Next-generation Communication Networks Research Articles

Interactive Artificial Intelligence Meets Game Theory in Next-Generation Communication Networks

Next-generation communication networks can provide high capacity, low latency, and massive connections; however, they introduce novel challenges of management complexity, and traditional mathematical methods cannot well characterize the rational behavior of users. In this article, we pay attention to the methods of artificial intelligence (AI) and game theory. We first review the applications of machine learning (ML) and game theory models in wireless communications and summarize their advantages and disadvantages. After surveying the state of the art, in this article we propose a novel framework combining ML and game theory, which explores and exploits the benefits of the two disciplines. Finally, we apply our novel framework to solve the network selection problem in a 5G ultra-dense and heterogeneous network. Simulation results confirm the advantage of our presented framework on reducing the average delay of users.

UAV-Assisted Multi-path Parallel Routing for mmWave-Based Wireless Networks

The Millimeter Wave (mmWave) spectrum band, with its high bandwidth, will significantly satisfy the need for high data-demand of the next-generation communication networks. However, transmission over the mmWave band suffers from a short communication range due to its high frequency. Such short-range communication can dramatically affect the network connectivity in mesh-based networks, leading to excessive packet loss. To improve the network connectivity and thus the throughput, Unmanned Aerial Vehicles (UAVs)/drones can be utilized as relays. Along with UAVs, multi-path routing is needed to ensure better network reliability through different routes. In this paper, we propose maximizing mmWave-based mesh network connectivity via optimally deploying a number of UAVs/drones and enabling multiple parallel paths at the upper network layers. We model the optimization problem for minimizing end-to-end delay with a minimum number of drones, we further perform a delay analysis for the received queues and obtain the link layer end-to-end delay. The evaluation is first performed through MATLAB and then verified using a realistic scenario in the NS-3 simulator by assuming an IEEE 802.11ad-based wireless mesh network. The results show that the proposed UAV-assisted schemes achieve higher throughput and shorter delay compared to baselines scenario with no deployment of UAVs or single transmissions.

Special issue on “Ubiquitous clouds and communication networks”

The recent technological enhancement in the communication and computing paradigm paves way for the development of next-generation ubiquitous IoT systems and applications. Moreover, the 5G and technology beyond are making huge differences on both computing and communication services. As the connectivity increases, the sheer volume of things connected through wireless mode for various real-time applications will not be efficiently handled by the existing technologies. The next-generation ubiquitous clouds and communication networks will gain the ability to leverage on-demand access through internet to utilize a shared pool of configurable communication resources. The ubiquitous cloud and communication platforms are widely used as services for data management, processing, and storage, whereas it can also enhance its reliability, flexibility, and efficiency by reducing the complexities. The research papers for this special issue were selected from among all the accepted papers by the special issue guest editors Dr. V. Suma, Dr. Ram Palanisamy, Dr. Xavier Fernando, and Dr. Robert Bestak based on the scope and objective of the journal. We appreciate the willingness of the authors to help in organizing this special issue. This special issue contains a collection state-of-the-art research articles with the objective to share research ideas and techniques in the areas of ubiquitous clouds and communication with the underlying technologies and applications, which include internet architecture and protocol, data analysis, information management, and its security. In particular, the articles included in the special issue analyzes the emerging state-of-the-art research areas like big data, cloud, cyber physical systems, and IoT to develop innovative solutions in order to overcome the existing challenges in computing and communication domains. This remains more essential to comply with the necessities of ubiquitous computing and communication applications. As one of the intended goals, the research articles aim to propose various network optimization algorithms, cloud/edge computing architectures, network routing protocols and task scheduling, self-organized networks, heterogeneous 5G networks, and Artificial Intelligence (AI) frameworks to propose the diverse range of features of reliability, flexibility, security, privacy, trust in ubiquitous clouds, and communication networks. Furthermore, this special issue also examines the significant network theories, formulates significant communication applications, and devises innovative methods to overcome the significant challenges that this research area poses.

Dynamic Resource Pricing and Allocation in Multilayer Satellite Network

The goal of delivering high-quality service has spurred research of 6G satellite communication networks. The limited resource-allocation problem has been addressed by next-generation satellite communication networks, especially multilayer networks with multiple low-Earth-orbit (LEO) and non-low-Earth-orbit (NLEO) satellites. In this study, the resource-allocation problem of a multilayer satellite network consisting of one NLEO and multiple LEO satellites is solved. The NLEO satellite is the authorized user of spectrum resources and the LEO satellites are unauthorized users. The resource allocation and dynamic pricing problems are combined, and a dynamic game-based resource pricing and allocation model is proposed to maximize the market advantage of LEO satellites and reduce interference between LEO and NLEO satellites. In the proposed model, the resource price is formulated as the dynamic state of the LEO satellites, using the resource allocation strategy as the control variable. Based on the proposed dynamic game model, an open-loop Nash equilibrium is analyzed, and an algorithm is proposed for the resource pricing and allocation problem. Numerical simulations validate the model and algorithm.

An Autonomous Transmission Scheme Using Dueling DQN for D2D Communication Networks

In this paper, we investigate device-to-device (D2D) communication networks which are one of the key technologies for next-generation mobile communication networks and many other applications such as unmanned aerial vehicles (UAVs), vehicle-to-vehicle (V2V), and Internet of things (IoT). The overlay D2D communication networks that are considered in our study use dedicated radio resources separate from what cellular networks use and there exists co-channel interference in D2D networks without cross-channel interference between two networks. We propose a new transmission scheme for overlay D2D networks that uses a dueling deep reinforcement learning (DRL) architecture. The DRL is especially effective in environments where actions do not affect subsequent states as in wireless communication networks. The main contribution of this paper is that the proposed architecture is designed to utilize only information that each D2D devices can easily obtain by measuring channels. The proposed scheme thus enables D2D devices to train their own neural networks and to decide autonomously whether to transmit data without any intervention from infrastructures. The performance of the proposed scheme is analyzed in terms of average sum-rates and is compared to three baseline schemes. Simulation results show that the proposed scheme can achieve almost optimal sum-rates with low signal-to-noise (SNR) values without any intervention from infrastructure.

SIMULATION MODELING OF ADAPTIVE ROUTING UNDER EXTERNAL DESTROYING EFFECTS IN NGN NETWORKS

Modern subscribers of infocommunication services require a wide class of different services and applications, implying a wide variety of protocols, technologies and transmission rates. Networks are overloaded in the prevailing situation in the market of infocommunication services: they are overflowing with numerous customer interfaces, network layers and are controlled by too many control systems. High operating costs are pushing operators to look for solutions that simplify the operation, while maintaining the possibility of creating new services and ensuring the stability of existing sources of income from the provision of communication services. The NGN concept is the concept of building next-generation communication networks (Next-generation network), providing an unlimited set of services with flexible settings for their management, personalization, creation of new services through the unification of network solutions. Multiservice network is a communication network that is built in accordance with the NGN concept and provides an unlimited set of infocommunication services (VoIP, Internet, VPN, IPTV, VoD, etc.). An NGN is a packet-switched network suitable for the provision of telecommunication services and for the use of multiple broadband transport technologies with QoS enabled, in which the service-related functions are independent of the applied transport technologies. The main feature of NGN networks is the differentiation between services and transport technologies. This allows to view the network as a logically divided entity. Each layer of the network can evolve independently without affecting other layers. Inter-layer communication is based on open interfaces. The logical separation principle allows the provision of both existing and innovative services access technologies regardless of the used transport. The basic principle of the NGN concept is to separate from each other transfer and switch functions, call control functions and service control functions.

A Multi-Carrier Waveform Design for 5G and beyond Communication Systems

The next generation communication network (NGCN) is expected to provide higher spectral efficiency, low latency, large throughput and massive machine-to-machine type communications. In this regard, the design of the multi-carrier waveform (MCW) is posing a major research problem for the NGCN. To overcome the stated problem, a lot of state-of-the-art work exists that proposes various MCW alternative to the standard orthogonal frequency division multiplexing (OFDM) waveform. It is true that OFDM was used in a number of real-time communication systems of fourth generation (4G) networks. However, their use in the upcoming fifth generation (5G) network is not very feasible. This is because of the strict requirements of 5G communication systems, which also extend beyond 5G systems; hence rendering the use of OFDM infeasible for newer communication standards. To satisfy the requirements of upcoming communication networks, there is a dire need for MCWs with better flexibility. In this regard, a precoding-based MCW has been proposed. The proposed MCW fulfills the requirements of the NGCN in terms of low peak-to-average power ratio (PAPR), high spectral efficiency and throughput. The MCW proposed in this work uses power-domain multiplexing such as non-orthogonal multiple access (NOMA) and phase rotation by using the selective mapping (SLM) and generalized chirp-like (GCL) precoding of the input signal to the universal filtered multi-carriers (UFMC) modulations. Statistical analysis of the PAPR is presented by using the complementary cumulative distribution function (CCDF). The MATLAB® simulations have been carried out to implement the CCDF of PAPR and results show that a PAPR gain of 5.4 dB is obtained when the proposed waveform is compared with the standard NOMA-UFMC waveform at clip rate of 10−3, using 4-QAM.

Design of Interactive Visualizations for Next-Generation Ultra-Large Communication Networks

With the increasing size and complexity of next-generation communication networks, it is critical to utilize interactive visualizations to support the monitoring, planning, and management of networks. Effectively visualizing large-scale networks is difficult with traditional methods because of the high link density and complex node relationships. Given the limited screen space, to assist Internet Service Provider’s (ISP) network planning and management activities, investigating how to present ultra-large-scale network data efficiently is crucial. This paper presents a real-time interactive visualization system that combines the design strategies of progressive disclosure and multiple panels to elegantly visualize the large-scale networks and avoid the information-overload problem. The system also visualizes the configuration of the network elements and provides the network performance information, including the port-level Quality of Service (QoS) metrics. Furthermore, the system enables navigation through the port-level connection and provides different modes for multiple purposes.

Ultra-low loss electro-optical polymer modulator based on D-shaped few-mode fiber using improved M-Z structure

Abstract An electro-optical polymer optical fiber modulator based on D-shaped few-mode fiber is proposed and optimized. In the D-shaped few-mode fiber, the electro-optic polymer coated on the few-mode fiber influences the refractive index of LP01 mode and LP02 mode, while LP01 mode is more sensitive. According to that, the mode field distribution has been analyzed and the varying properties of D-shaped FMF covered with electro-optic polymer has been discussed. Its simple cascade and axial alignment design enhances the stability of all-fiber modulators. Using improved M-Z structure with advanced operating point, the electro-optic modulator achieves an insertion loss of less than 2 dB with a modulation depth of 22 dB at 1550 nm. And the length of modulator is 25.69 mm. Moreover, the Vpi is 2.7 V and the optical bandwidth is 6.9 nm, which make the modulator have low power consumption and can be used in next-generation all-optical communication networks.

A monolithic bipolar CMOS electronic–plasmonic high-speed transmitter

To address the challenge of increasing data rates, next-generation optical communication networks will require the co-integration of electronics and photonics. Heterogeneous integration of these technologies has shown promise, but will eventually become bandwidth-limited. Faster monolithic approaches will therefore be needed, but monolithic approaches using complementary metal–oxide–semiconductor (CMOS) electronics and silicon photonics are typically limited by their underlying electronic or photonic technologies. Here, we report a monolithically integrated electro-optical transmitter that can achieve symbol rates beyond 100 GBd. Our approach combines advanced bipolar CMOS with silicon plasmonics, and addresses key challenges in monolithic integration through co-design of the electronic and plasmonic layers, including thermal design, packaging and a nonlinear organic electro-optic material. To illustrate the potential of our technology, we develop two modulator concepts—an ultra-compact plasmonic modulator and a silicon-plasmonic modulator with photonic routing—both directly processed onto the bipolar CMOS electronics. The monolithic integration of electronic and plasmonic technologies can be used to create electro-optic transmitters capable of symbol rates beyond 100 GBd.

Latency-Aware Offloading in Integrated Satellite Terrestrial Networks

Next-generation communication networks are expected to integrate newly-used technologies in a smart way to ensure continuous connectivity in rural areas and to alleviate the traffic load in dense regions. The prospective access network in 6G should hinge on satellite systems to take advantage of their wide coverage and high capacity. However, adopting satellites in 6G could be hindered because of the {additional latency introduced}, which is not tolerable by all traffic types. Therefore, we propose a traffic offloading scheme that integrates both the satellite and terrestrial networks to smartly allocate the traffic between them while satisfying different traffic requirements. Specifically, the proposed scheme offloads the Ultra-Reliable Low Latency Communication (URLLC) traffic to the terrestrial backhaul to satisfy its stringent latency requirement. However, it offloads the enhanced Mobile Broadband (eMBB) traffic to the satellite since eMBB needs high data rates but is not always sensitive to delay. Our scheme is shown to reduce the transmission delay of URLLC packets, decrease the number of dropped eMBB packets, and hence improve the network's availability. Our findings highlight that the inter-working between satellite and terrestrial networks is crucial to mitigate the expected high load on the limited terrestrial capacity.

Resource Optimization for Cognitive Radio Based Device to Device Communication Under an Energy Harvesting Scenario

Device to device (D2D) communication has emerged as a potential candidate for next-generation communication networks to support higher data rates and minimize power consumption. The spectral and energy efficiency of D2D communication can further be improved using cognitive radio (CR) and radio frequency energy harvesting (RF-EH) technologies. Therefore, in this paper, a sum throughput maximization problem for a CR assisted D2D network is modeled considering the RF-EH mechanism. A joint optimization problem is formulated for sum-rate maximization of cellular and D2D users by considering power allocation, channel assignment, user pairing and transmission time ratio allocation. Then, the problem is transformed into a standard convex optimization problem subject to power constraints at individual nodes, interference constraint, and the individual rate. Furthermore, the secrecy capacity requirements of cellular and D2D nodes are also considered. The duality theory is used to decompose the problem into multiple sub-problems and Karush-Kuhn-Tucker conditions are exploited to provide the solution of the sub-problems. The simulation results are provided for the validation of our proposed schemes.

Multi-Agent Actor Critic for Channel Allocation in Heterogeneous Networks

Heterogeneous networks (HetNets) can equalize traffic loads and cut down the cost of deploying cells. Thus, it is regarded to be the significant technique of the next-generation communication networks. Due to the non-convexity nature of the channel allocation problem in HetNets, it is difficult to design an optimal approach for allocating channels. To ensure the user quality of service as well as the long-term total network utility, this article proposes a new method through utilizing multi-agent reinforcement learning. Moreover, for the purpose of solving computational complexity problem caused by the large action space, deep reinforcement learning is put forward to learn optimal policy. A nearly-optimal solution with high efficiency and rapid convergence speed could be obtained by this learning method. Simulation results reveal that this new method has the best performance than other methods.

Performance of Feature-Based Techniques for Automatic Digital Modulation Recognition and Classification—A Review

The demand for bandwidth-critical applications has stimulated the research community not only to develop new ways of communication, but also to use the existing spectrum efficiently. Networks have become dynamic and heterogeneous. Receivers have received various signals that can be modulated differently. Automatic modulation classification (AMC) is a key procedure for present and next-generation communication networks, and facilitates the demodulation process at the receiver side. Under the presence of noise from the channel, the transmitter and receiver with its unknown parameters, such as carrier frequency, phase offset, signal power, and timing information, have become cumbersome because detecting the modulation scheme of the received signal is a complicated procedure. Two main methods, namely maximum likelihood functions and the signal statistical feature-based (FB) approach, are used for the automatic classification of modulated signals. In this study, a comprehensive survey of various modulation techniques based on FB approach is conducted. In this research, a number of basic features that are usually used in determining and discriminating modulation types were investigated. The classifier that was used in the discrimination process is studied in detail and compared to other types of classifiers to help the reader determine the limitations associated with the FB approach. Both classifiers and basic features were compared, and their advantages and disadvantages were investigated based on previous researches to determine the best type of classifier and the set of features in relation to each discrimination environment. This work serves as a guide for researchers of AMC to determine the suitable features and algorithms.

Free space optics/millimeter-wave based vertical and horizontal terrestrial backhaul network for 5G

The exponential increase of mobile users and high-speed data driven applications, along with the demand for IoT based services have resulted in a significant congestions in cellular backhaul network. An essential feature requirement for 5G backhaul networks is their ultimate capacity to handle not only human centric traffic, but also machine centric traffic including interconnected vehicles, machines and networks. The hybrid concept of Free Space Optics/Millimeter-Wave technology emerges as a suitable complementary solution platform for next-generation communication networks. In this paper, we have investigated the feasibility of ground station backhaul network. In this approach, a flying network platforms passage the backhaul traffic between the access and the core networks via point-to-point RF/FSO links. We use numerical and analytical results to analyze the performance of the proposed free space optics/millimeter-wave based vertical and horizontal terrestrial backhaul network under different adverse weather conditions, such as the atmospheric turbulence and attenuation. The detrimental effects such as longitudinal pulse broadening of the signal (which is a major reason behind group velocity dispersion (GVD)) and misalignment between the transmitter and the receiver (which is the reason behind pointing errors) are also included in this study. Taking into account these effects, based on Meijer G-function a closed-form analytical expression is derived. The performance is analyzed in terms of probability of fade, threshold and outage probability using receiver diversity over gamma–gamma channel model. These results are useful in designing and deploying a RF/FSO vertical and horizontal backhaul link for 5G communication system.

Wireless networks performance enhancement via buffered cooperative communications

The next-generation wireless communication network is expected to provide a significant increase in average throughput, radio resource utilisation as well as reduced call blocking probability for edge-cell user equipments (UEs). Satisfying these goals has remained as a Herculean task to wireless network designers and operators. The cooperative communication has been proposed by researchers as a possible technique to surmount these challenges. This study addresses the problems of enhancing the network performance of cell-edge UEs in wireless communication networks. A Buffered Cooperative Communication (BCC) model that exploits the transmission channel qualities using link adaptation to enhance the average throughput, quality of service and radio resource utilisation is proposed. In the proposed BCC model, the Markov chain analysis is used to investigate the effect of the queue buffer size on the average throughput, data blocking probability and radio resource utilisation. Finally, this work provides a framework to investigate the performance of the BCC scheme compared to the benchmark: non-BCC (NBCC) scheme. The simulation results show the proposed BCC scheme has significant improvements in the performance over the NBCC scheme.

Analysis of flat-topped Gaussian vortex beam scintillation properties in atmospheric turbulence

We analyze the scintillation properties of a flat-topped Gaussian vortex beam propagating in a weakly turbulent atmosphere. We utilize a random phase screen model to perform this analysis. We evaluate the scintillation against the changes of topological charge, beam order, operating wavelength, receiver aperture side length, and source size parameters. The results show that using a flat-topped Gaussian vortex beam with a high topological charge causes a reduction in scintillation. Increasing the receiver aperture side length reduces scintillation level. As the source size increases, scintillation decreases. Our results also indicate that a flat-topped Gaussian vortex beam with high topological charges has less scintillation than the fundamental Gaussian beam. We believe that our findings will be useful in improving the performance of next-generation optical communication links and networks.

300 GHz Optoelectronic Transmitter Combining Integrated Photonics and Electronic Multipliers for Wireless Communication

THz communications systems at carrier frequencies above 200 GHz are the key to enable next-generation mobile communication networks with 100 Gbit/s wireless data rates. One of the key questions is, which carrier frequency generation technique will be the most suitable. This is currently addressed by two separate approaches, electronics-based and photonics-based. We present in this paper a truly microwave photonic approach that benefits from the main key features of each, bandwidth, tunability, stability and fiber compatibility from photonics and power handling capability from the electronics. It is based on a Photonic Local Oscillator (PLO), generating a 100 GHz frequency, fed into an electronic frequency multiplier. A high speed uni-travelling carrier photodiode (UTC-PD) provides the 100 GHz PLO for Schottky tripler diodes, generating 300 GHz signal. To feed the UTC-PD, we present a photonic integrated mode locked laser source. According to the simulations and measurements, the developed transmitter can produce a maximum of 12 μW of THz power at 280 GHz.

Regional Information Flows: Existing and New Approaches to Geographical Study

The global experience of geographical study of information flows is reviewed for the first time based on journal papers and monographs published in 1988–2017. It is established that the issue is understudied, subject to a shift from understanding the relevance of such studies to attempts to measure and structure information flows. The key areas of geographic study are identified: flows without channels and traffic, channels without traffic, traffic without channels, and flows with channels and traffic. No publication has been retrieved for the fourth area, which is most important for regional studies. Three new approaches are proposed in the framework of next-generation communication network studies and in line with the fourth area: uplink–downlink traffic distribution, redistribution of traffic inside a region proportionally to the population size of settlements, and the definition of potential of mobile communication field. The new approaches are tested with a case study of Russia’s Irkutsk oblast.

Integrated lithium niobate electro-optic modulators operating at CMOS-compatible voltages.

Electro-optic modulators translate high-speed electronic signals into the optical domain and are critical components in modern telecommunication networks1,2 and microwave-photonic systems3,4. They are also expected to be building blocks for emerging applications such as quantum photonics5,6 and non-reciprocal optics7,8. All of these applications require chip-scale electro-optic modulators that operate at voltages compatible with complementary metal-oxide-semiconductor (CMOS) technology, have ultra-high electro-optic bandwidths and feature very low optical losses. Integrated modulator platforms based on materials such as silicon, indium phosphide or polymers have not yet been able to meet these requirements simultaneously because of the intrinsic limitations of the materials used. On the other hand, lithium niobate electro-optic modulators, the workhorse of the optoelectronic industry for decades9, have been challenging to integrate on-chip because of difficulties in microstructuring lithium niobate. The current generation of lithium niobate modulators are bulky, expensive, limited in bandwidth and require high drive voltages, and thus are unable to reach the full potential of the material. Here we overcome these limitations and demonstrate monolithically integrated lithium niobate electro-optic modulators that feature a CMOS-compatible drive voltage, support data rates up to 210 gigabits per second and show an on-chip optical loss of less than 0.5 decibels. We achieve this by engineering the microwave and photonic circuits to achieve high electro-optical efficiencies, ultra-low optical losses and group-velocity matching simultaneously. Our scalable modulator devices could provide cost-effective, low-power and ultra-high-speed solutions for next-generation optical communication networks and microwave photonic systems. Furthermore, our approach could lead to large-scale ultra-low-loss photonic circuits that are reconfigurable on a picosecond timescale, enabling a wide range of quantum and classical applications5,10,11 including feed-forward photonic quantum computation.