than LMS.

We discuss the implications of using monolithically integrated semiconductor lasers in high capacity optical coherent links suitable for metro applications, where the integration capabilities of semiconductor lasers make them an attractive candidate to reduce transceiver cost. By investigating semiconductor laser frequency noise profiles we show that carrier induced frequency noise plays an important role in system performance. We point out that, when such lasers are employed, the commonly used laser linewidth fails to estimate system performance, and we propose an alternative figure of merit that we name “Effective Linewidth”. We derive this figure of merit analytically, explore it by numerical simulations and experimentally validate our results by transmitting a 28 Gbaud DP-16QAM over an optical link. Our investigations cover the use of semiconductor lasers both in the transmitter side and as a local oscillator at the receiver. The obtained results show that our proposed “effective linewidth” is easy to measure and accounts for frequency noise more accurately, and hence the penalties associated to phase noise in the received signal.

We propose and experimentally demonstrate a fiber-wireless transmission system for optimized delivery of 60-GHz radio frequency (RF) signals through picocell mobile backhaul connections. We identify advantages of 60-GHz links for utilization in short-range mobile backhaul through feasibility analysis and comparison with an alternative E-band (60-90 GHz) technology. The 60-GHz fiber-wireless-fiber setup is then introduced: two spans of up to 20 km of optical fiber are deployed and bridged by up to 4 m of wireless distance. The 60-GHz radio-over-fiber technology is utilized in the first span of fiber transmission. The system is simplified and tailored for delivery of on-off keying data signals by employing a single module for lightwave generation and modulation combined with a simplified RF downconversion technique by envelope detection. Data signals of 1.25 Gb/s are transmitted, and a bit-error-rate performance below the 7% overhead forward-error-correction limit is achieved for a range of potential fiber deployment scenarios. A spurious free dynamic range of 73 dB-Hz2/3 is attained for a frequency-doubling photonic RF upconversion technique. The power budget margin that is required to extend the wireless transmission distance from 4 m to a few hundred meters has been taken into account in the setup design, and the techniques to extend the wireless distance are analyzed.