Telecommunication Systems

Online ISSN: 1572-9451
Recent publications
Article
With rapid advancements in the technology, almost all the devices around are becoming smart and contribute to the Internet of Things (IoT) network. When a new IoT device is added to the network, it is important to verify the authenticity of the device before allowing it to communicate with the network. Hence, access control is a crucial security mechanism that allows only the authenticated node to become the part of the network. An access control mechanism also supports confidentiality, by establishing a session key that accomplishes secure communications in open public channels. Recently, blockchain has been implemented in access control protocols to provide a better security mechanism. The foundation of this survey article is laid on IoT, where a detailed description on IoT, its architecture and applications is provided. Further, various security challenges and issues, security attacks possible in IoT and their countermeasures are also provided. We emphasize on the blockchain technology and its evolution in IoT. A detailed description on existing consensus mechanisms and how blockchain can be used to overpower IoT vulnerabilities is highlighted. Moreover, we provide a comprehensive description on access control protocols. The protocols are classified into certificate-based, certificate-less and blockchain-based access control mechanisms for better understanding. We then elaborate on each use case like smart home, smart grid, health care and smart agriculture while describing access control mechanisms. The detailed description not only explains the implementation of the access mechanism, but also gives a wider vision on IoT applications. Next, a rigorous comparative analysis is performed to showcase the efficiency of all protocols in terms of computation and communication costs. Finally, we discuss open research issues and challenges in a blockchain-envisioned IoT network.

Article
The parity-check matrices for quasi-cyclic low-density parity-check convolutional (QC-LDPC-C) codes have different characteristics of time-varying periodicity and need to realize fast encoding. The finite field construction method for QC-LDPC-C codes with cyclic two-dimensional maximum distance separable (2-D MDS) codes is proposed using the base matrix framework and matrix unwrapping, thus the constructed parity-check matrices are free of length-4 cycles. The unwrapped matrices are constructed respectively based on different cyclic 2-D MDS codes for the case of matrix period less than or greater than constraint block length, and construction examples are given. LDPC-C codes with different periodicity characteristics are compared with QC-LDPC-C codes constructed with the proposed method. Experimental results show that QC-LDPC-C codes with the proposed method outperform the other codes and have lower encoding and decoding complexity.

Article
Backscatter communication networks have attracted much attention due to their small size and low power waste, but their spectrum resources are very limited and are often affected by link bursts. Channel prediction is a method to effectively utilize the spectrum resources and improve communication quality. Most channel prediction methods have failed to consider both spatial and frequency diversity. Meanwhile, there are still deficiencies in the existing channel detection methods in terms of overhead and hardware dependency. For the above reasons, we design a sequence-to-sequence channel prediction scheme. Our scheme is designed with three modules. The channel prediction module uses an encoder-decoder based deep learning model (EDChannel) to predict the sequence of channel indicator measurements. The channel detection module decides whether to perform a channel detection by a trigger that reflects the prediction effect. The channel selection module performs channel selection based on the channel coefficients of the prediction results. We use a commercial reader to collect data in a real environment, and build an EDChannel model based on the deep learning module of Tensorflow and Keras. As a result, we have implemented the channel prediction module and completed the overall channel selection process. The experimental results show that the EDChannel algorithm has higher prediction accuracy than the previous state-of-the-art methods. The overall throughput of our scheme is improved by approximately 2.9% and 14.1% over Zhao’s scheme in both stable and unstable environments.

Article
One of the network communication systems in our surroundings that has a significant influence on our day-to-day lives is the satellite network. Many authentications and key agreement procedures have been developed for satellite communication systems in order to ensure secure communication. None, however, offer the satellite communication system with the desired security characteristics. Using elliptic curve cryptography and a hash function, this article provides a safe and efficient architecture for satellite network systems. By employing key agreement, users can safely access services offered by the network control centre in the proposed protocol. The suggested framework is resistant to a wide range of security threats and includes a variety of security features and capabilities. Users can easily update their passwords using the proposed protocol. The random oracle model is used to show the suggested protocol security. We provide security verification of the proposed protocol by using AVISPA software tool against man in the middle attack and replay attack. Further, we demonstrates the informal security of the proposed protocol and shows that proposed protocol secure against various security attacks and maintain various cryptographic security properties. We further show that the proposed protocol has lower computation and transmission overhead than competing methods. As a consequence, the proposed satellite network protocol is both efficient and secure.

Article
Interference is the main source of capacity limitation in wireless networks. In some medium access technologies in cellular networks, such as OFDMA, the allocation of frequency subbands is such that interference between cells occurs. This article focuses on preventing harmful interference by properly allocating cells and wireless resources such as subbands to users. In this way, at any time, a set of connections is established that there is no harmful interference between them. In this study, we model inter-cell interference using the protocol interference model and describe interference graph. The proposed model is also applicable to heterogeneous cellular networks. This study provides several types of constraints for the feasibility of a set of connections; each uses a specific component in the network. All constraints are linear; thus, including them in the optimization programs does not increase their structural complexity. A network utility maximization program with joint cell association and interference management is presented, and the effect of applying such interference constraints on simplifying and linearizing the problem structure is described. The presented constraints are discussed in terms of necessary and sufficient conditions for the feasibility of connection, as well as the possibility of distributed construction and verification in cellular network. Two network scenarios are considered, and by using the proposed interference model and appropriate interference constraint, the problem of subband and cell allocation is formulated and solved. The simulation results strongly confirm the performance of the proposed model in practice.

Article
The nature of cognitive radio (CR) technology creates a lot of opportunities for attackers. When an attack occurs, the function of the primary network is affected and thus the overall system performance will be reduced. In the present paper, we introduce and simulate a novel method for identifying spectral sensing data falsification (SSDF) attack and recognizing the malicious users (MU), which we refer to as “Recognition and Elimination of SSDF Attackers”. Our proposed scheme uses the generalized likelihood ratio test (GLRT) approach for solving the MUs detection problem. In this method, we do not need previous information about the network and number of the MUs and secondary users (SUs). In addition to detecting the occurrence of an attack, our method can recognize attackers. By recognizing the MUs, their negative effect will be eliminated and the cognitive radio network (CRN) performance will return to normal condition. Consequently, our scheme can save resources by identifying the strategy of the known attackers. Simulation results reveal that our detection and recognition scheme is better than some of methods available.

Article
In a backbone-assisted industrial wireless network (BAIWN), the technology of successive interference cancellation (SIC) based non-orthogonal multiple access (NOMA) provides potential solutions for improving the delay performance. Previous work emphasizes minimizing the transmission delay by user scheduling without considering power control. However, power control is beneficial for SIC-based NOMA to exploit the power domain and manage co-channel interference to simultaneously serve multiple user nodes with the high spectral and time resource utilization characteristics. In this paper, we consider joint power control and user scheduling to study the scheduling time minimization problem (STMP) with given traffic demands in BAIWNs. Specifically, STMP is formulated as an integer programming problem, which is NP-hard. To tackle the NP-hard problem, we propose a conflict graph-based greedy algorithm, to obtain a sub-optimal solution with low complexity. As a good feature, the decisions of power control and user scheduling can be made by the proposed algorithm only according to the channel state information and traffic demands. The experimental results show that compared with the other methods, the proposed method effectively improves the delay performance regardless of the channel states or the network scales.

Article
Internet-of-Things (IoT) has become an enthralling attacking surface for attackers to explode multitude of cyber-attacks. Distributed Denial of Service (DDoS) attack has transpired as the most menacing attack in the IoT networks. In this article, we propose an attack detection system to identify anomalous activities in the fog-enabled IoT network. Initially, authors have investigated exhaustively on the performance of filter-based feature selection algorithms comprising ReliefF, Correlation Feature Selection (CFS), Information Gain (IG), and Minimum-Redundancy-Maximum-Relevancy (mRMR) and distinct categories classification algorithms upon the prepared dataset consisting of IoT network specific features. Performance of the tested classification algorithm is assessed using prominent evaluation measures. Moreover, response time of classifiers is calculated for centralized and fog-enabled IoT network infrastructure. The experimental outcomes unveil that, in terms of both accuracy and latency, J48 classifier outperforms all other tested classifier with mRMR feature selection algorithm.

Article
Rapid developments in radio technology and processors have led to the emergence of small sensor nodes that provide communication over Wireless Sensor Networks (WSNs). The crucial issues in these networks are energy consumption management and reliable data exchange. Due to the limited resources of sensor nodes, WSNs become a vulnerable target against many security attacks. Thus, energy-aware trust-based techniques have become a powerful tool for detecting nodes’ behavior and providing security solutions in WSN. Clustering-based routings are one of the most effective methods in increasing the WSN performance. In this paper, an Energy-Aware Trust algorithm based on the AODV protocol and Multi-path Routing approach (EATMR) is proposed to improve the security of WSNs. EATMR consists of two main phases: firstly, the nodes are clustered based on the Open-Source Development Model Algorithm (ODMA), and then in the second phase, clustering-based routing is applied. In this paper, the routing process follows the AODV protocol and multi-path routes approach with considering energy-aware trust. Here, the optimal and safe route is determined based on various parameters, namely energy, trust, hop-count, and distance. In this regard, we emphasize the evaluation of node trust using direct trust, indirect trust, and a multi-objective function. The simulation has been performed in MATLAB software in the presence of a Denial of Service (DoS) attack. The simulation results show that EATMR performs better than the state-of-the-art methods in terms of successfully detecting malicious nodes and enhancing network lifetime, energy consumption, and packet delivery ratio. As a conclusion, EATMR shows an average of 4.3 and 6.1% superiority over M-CSO and SQEER in different scenarios, respectively.

Article
• Afsaneh Allahvirdi
• Saleh Yousefi
• Asghar Asgharian Sardroud
Network Function Virtualization (NFV) is an emerging approach to overcome the limitations of proprietary network hardware appliances. Under the paradigm of NFV, network functions may be implemented virtually-referred to as Virtual Network Functions (VNFs). A set of chained network functions compose an end-to-end network service called a Service Function Chain (SFC). The SFC placement problem on fully VNF-enabled networks has a reach body of work in the literature in recent years. However, before fully realizing NFV, we face hybrid networks in which only some network nodes support virtualization. In this paper, we study the problem of dynamic SFC placement considering such a hybrid network. First, we formulate the problem as an Integer Linear Programming (ILP) model. Then, we propose some heuristic algorithms for initial SFC placement and handling SFC scaling requests (i.e., network function insertion/deletion to/from the deployed SFC) reactively and proactively. Furthermore, we propose two placement strategies, i.e., sharing and grouping for placing SFCs on the substrate network. Using simulation, we compare the performance of the proposed model and algorithms on fully VNF-enabled and hybrid networks. Moreover, we show that sharing and grouping VNFs can provide higher performance in terms of request acceptance rate and efficiently and reduce the average delay and overall cost.

Article
• Xiaohu Huang
• Dezhi Han
• Tien-Hsiung Weng
• [...]
• Kuan-Ching Li
WSNs (Wireless Sensor Networks) are critical components of the Internet of Things (IoT). With the internationalization of the IoT and the widespread use of apps, it is crucial to increase WSNs localization algorithms' accuracy and their flexibility to dynamic and changing surroundings. To this end, it is proposed in this article a wireless sensor network location algorithm based on Manhattan distance (MDV-Hop) to solve many existing problems encountered in the wireless sensor network location algorithm. The MDV-Hop localization algorithm improves over present algorithms regarding frequency hopping, length, and least-squares of nodes to enhance the WSNs nodes' location accuracy and algorithm's adaptability in multi-variable environments. Manhattan distance has the characteristics of the sum of the projection distance of the line segment between two points on the coordinate axis in Euclidean space. The Manhattan distance measurement method is combined with Euclidean distance to determine the second minimum frequency hopping between beacon nodes, which substantially increases the DV-Hop algorithm's localization performance. On this foundation, the multi-objective genetics (NSGA-II) algorithm is employed to refine the outcomes of the least-squares approach to increase the suggested algorithm's localization accuracy, as it succeeds the simplicity and flexibility of the original DV-Hop method. Extensive simulations are performed in network scenarios with sparse and unevenly distributed anisotropic sensor nodes, and experimental results show that the MDV-Hop method outperforms the current WSNs node localization techniques in terms of performance and precision.

Article
Nowadays, many applications need varying levels of Quality of Service (QoS). The network that provides the communication service connects the servers and clients. The network traffic which is routed through the network should be engineered. Traffic Engineering (TE) is a mechanism for transferring the packets considering the different QoS level requirements among applications. The optimal resource allocation is the primary strategy for TE so that the network can provide the QoS requirements for each application. The TE can improve network efficiency, performance, and user satisfaction. Software Defined Network (SDN) has been proposed as the novel network architecture that could make networks agile, manageable, and programmable using control and data plane separating compared to traditional network architecture. In this paper, we survey network traffic engineering in SDN. We investigate and cluster the articles published between 2017 and 2022 on traffic engineering in SDN. The state-of-the-art articles about the traffic engineering mechanisms in SDN have been examined and classified into four types: topology discovery, traffic measurement, traffic load balancing, QoS, and dependability. Finally, the cutting-edge issues and challenges are discussed for future research in SDN-based TE.

Article
Access control technology is one of the key technologies to ensure safe resource sharing. Identity authentication and authority distribution are two key technologies for access control technology to restrict unauthorized users from accessing resources, and only authorised legal users can access resources. However, user privacy protection and frequent permission changes are two thorny issues that need to be solved urgently by access control technology. In this paper, a dynamic access control model based on privacy protection is proposed to deal with these problems. Compared with existing access control technologies, the main advantages of this paper are as follows: (1) Encrypt and hide the attributes of entities, and use attribute-based identity authentication technology for identity authentication, which not only achieves the purpose of traditional identity authentication, but also ensures the attributes and privacy of entities are not leaked; (2) Binding resource access permissions with entity attributes, dynamically assigning and adjusting resource access control permissions through changes in entity attributes, making resource access control more fine-grained and more flexible. Security proof and performance analysis show that the proposed protocol is secure under the hardness assumption of the discrete logarithm problem and the decision bilinear Diffie–Hellman problem. Compared with the cited references, this model has the advantages of low computational complexity, short computational time, and low communication overhead.

Article
A typical 5G multiple-input and multiple-output (MIMO) system must combine a high number of antennas at both the transmitter and receiver to realize spatial multiplexing capability. In this paper, a wideband 16- element indoor base station (BS) antenna array that can cover 3.3–6.0 GHz is proposed for 5G applications. A π-shaped monopole antenna is designed to cover the Lower band (LTE bands 42/43–N77–N78), the intermediate band (N79), and the higher band (LTE 46). The antenna elements are arranged in a limited space printed on a substrate take the Hexakaidecagon Polygon shape. As the antenna elements are arranged with good isolation, achieving good polarization diversity. The proposed BS array is simulated, fabricated, and tested. The typical results, S-parameters, antenna efficiency, and radiation patterns are investigated. Moreover, to validate the MIMO performances, a very low envelope correlation coefficient (ECC) below 0.02, high antenna efficiency of about 82–93.2% are achieved. The calculated ergodic channel capacity of the 16 × 16 MIMO system reached up to 85 bps/Hz. The proposed antenna array was compared to some other 5G MIMO indoor base station antennas.

Article
The IEEE 802.11ay is an emerging system that will become a full member of the big family of the IEEE 802.11 standards in the near future. Compared to its predecessor IEEE 802.11ad, it promises to offer higher system flexibility and more reliable wireless communication links for short distances in millimeter-wave bands. This paper provides a simulation-based performance study of IEEE 802.11ay single carrier-physical (SC-PHY) layer for different transmission modes and scenarios. For this purpose, a MATLAB-based IEEE 802.11ay SC-PHY simulator is introduced. Next, 60 GHz indoor channel models based on extensive real-world indoor measurements, conducted by ourselves, are created and used to analyze the performance of IEEE 802.1ay SC-PHY in terms of Bit Error Ratio and data throughput. Both the simulator and channel models are available online. A phase noise behavioral model to emulate channel impairments is also considered and used in this work. The obtained results show how the IEEE 802.11ay SC-PHY system employing different transmission modes is influenced under various channel conditions.

Article

Article
With the popularity of autonomous vehicles and the rapid development of intelligent transportation, the application scenarios for detecting pedestrians in everyday life are becoming more and more widespread, with high and high application value. Pedestrian detection is the basis of many human-based tasks, including speed tracking, pedestrian motion detection, automatic pedestrian recognition, and appropriate response measures, or rejecting true false pedestrian detection. Various researchers have done a lot of research in this area, but there are still many errors in the correct identification of rejecting true false pedestrians. This article focuses on the design and implementation of real pedestrian discovery using deep learning technology to identify pedestrian rejections. In this work, our goal is to estimate the achievement of the current 2D detection system with a 3D Convolutional Neural Network on the issues of rejecting true false pedestrians using images obtained from the car's on-board cameras and light detection and ranging (LiDAR) sensors. We evaluate the single-phase (YOLOv3 models) and two-phase (Faster R-CNN) deep learning meta-structure under distinct image resolutions and attribute extractors (MobileNet). To resolve this issue, it is urge to apply a data augmentation approach to improve the execution of the framework. To observe the performance, the implemented methods are applied to recent datasets. The experimental assessment shows that the proposed method/algorithm enhances the accuracy of detection of true and false pedestrians, and still undergoes the real-time demands.

Article
The process of locating nodes is really a challenging problem in the field of wireless sensor networks. Wireless sensor network localization is commonly followed by the distance vector algorithm. All beacon nodes are currently using DV-Hop algorithms to locate the dumb node. On the other hand, the approximate distance from the dumb node to certain beacon nodes contains a significant error, resulting in a large finished dumb node localization problem. To improve localization error an efficient DV-Hop method on social learning class topper optimization for wireless sensor networks is implemented in this paper. The proposed algorithm reduces communication between unknown or dumb and beacon nodes by measuring the dimensions of all the beacons at dumb nodes. The network imbalance model is frequently used to show the applicability of the proposed approach in anisotropic networks. Simulations are performed on LabVIEW 2015 platform. The results show that our proposed method outperforms some existing algorithms in terms of computing time (2%), localization error (6.6%), and localization error variance (8.3%).

Article
This work addresses the problem of traffic splitting for improving the overall delay jitter performance in the uplink multi-access system. We propose a packet-scheduling paradigm based on stochastic approximation algorithm to distribute the source traffic across the multiple network paths/interfaces. We first provide an analytical model and the delay jitter analysis for an individual interface. Later we formulate the traffic splitting problem as an optimization problem to learn the optimal split across the interfaces. We share the experimental results for the video and constant bit rate traffic on real networks (Wi-Fi or cellular networks) and convergence of our system using the proposed scheme in the dynamic network environment. The paradigm proposed in the paper is general and can be adapted to different objective functions.

Article
This paper studies the harvested energy maximization in an intelligent reflecting surface (IRS) aided multiuser multiple-input multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) system in which the users can exploit power-splitting (PS) techniques for information decoding and energy harvesting (EH) simultaneously. A design problem is mathematically formulated as a joint optimization problem of transmit precoding (TPC) matrices at the base station (BS), the phase shifts at the IRS, and EH PS factors at the users to maximize the total harvested energy at the users while guaranteeing the quality of service requirements in terms of minimum achievable user rates and minimum harvested energy at each user. Considering the nonlinear EH models of the practical EH circuits at the users and unit-modulus constraints of the IRS phase shifters, the design problem becomes a highly nonlinear and non-convex optimization problem of the coupled matrix variables. To tackle the mathematical challenges in seeking the optimal solutions, we adopt alternating optimization to decompose the original design problem into two subproblems. The first subproblem is to jointly determine the TPC matrices at the BS and PS factors at the users while the second subproblem is to obtain the phase shifts at the IRS. Since each subproblem is still a non-convex optimization problem, we employ the minorization-maximization method to devise lower bound concave functions for the nonlinear EH and user rate functions and find the appropriate convex inner sets of the feasible sets to transform the optimization problems into convex ones. Verified by simulation results that the convergence of the proposed iterative algorithm is guaranteed and the total harvested energy is significantly improved as the multiuser MIMO SWIPT system is aided by the IRS with optimal phase shifts.

Article
The Internet of Things (IoT) paradigm, has opened up the possibility of using the ubiquity of small devices to route information without the necessity of being connected to a Wide Area Network (WAN). Use cases of IoT devices sending updates that are routed and delivered by other IoT devices have been proposed in the literature. In this paper we focus on receivers only interested in the freshest updates from the sending device. In particular, the dynamic network created by routing/gossiping through small devices creates the possibility of delivering updates out of order. Thus, the entire process can be studied well through a queueing system with infinitely many servers, all serving updates with a random service time. Age of Information (AoI) was proposed as the main metric to measure information freshness. We study the amount of time that the AoI is over a certain threshold at the receiver end as a Quality of Service (QoS) measure, called update outage probability. Particularly, given the recent interest in the literature for time domain analysis of the AoI, we obtain the exact expressions for the AoI, peak AoI (pAoI), effective service time and effective departure time distributions for an M/M/∞ queuing system from a time domain perspective, and study the interdependence between the various parameters involved in order to satisfy a given statistical constraint on timeliness.

Article
The frequency spectrum is a scarce resource, and is owned and regulated by the state to ensure its efficient and fair utilization. All over the world, a large number of Mobile Network Operators (MNOs) are already involved in either active or passive Radio Access Network (RAN) sharing to maximize cost savings. The aim of this article is to challenge the ownership of individual operator’s infrastructure and present technical arguments for One Radio Access Network (OneRAN) approach for deploying a cellular network. The enormous increase in data traffic and regulatory requirements concerning public safety communications provide the basis for migrating to OneRAN infrastructure. The OneRAN approach provides an opportunity to gain technological benefits and helps in meeting the requirements of critical communication. OneRAN targets to maximize the savings on capital and operational expenses. The main focus of this work is outdoor wide-area coverage i.e., outdoor users in rural areas and on highways, as it is assumed that indoor service provision in the future requires a dedicated indoor solution. For the research work of this article, a measurement campaign was launched and different Key Performance Indicators(KPIs) of Long Term Evolution(LTE) technology for three commercial MNOs of Finland were measured over a 52 km highway from Iittala to Tampere city. The acquired results highlight the gain of OneRAN infrastructure as it enhanced the user quality of experience i.e., user throughput, especially of the critical cell border users, and improved the overall system performance economically. Finally, supportive arguments are presented for having a OneRAN infrastructure specifically over the highways.

Article
Contradictory needs for high scalable, high speed, low latency, and low-cost architectures turn researchers’ attention toward optoelectronic architectures. This is due to its ability to provide high scalability and high performance at a manageable cost, by imposing some optical links in suitable locations while designing the architecture. In this paper, the most common optoelectronic architectures are overviewed and evaluated in terms of various topological properties, namely, size, diameter, cost, bisection width, maximum and minimum node degree, and Hamiltonian path and cycle. Thus, most of these architectures are based on Optical Transpose Interconnection System (OTIS). The evaluated optoelectronic architectures in this paper are OTIS-Hypercube, Extended OTIS-n-Cube, Enhanced OTIS-Cube, OTIS-Ring, OTIS k-Ary n-Cube, OTIS-Mesh, OTIS-Mesh of Trees, OTIS Hyper Hexa-Cell, and Optical Chained-Cubic Tree. The obtained results showed the strengths and weaknesses of the mentioned optoelectronic architectures to help designers and developers to investigate and decide on the suitable architecture for their problem of interest.

Article
Nowadays, the intelligent transportation system (ITS) has developed prosperously all over the world. As a key technique in ITS, vehicular ad-hoc network (VANET) supports fast transmitting while bringing security problems simultaneously. To ensure efficiency, those unprotected data transmitting at a high speed can be easily eavesdropped on or forged, which will badly damage the ITS. To authenticate the identities of the vehicles in VANETs, signatures with certificates are often employed in historical research, but seldom study discusses the protection of generated data or mutual authentication between participants in VANETs. In order to tackle the problems above, we propose a new mutual authentication scheme for VANET where the private data can be kept away from attackers. In our scheme, the corresponding manager of each region can deal with the dynamic information of vehicles. The security analysis is also carried out and shown to emphasize the reliability of the scheme, such as anonymity, unlinkability and resistance to replay attacks, etc. Besides the resistance to different attacks, the real-time information secrecy can also be protected in our scheme, which is not achieved in the compared schemes. Moreover, the performance evaluation and simulation with NS-3 show that the packet delivery ratio reaches over 99% in most of the application scenarios, which proves that the scheme is efficient and practical.

Article
With the help of fog computing theory, this paper proposes Cluster Routing Optimized Algorithm of Nonlinear Event Migration Strategy, CR-NEMS. First, the fog node is used for high computing power and control ability to match and schedule sensor nodes to make them evenly distributed to achieve the purpose of network energy balance. Secondly, the intelligent algorithm is adopted to optimize the data transmission link to reduce network delays and improve transmission efficiency. Thirdly, the routing optimization is achieved through the iterative change and update strategy of controllable parameters to improve the global traversal capability of the entire network. Finally, the simulation experiment shows that the algorithm is compatible with other algorithms under the conditions of data transmission in the entire network. Compared with the network delay, network energy and network lifetime, the proposed strategy reduces by 23.49%, 13.22% and 12.17% respectively. It verifies that the algorithm in this paper effectively balances the network energy while solving the routing optimization problem and resource allocation problem in the target area.

Article
IoT era and its ubiquitous sensing raise serious security challenges such as wormhole attacks. Given that these attacks may affect the location determination of the employed sensors, security can be seriously compromised. The most common and severe attack is the single wormhole one, which is the focus of this paper. One of the most employed algorithms to approach the sensor location determination is the Distance Vector Hop (DV-Hop) algorithm, which can still be seriously affected from wormhole attacks. To overcome the challenges of this algorithm, this article proposes a novel secure DV-Hop localization algorithm against wormhole attack (ANDV-Hop), where beacon nodes delegate their attacked neighboring nodes to broadcast data messages, and the intersection of communication range of these neighboring nodes does include wormhole nodes. For implicit attacks, close nodes to the wormhole node are selected in order to broadcast data messages, whilst the nodes within the attack range remove beacon nodes at the other end of the link from the neighboring list. For explicit wormhole attack, the algorithm employs a trust model that calculates the comprehensive trust value obtained via a selection reward/punish coefficient. The selected ones within the intersection zone are considered rewarded, whilst the ones to be removed are classified as punished. Experimental results show that the proposed algorithm improves detection success rate, reduces relative localization error and energy loss, showing effectiveness and reliability.

Article
The ever-expanding growth of internet traffic enforces deployment of massive Data Center Networks (DCNs) supporting high performance communications. Optical switching is being studied as a promising approach to fulfill the surging requirements of large scale data centers. The tree-based optical topology limits the scalability of the interconnected network due to the limitations in the port count of optical switches and the lack of optical buffers. Alternatively, buffer-less Fast Optical Switch (FOS) was proposed to realize the nanosecond switching of optical DCNs. Although FOSs provide nanosecond optical switching, they still suffer from port count limitations to scale the DCN. To address the issue of scaling DCNs to more than two million servers, we propose the hyper scale FOS-based L-level DCNs (HFOSL\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_L$$\end{document}) which is capable of building large networks with small radix switches. The numerical analysis shows L of 4 is the optimal level for HFOSL\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_L$$\end{document} to obtain the lowest cost and power consumption. Specifically, under a network size of 160,000 servers, HFOS4\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_4$$\end{document} saves 36.2% in cost compared with the 2-level FOS-based DCN, while achieves 60% improvement for cost and 26.7% improvement for power consumption compared with Fat tree. Moreover, a wide range of simulations and analyses demonstrate that HFOS4\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$_4$$\end{document} outperforms state-of-art FOS-based DCNs by up to 40% end-to-end latency under DCN size of 81920 servers.

Article
The protection of user data and privacy is becoming more critical because they mainly come from different sources, such as the Internet of Things. The searchable encryption (SE) primitive is a potential candidate who can guarantee data privacy while maintaining the search capability. The majority of known SE methods rely on the bilinear pairing operation, which is an expensive operation compared to other cryptographic operations. Therefore, bilinear-based SE may not be suitable for deployment on constraint devices with limited processing power. In addition, most of the schemes presented in the literature were vulnerable to different types of attacks, such as keyword guessing attacks. We tackle these issues by presenting a pairing-free public key encryption with keyword search and does not require a secure channel. The proposed scheme is proven in the random oracle model to be secure against various keyword guessing attacks, based on the hardness of solving the discrete logarithm and the computational Diffie–Hellman problems. These results are concluded by thoroughly analyzing the proposed scheme and five other state-of-the-art schemes recently presented in the literature. Finally, based of the performance analysis, where the experiments are conducted using three different sets of parameters for the elliptic curve, combined with three hash functions that were advised by NIST to satisfy the different security requirements, we observe that the proposed scheme does not require much communication costs and is somewhat fast in executing the different algorithms. Moreover, the proposed scheme guarantees the security requirements and makes it semantically ciphertext-indistinguishability, trapdoor-indistinguishability secure, and resilient to online and offline keyword guessing attacks.

Article
On-time delivery of network flows is crucial to ensure the quality of service of deadline-constrained applications. Today, real time applications have various uses in multimedia communications, the Internet of Things (IoT), and 5G (5th generation mobile network) technology. In Software Defined Network (SDN) architecture, the controller has a global view of the network. Hence, it is possible to enrich the features of the controller and/or forwarding devices to support real time communication. In this paper, we propose a firm real time software-defined approach (FRT-SDN) for real time communication and present a novel solution for the real time forwarding/routing of time-sensitive applications in SDN. To this end, FRT-SDN divides traffic into real time and non-real-time flows, prematurely drops late packets that probably miss their deadlines according to a four-stage mathematical modeling, and uses adaptive multipath routing, Earliest Deadline First (EDF) scheduling algorithm, and prioritized queues. We evaluate FRT-SDN with the Mininet tool. Emulation results show that FRT-SDN yields a 23–97% improvement in deadline hit ratio and an 88% decrease in the end-to-end delay and jitter. Hence, it effectively enhances the timeliness of the network. On the other hand, based on the correlation coefficient concept, the effect of network parameters on the average deadline hit ratio has been measured.

Article
In this paper, we combine two new techniques: non-orthogonal multiple access (NOMA) and full-duplex (FD) in a downlink of wireless cooperative relay communication system with two end users. The NOMA approach is applied to both the source and the relay. Whereas, the FD is only applied to the relay. The system performance is investigated in the case of vehicle-to-vehicle (V2V) communication. The self-interference (SI) due to FD protocol is taken into consideration, and then the outage probability (OP) and ergodic capacity (EC) of the considered FD-NOMA-V2V system are derived over the double Rayleigh fading channels. Furthermore, an impact of distance between the vehicles and a path loss exponent on the system performance is discussed. The numerical results show that the system performance strongly decreases in comparison with that over the Rayleigh fading channel, and the SI lets the performance of the considered system decrease significantly. Due to the FD mode and NOMA scheme, the system performance in terms of OP and EC reaches the floor at the high signal-to-noise ratio (SNR) region. Based on the distance between the vehicles, the path loss exponent and the residual self-interference (RSI), the power allocation coefficients is decided in the sense of similar performance of both users in the cooperative FD-NOMA-V2V system. Additionally, we can choose locations of the relay to achieve the best performance of the considered system. Finally, the perfect match between the theoretical and simulation results validates our proposed method.

Article
Localization is a crucial method applied in Wireless Sensor Networks (WSNs) to determine the geographic position of the sensor nodes in the sensing region. Many existing WSNs applications require location awareness of sensor nodes. Global Positioning System (GPS) is a well-known technique of localization. However, as a WSN is composed of thousands of sensor nodes, the installation of GPS is not available at every node. Nowadays, many localization algorithms are developed to solve the location awareness problem. The Distance Vector-Hop algorithm (DV-Hop) is a well-known technique thanks to its simplicity and its accurate localization results for WSNs. However, the DV-Hop presents some localization accuracy drawbacks. In this paper, we propose an improvement of the DV-Hop algorithm based on Tikhonov regularization method for wireless sensors networks. We verify the validity of the proposed method through experiments. Simulation results confirm that the proposed localization algorithm is better than the original DV-Hop algorithm and some of its improved algorithms with up to 60% in terms of localization accuracy.

Article
The parameter analysis of satellite tracking, telemetry, and command signal is necessary for space situational awareness. Unified S-Band (USB) waveforms are widely used in space missions. As a crucial parameter of the USB waveform, the modulation index influences the power distribution and spectrum characteristics of the waveform. This paper proposes two novel blind estimation methods of the modulation index based on spectral analysis. The equations for estimating the modulation index are constructed by the relation between the spectral characteristics and the Fourier transform of signal. The theoretical analysis of the estimation error of the methods is derived. The factors that influence the estimation error are investigated by Monte Carlo simulation, and an actual Geostationary Earth Orbit satellite signal is used to verify the methods. The proposed methods have lower complexity than existing methods, while also providing more than 10 times accuracy improvement at low signal-to-noise ratios. Suggestions for the application of the proposed methods to different scenarios are also provided.

Article
LoRaWAN is one of the most suitable communication protocols for the IoT applications that require low power over long-range communication. However, the LoRa network suffers from scalability, low data rate, and other performance issues that significantly affect the network performance. The study of the optimal spreading factor allocation can overcome these issues and help to improve the network performance. Hence, this article puts forward the state-of-the-art literature review on the Spreading Factors Allocation schemes for the LoRaWAN. Industry and academia have done an extensive research to address the issues related to optimal resource allocation, like spreading factor allocation to the spatially distributed end-devices of the network. Most of the problems concerning spreading factor allocation are being explored and resolved. Therefore, this paper reviews and compares various spreading factor allocation schemes proposed by the researchers. Furthermore, we provide a summary of the different review studies of the LoRaWAN. The literature presented in this paper motivates researchers to examine other aspects of spreading factor allocation schemes to improve the LoRa network performance.

Article
The precise node location of the sensor nodes is an essential requirement in wireless sensor networks (WSNs) to determine the place or event occurring at a particular instant of time. In WSN, existing localization schemes consider two-dimensional (2D) space, while in actual life, sensor nodes are placed in three-dimensional (3D) space. In 3D localization, there are many research challenges, such as higher computational complexity, poor location prediction, lesser coverage, and depending only on fewer anchor nodes. To address various research issues in a 3D environment we propose a range-free technique applied in an anisotropic scenario having degree of irregularity (DOI) as 0.01 using the concepts of a fuzzy logic system (FLS). Anisotropic properties of nodes are considered to determine the efficiency of Grey wolf with the Firefly algorithm. In our proposed scenario, the received signal strength (RSS) information is necessary among the target nodes and their corresponding anchor nodes for determining the location of target nodes using the information based on edge weights. These edge weights are further modeled using Hybrid Grey Wolf Optimization with Firefly Algorithm (GWO-FA) to estimate the location of target nodes. The proposed algorithm is energy efficient as a single location-aware node is used for localization. Further, the concept of virtual anchors is introduced that helps the algorithm to determine 3D positions.

Article
The generalization problem in deep learning has always been an important problem to be solved. In the field of steganalysis, generalization is also an important factor that makes steganalysis models difficult to deploy in real-world scenarios. For a group of suspicious images that never appeared in the training set, the pre-trained deep learning-based steganalysis models tend to suffer from distinct performance degradation. To address this limitation, in this paper, a feature-guided subdomain adaptation steganalysis framework is proposed to improve the performance of the pre-trained models when detecting new data. Initially, the source domain and target domain will be divided into subdomains according to class, and the distributions of the relevant subdomains are aligned by subdomain adaptation. Afterward, the guiding feature is generated to make the division of subdomains more stable and precise. When it is used to detect three spatial steganographic algorithms with a wide variety of datasets and payloads, the experimental results show that the proposed steganalysis framework can significantly improve the average accuracy of SRNet model by 5.4% at 0.4bpp, 8.5% at 0.2bpp, and 8.0% at 0.1bpp in the case of dataset mismatch.

Article
Intelligent reflecting surfaces aided communication have been emerging as strong candidates to support the 6G wireless physical platforms. IRS has shown promising qualities in enhancing the spectral efficiency of wireless networks because of its capability to alter the conduct of interacting electromagnetic waves through intelligent handling of the reflections phase shifts. Also, NOMA proves itself to be superior among the other multiple access techniques as it supports a greater number of users using non-orthogonal resource allocation. This paper brings a survey over the IRS-assisted NOMA networks. The IRS and NOMA technologies, and their physical working principles are first introduced in the paper. The state-of-theart of the IRS-assisted NOMA communication networks is next presented followed by a discussion of related performance parameters for analysis. Afterward, it discusses the resource allocation, and secrecy requirements in the IRS–NOMA networks. Furthermore, it presents the relevant work related to the optimization of energy efficiency, power efficiency and coverage. A comparison of IRS–NOMA network with MIMO–NOMA, and relay aided NOMA network is provided. Finally, a few exciting open challenges for IRS-assisted NOMA networks are identified including optimization problem using ML, identifying implementing scenarios of NOMA or OMA with IRS, PLS, and terahertz communication.

Article
Modern day millimeter wave communication systems prefer hybrid precoding architecture over digital architecture due to higher energy efficiency, lower power consumption and comparable spectral efficiency. Both energy efficiency and spectral efficiency defines the system performance of a hybrid precoder and are dependent on the number of available active RF chains. The aim to maximize energy efficiency without any obvious performance degradation in terms of spectral efficiency has created a tradeoff due to dependency of energy and spectral efficiency on RF chains. This tradeoff is being investigated in this paper by performing RF chain selection using evolutionary algorithms. We present a hybrid heuristic approach comprising of low computationally complex evolutionary algorithms for RF chain selection and successive interference cancellation for precoding. Furthermore, we have shown that for low SNR regime the analog percoding is optimal in terms of energy efficiency and for high SNR regime we can adopt the RF chain selection procedure to maximize the energy efficiency. Moreover, the channel irregularities do not effect our proposed scheme.

Article
In this work, a Carrier Waveform Inter-Displacement (CWID) modulation, based on Linear Frequency Modulation-Phase Shift Keying (LFM-PSK), is proposed to achieve high Bit Transmission Rate (BTR) in wireless radio communications system. The novel modulation scheme introduces position modulation by re-ordering inter-displacement in different symbol carriers, which improves the BTR as compared with the LFM-PSK system. Moreover, a Graphical User Interface (GUI) based on Wireless open-Access Research Platform (WARP) is designed and the CWID system is implemented and validated on the Software Defined Electronics platform. Results of simulations and experiments show the effectiveness and the superiority of the CWID over its competitors.

Article
In Cognitive radio-based Internet of Things (CR-IoT) systems, the return of the primary user (PU) causes the secondary user (SU) that is communicating to face the spectrum handoff problem. In the process of spectrum handoff, the user terminal cant get the idle channels in time because of the unknown channel usage state.To solve this problem, a hybrid spectrum handoff algorithm based on genetic algorithm is proposed. The algorithm considers the regularity of PU activities in space and time, defines the idle probability of channels from the perspective of week attributes and time periods, obtains the optimal time period length using genetic algorithm,generates a channel idle probability table, and provides the target channel sequence for SUs in combination with the proposed channel ordering scheme. Simulation results show that when the total number of SUs is within 10 ∼ 20, the proposed algorithm has a spectrum handoff outage probability of less than 7%, an average delivery time of less than 13s, a total packet error rate of less than 5.5%, a channel utilization of consistently above 70%, and an average detection times of less than 7 times.

Article
The Internet of Things (IoT) is a new paradigm for connecting various heterogeneous networks. Cognitive radio (CR) adopts cooperative spectrum sensing (CSS) to realize the secondary utilization of idle spectrum by unauthorized IoT devices, allowing IoT objects can effectively use spectrum resources. However, the abnormal IoT devices in the cognitive Internet of Things will disrupt the CSS process. For this attack, we propose a spectrum sensing strategy based on weighted combining of the hidden Markov model. The method uses the hidden Markov model to detect the probability of malicious attacks at each node and reports to the Fusion Center (FC), which evaluates the submitted observations and assigns reasonable weight to improve the accuracy of the sensing results. Simulation results show that the algorithm proposed has a higher detection probability and a lower false alarm probability than other algorithms, which can effectively resist spectrum sensing data falsification (SSDF) attacks in cognitive Internet of Things and improve the performance of IoT devices.

Article
The small cell structure in which many cells are arranged per unit area by reducing the size of cells is a candidate technology for an increase in transmission capacity in the 5G environment. However, the decrease in the size of the cell led to additional problems such as increased inter cell interference and frequent cell changes owing to the movement of the terminal. Therefore, the aim of this study was to propose small cell dynamic channel allocation (SDCA) and hybrid and dynamic channel allocation (HDCA) using conventional reuse methods to improve the macro cell performance while efficiently utilizing scarce frequency resources. The proposed method facilitates an improved performance that is lacking for macro-cell users in the center area of the cell boundary for the network where conventional macro cells and small cells are superposed. Furthermore, to improve the performance, it can provide resources that are lacking in the small cells of the center. To evaluate the performance, the proposed method was compared to frequency reuse factor1 (FRF1), frequency reuse factor3 (FRF3), and fractional frequency reuse (FFR) methods in terms of the signal-to-interference/noise-ratio (SINR) of users of each macro cell and small cell, outage, capacity for each user, and total system capacity. As a result of comparing the SINR, it was confirmed that the performance of the macro cell users has improved by an average of 43.88% compared to FRF1, FRF3, and FFR, and the performance of small cell users has improved by an average of 4.31%. Comparison results show that the outage proportions of the macro and small cell users are 61.29% and 70.59% lower on average, respectively. A comparison of results show that the capacities of the macro and small cell users have also improved by 22.5% and 14.5% on average, respectively. As the comparison results of the total system capacity indicate, the proposed method shows an average improvement of 11.67%. In cases in which the added resources of the small cells are found to be unnecessary based on the results of the performance evaluation, there is an advantage in that they can be reduced to improve the performance of macro cell users, or they can be used to fill the insufficient resources of the small cells while maintaining the performance of the macro cell users. This fluidity originates from the ability to address occasional situations in a dense environment. These two approaches are expected to be used effectively in 5G network environments.

Article
One goal of the sixth generation (6 G) is to extend the communication abilities of a Gbps bitrate, low latency and high reliability to global areas. The Space-Air-Ground Network (SAGN) is a promising scheme. Deterministic services in SAGN are very important for network providers, but service conflicts and a lack of end-to-end feature abstractions restrict the development of more services and applications. Abstracting the network features to design service components and abilities is the key issue. Therefore, this paper proposes a new service development scheme for SAGNs, which provides global service components and abilities based on a microservice framework for different networks. We explore the unified feature description method based on the ground state, which decouples the network element function (NEF) from different end-to-end networks. A convex optimisation model based on reversible driving factors is designed for the service developments model, which can optimise the choreographies and combinations of the services in SAGN. A feature compression method based on equivalent mapping service description and orbital shrinking is proposed to improve the development efficiency of SAGN services. Simulations and tests are conducted to examine the performance enhancement of services, which improves the service generating speed by 14.5% and the service conflict rate by 23.4%.

Article

Article
In non-orthogonal multiple access (NOMA) scheme, the strong users, located near to base station, demodulate their data by considering the information of other users as interference. One of the crucial challenges in NOMA is the design of sophisticated interference cancellation techniques to improve performance. An alternate approach is to exploit cooperative communication with more straightforward interference cancellation techniques to enhance performance without increasing computational complexity. In this paper, we propose a novel hybrid minimal set decode-amplify-forward (MS-DAF) relaying scheme with maximal ratio combining and space–time block coding for MIMO-NOMA to enhance the performance of weak users located away from the base station and/or having poor channel conditions. The proposed MS-DAF approach reduces the number of relayed links through an intelligent selection of relaying users. The aim is to minimize the re-transmission overhead without compromising the performance. Furthermore, the proposed MS-DAF approach switches between amplify-and-forward and decode-and-forward based on the channel conditions. Simulation results for both SISO- and MIMO- NOMA are presented to show the superiority of the proposed hybrid scheme over existing individual schemes. The proposed technique can be used to improve the performance of edge users in a cellular network with minimal relayed links.

Article
Energy saving in User Equipment (UE) is one of the important issues for limited sources of power in the device. It is critical for the UE to maximize its energy efficiency. In this paper, we have presented two stochastic models, namely the Markov model and semi-Markov model, for the UE based on the states of discontinuous reception (DRX) mechanism, i.e., a power saving method in mobile communication networks. Explicit expressions are derived for transient and steady-state system size probabilities for the Markov model. For the semi-Markov model, steady-state probabilities are computed. Further, the performance measures such as mean and variance are computed for both models. Using these models, based on the states of DRX mechanism, energy saving in the UE is calculated. Finally, sensitivity analysis is performed in which the results obtained are compared for both models. Numerical results obtained in this paper ensure that energy saving can be maximized in the UE using the Markov modelling of DRX mechanism rather than semi-Markov modelling. The energy saving using the Markov model is atleast 33.19%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\%$$\end{document} more than the semi-Markov model. Also, for energy saving in the UE, the semi-Markov model for DRX mechanism is compared with the Markov model. The semi-Markov models for the DRX mechanism are available in the literature without considering the packet arrivals. Our analysis of DRX mechanism and conclusion on its performance can be designed and implemented to an extension for the existing DRX mechanism. We believe that, these models can also be extended to study the energy saving of hardware and other components of the system.

Article
With the continuous development of evolutionary computing, many excellent algorithms have emerged, which are applied in all walks of life to solve various practical problems. In this paper, two hybrid fish, bird and insect algorithms based on different architectures are proposed to solve the optimal coverage problem in wireless sensor networks. The algorithm combines the characteristics of three algorithms, namely, particle swarm optimization algorithm, Phasmatodea population evolution algorithm and fish migration optimization algorithm. The new algorithm has the advantages of the three algorithms. In order to prove the effectiveness of the algorithm, we first test it on 28 benchmark functions. The results show that the two hybrid fish, bird and insect algorithms with different architectures have significant advantages. Then we apply the proposed algorithm to solve the coverage problem of wireless sensor networks through experimental simulation. The experimental results show the advantages of our proposed algorithm and prove that our proposed hybrid fish, bird and insect algorithm is suitable for solving the coverage problem of wireless sensor networks.

Article
Rapid growth of the internet facilitates various facilities in everyday lifestyle, but intrusion becomes a significant threat in internet usage. Thus, the detection of intrusion is essential for smooth and secure communication in a network. In literature, many techniques have been proposed for the detection of intrusion. But those techniques either complex or fails to provide better performance in a big data application. Therefore, this paper proposed a novel Hybrid Mayfly Apriori-Intrusion Detection mechanism for effective intrusion detection in big data applications. In the proposed mechanism, Mayfly optimization based Apriori is used to detect the intrusion. Unlike conventional classification based intrusion detection, in the proposed mechanism, the network data processed to form an apriori rule based on frequent itemset. The infrequent itemset or transactions are marked as an intrusion. Comparison with established algorithms such as Artificial Neural Network, Random Forest, K-Nearest Neighbour and Support Vector Machine analyses the efficacy of the suggested mechanism. Ultimately, the proposed mechanism has shown its effectiveness by providing better results as 97% accuracy, 99% precision, and 97% recall. Thus, this mechanism is more suitable for intrusion detection in big data.

Article
Electronic health record (EHR) systems provide the platform that enables digital documentation of patients health information. Practically, EHR systems aid in delivering quality medical healthcare and limiting medical errors. However, EHR systems are associated with known technical and security challenges such as interoperability, confidentiality, authentication, auditability, and access control. To overcome these challenges, we first propose a new heterogeneous signcryption with proxy re-encryption (HSC-PRE) scheme. Secondly, via an example design, we demonstrate how our scheme can be utilized to achieve a secure, interoperable, auditable and accessible EHR system using blockchain technology. The blockchain technology is required to assure interoperability and auditability while the HSC-PRE assures confidentiality, authentication and access control. Via comprehensive security analysis (in random oracle model (ROM)), we affirm that the HSC-PRE scheme is secure. Besides, it shows up efficient against other recent related schemes.

Article
Mobile communication networks have entered a new age by introducing fifth-generation technologies (5G). The International Union of Telecommunications (IUT) proposes new core innovations and capabilities for 5G networks to meet the growing need for mobile broadband services. The requirements set by 5G for the enhanced Mobile BroadBand (eMBB) use case seem contradictory. It intends to increase the data rate, afford efficient spectrum usage, provide an excellent fairness level to all users, and reduce buffer size. Accordingly, these needs should be met to perform the expected quality of service. Besides, the scheduling algorithms existing in the field respond separately to the criteria mentioned earlier. For all these reasons, we opted for a multi-objective problem formulation to take all these constraints into account. This paper presents a multi-criteria scheduler for 5G eMBB communications transmitting in a dense urban environment. Our proposed solution combines the weighted sum multi-objective optimization and the perceptron's weights management deployed in neural networks. Moreover, a comparison study was carried out to assess the performance of the suggested algorithm. The comparative analysis proves that the algorithm developed in this paper provides the best performances for the enhanced mobile broadband use case and the scenario adopted.

Top-cited authors
• Ibb University
• Massachusetts Institute of Technology
• Universiti Kebangsaan Malaysia
• National Institute of Technology, Kurukshetra
• Intel Corporation, Penang, Malaysia