5G Mobile Networks Research Articles

Improving 5G network operations with Software-Defined Network Control

The fifth generation (5G) mobile network is being created to keep up with the Internet of Things (IoT) and the rapid expansion of communication technologies, which generate large amounts of data. This mobile network provides expanded communication features for cellular phones. However, there are limitations to this strategy. Programming Characterized Organization (SDN) technology is being developed as a basic solution to the problem of dealing with many devices running multiple administrations. In 5G portable organizations, SDN architecture improves adaptation, versatility, cost-effectiveness, and energy efficiency. Many alternative designs are often utilized to build the SDN control plane. For 5G networks, we analyze several setups and recommend using the. Controller management architecture for Logically Centralized-Physically Distributed (LC-PD) systems. This solution outperforms traditional control plane systems, delivering superior throughput and reduced latency. This study demonstrates how the LC-PD control plane architecture improves internet services' QoS and communication efficiency in 5G mobile networks. We conduct simulation experiments utilizing the Mini net-WIFI emulator. Our simulations show that the LC-PD control plane architecture increases the quality of service (QoS) compared to other SDN implementations of Internet services in 5G networks.

Privacy-Based Deployments: The Role of DevPrivOps in 6G Mobile Networks

Privacy-Based Deployments: The Role of DevPrivOps in 6G Mobile Networks

A Review on 5G Antenna: Challenges and Parameter Enhancement Techniques

The need for a high-speed mobile network has increased due to the COVID19 pandemic.5G is the newest and most sophisticated technology designed to handle the demands of the internet. The 5G network ensures connection security and simplifies mobile device connectivity to wireless devices. This paper explains every parameter related to 5G technology that has been covered in various papers. It addresses some of the difficulties that 5G technology faces. The development of Vivaldi, conformal, MIMO antennas satisfies the requirements of the 5G mobile network and presents opportunities to overcome obstacles. In the paper, MIMO antenna is discussed along with various techniques for enhancing its parameters, such as appropriate substrate selection, antenna element placement, and mutual coupling reduction. Different techniques like isolation, DGS, slot, metamaterial, neutralizing line, and frequency reconfigurations are explained under mutual coupling reduction techniques. A comparative analysis of various antenna feeding techniques is presented in the paper. The article provides details on how various parameters are affected by parameter enhancement techniques.

A comparative analysis of alpha-beta-gamma and close-in path loss models based on measured data for 5G mobile networks

Mobile coverage is crucial for the fifth-generation (5G) network since it affects the network's accessibility and dependability in various locations. With a wider coverage, more people and devices will access the 5G network, allowing them to experience the benefits and capabilities of this important technology. However, the development and construction of the networks need a lot of time and effort to maximize network coverage and service delivery while utilizing the fewest possible infrastructure components. Path loss models are commonly employed to predict network coverage. Therefore, it is expedient to adopt a path loss model that is suitable for the specified geographical area. In this paper, we investigated and analysed two empirical models: the Close-in free space reference distance (CI) model and the alpha-beta-gamma (ABG) model at the low- and mid-spectrum bands. Secondly, the path loss parameters were derived to characterize the two empirical models based on data from the measurement campaign. Finally, Root Mean Square Error (RMSE) was employed for the comparison of the models. It was found that at frequencies 0.9 and 1.8 GHz, the CI model's least RMSE values were 3.6 and 4.1 at location 1 and 4.7 and 4.2 dB at location 2, respectively, outperforming the ABG. However, at 3.4 GHz, the ABG with 3.25 and 1.75 dB outperformed the CI at both locations. For future work, the integration of machine learning techniques to dynamically predict and adapt path loss models in real time based on continuous data collection will be appropriate.

New indoor propagation model proposed for future B5G/6G rollout

Abstract The rollout of the fifth-generation (5G) mobile network was completed in 2020. Now, the focus shifts towards exploring the new perspectives of Beyond 5G (B5G) and 6G. Despite being a key enabler of 5G, millimeter wave technology has not yet been fully implemented due to various deployment challenges. Over the past decade, numerous efforts have been dedicated to modeling the propagation channel across the spectrum from 0.5 to 100 GHz. Propagation models such as Close-In (CI), Floating Intercept (FI), and single frequency Alpha-Beta-Gamma (ABG) have been extensively utilized. However, a significant deviation between co- and cross-polarization models has been observed in many estimated models in the literature. In this paper, we propose an optimization of the classic CI model by considering both TX and RX antenna heights, along with a correction coefficient. Initially, we estimate the propagation channel using the classic CI model in indoor environments, revealing a notable deviation between co- and cross-polarization models. Subsequently, we introduce a new model aimed at reducing this deviation and optimizing the Path Loss Exponent (PLE). With our proposed model, the estimated channel depolarization in Line-of-Sight (LOS) conditions stands at 2.8 dB, 5.6 dB, and 2.9 dB for room, corridor, and stairwell environments, respectively. In contrast, utilizing the conventional model yields channel depolarization figures of 4.8 dB, 8.2 dB, and 7 dB for the same environments. This disparity in channel depolarization can have significant implications for millimeter wave propagation, particularly during meteorological events such as rainfall.

A Comprehensive Overview of Network Slicing for Improving the Energy Efficiency of Fifth-Generation Networks.

The introduction of fifth-generation (5G) mobile networks leads to an increase in energy consumption and higher operational costs for mobile network operators (MNOs). Consequently, the optimization of 5G networks' energy efficiency is crucial, both in terms of reducing MNO costs and in terms of the negative environmental impact. However, many aspects of the 5G mobile network technology itself have been standardized, including the 5G network slicing concept. This enables the creation of multiple independent logical 5G networks within the same physical infrastructure. Since the only necessary resources in 5G networks need to be used for the realization of a specific 5G network slice, the question of whether the implementation of 5G network slicing can contribute to the improvement of 5G and future sixth-generation networks' energy efficiency arises. To tackle this question, this review paper analyzes 5G network slicing and the energy demand of different network slicing use cases and mobile virtual network operator realizations based on network slicing. The paper also overviews standardized key performance indicators for the assessment of 5G network slices' energy efficiency and discusses energy efficiency in 5G network slicing lifecycle management. In particular, to show how efficient network slicing can optimize the energy consumption of 5G networks, versatile 5G network slicing use case scenarios, approaches, and resource allocation concepts in the space, time, and frequency domains have been discussed, including artificial intelligence-based implementations of network slicing. The results of the comprehensive discussion indicate that the different implementations and approaches to network slicing pave the way for possible further reductions in 5G MNO energy costs and carbon dioxide emissions in the future.

A Lightweight CNN with LSTM Malware Detection Architecture for 5G and IoT Networks

Fifth-generation (5G) mobile networks are being deployed all over the world and researchers are concerned about the network's security against hacking. Researchers have focused heavily on this topic in recent years as new technologies attempt to integrate into numerous sectors of corporate and social organizations. Malicious software referred to as malware, is an unwanted application that attackers frequently use to execute online attacks. Advanced packing and obfuscation methods are being used by malware variants to continue their evolution. Due to several application features in 5G networks such as APIs, calls and SMS, it is difficult to detect and classify malware attacks. In a variety of research areas, deep learning (DL) techniques are effectively utilized to address malware-related solutions. Especially, convolutional neural networks (CNN) played a crucial role in the classification of malware detection in 5G networks and the Internet of Things (IoT). In this work, a lightweight CNN architecture with a sequential Long Short-Term Memory (LSTM) layer is developed for malware detection and classification trained on the Malimg dataset. The results prove that the proposed approach achieves 99.8% accuracy with an F1-score of 0.9925 for malware detection and outperforms state-of-the-art approaches in the literature. The classification performance is improved up to 12.8% and 14% in terms of accuracy and F1-score, respectively when compared with existing malware classification models.

Distributed Ledger Standards for 6G Mobile Networks

Distributed ledger technology, with its multitude of advantages including immutability, transparency, decentralization, and security, has excellent potential to promote and even revolutionize future 6G mobile networks. Large-scale distributed ledger deployment within or for mobile networks relies on distributed ledger-focused standards to facilitate and ensure interoperability. The European Telecommunications Standards (ETSI) Industry Specification Group (ISG) on Permissioned Distributed Ledger (PDL) develops PDL-related standards, targeting various application verticals, especially within the Information and Communications Technology (ICT) domain. This article aims to give an overview of ETSI ISG PDL and describes selected PDL standards, which have synergies with future 6G mobile networks.

Performance evaluation of Non‐Orthogonal multiple access system based on outage probability and power consumption

SummaryIn this growing world, the field of communication is developing quickly. The research community's attention is shifting to the design of networks beyond fifth generation (5G) and the sixth generation (6G) due to the rapid spread of the 5G mobile networks. Due to that, there will be a lot of traffic in the area, which will interfere with the channels and maybe produce noise. Nonorthogonal multiple access (NOMA) contributes to streamlined communication and a decrease in the possibility of interference. The communication will be encoded and decoded from transmitter to receiver utilizing the superposition coding (SC) and successive interference cancelation (SIC) approaches, ensuring the message's secrecy. This paper considers a simultaneous wireless information and power transfer (SWIPT)‐based cooperative NOMA system, where the nearby user to the source node acts as a relay to assist the far user. To further enhance the system performance, an improved golden search optimization (IGSO) is used to determine the best power allocation and power splitting coefficients by decreasing the outage probability. The existing models are compared with the proposed model in the results section regarding outage probability and throughput, where the proposed model outperformed all other existing models.

Novel Orthogonal Time Frequency Space Based on Universal Filter Multi Carrier for 6G Wireless Networks

Obtaining an efficient multicarrier signalling technique is an essential part in signal processing of the (6G) wireless networks. In order to achieve their intended objectives, the 6G mobile networks needs the utilization of a multicarrier scheme that possesses the ability to withstand multipath fading and inter-symbol interference (ISI), as well as exhibit resilience against inter-carrier interference (ICI) and Doppler spread. In recent research, several filter-based methods have been suggested, including Filter Bank Multicarrier (FBMC), as well as various Orthogonal Frequency Division Multiplexing (OFDM) based techniques such as Universal Filtered Multicarrier (UFMC). Orthogonal Time-Frequency Space (OTFS) technique has been identified as a promising candidate waveform for 6G, particularly in high-mobility scenarios, where it has demonstrated superior performance compared to traditional OFDM-based techniques. The OTFS method offers an advantage in that it can be considered the pre-and post-processing stages for techniques based on OFDM. This papaer presents the design (OTFS) using (UFMC) technique. Additionally, a novel structure is proposed for coded/uncoded UFMC-based OTFS technique, which combines the advantages of both strategies while mitigating their limitations. The results of our analysis demonstrate that the UFMC-based OTFS system exhibits superior performance in terms of error probability and time-spectral efficiency compared to the OFDM-based OTFS system.

Cost-efficient RAN slicing for service provisioning in 5G/B5G

Network slicing represents a substantial technological advance in 5G mobile network, greatly expanding the variety and manifoldness of network services to be supported. Additionally, 3GPP 5G New Radio (NR) has introduced novel features such as mixed numerology and mini-slots, which can be harnessed by network slicing to cater to the diverse requirements of 5G services. While however the co-existence of multiple network slices leads to a challenging resource allocation problem, these new features also severely complicate the management of radio resources. As a further point of attention, the virtualization of radio functions may exact a significant toll from the, already limited, computing resources at the network edge. It follows that a cost-efficient resource allocation across all the slices becomes crucial. In this paper, we address the above-mentioned issues by modeling a cost-efficient radio resource management in 5G NR featuring network slicing, named CERS, through a Mixed Integer Quadratically constrained Program (MIQCP). We maximize the profit of all slices simultaneously guaranteeing the target data rate and delay specified in the service level agreements (SLAs) fo the different traffic flows. To reduce the complexity of the MIQCP problem, we decompose it into two sub-problems, namely, the scheduling problem of enhanced Mobile Broadband (eMBB) user equipments (UEs) on a time-slot basis and of Ultra-Reliable Low Latency Communications (uRLLC) UEs on a mini-slot basis, while keeping the objective unchanged. To address the scheduling issue of eMBB UEs, we employ a heuristic technique, and, by leveraging the outcome of this heuristic, we derive an optimal solution for the problem of uRLLC UEs. The significance of the proposed approach over a baseline approach is evaluated through extensive numerical simulations in terms of the number of allocated uRLLC resource blocks (RBs) per mini-slot. We also assess our approach by measuring the impact of the uRLLC slice changes on the eMBB slice, and vice versa, including delay for uRLLC users and data rates for eMBB users.

A Multi-Layered Defence Strategy against DDoS Attacks in SDN/NFV-Based 5G Mobile Networks

Software-defined networking (SDN) and network functions virtualisation (NFV) are crucial technologies for integration in the fifth generation of cellular networks (5G). However, they also pose new security challenges, and a timely research subject is working on intrusion detection systems (IDSs) for 5G networks. Current IDSs suffer from several limitations, resulting in a waste of resources and some security threats. This work proposes a new three-layered solution that includes forwarding and data transport, management and control, and virtualisation layers, emphasising distributed controllers in the management and control layer. The proposed solution uses entropy detection to classify arriving packets as normal or suspicious and then forwards the suspicious packets to a centralised controller for further processing using a self-organising map (SOM). A dynamic OpenFlow switch relocation method is introduced based on deep reinforcement learning to address the unbalanced burden among controllers and the static allocation of OpenFlow switches. The proposed system is analysed using the Markov decision process, and a Double Deep Q-Network (DDQN) is used to train the system. The experimental results demonstrate the effectiveness of the proposed approach in mitigating DDoS attacks, efficiently balancing controller workloads, and reducing the duration of the balancing process in 5G networks.

Organic 6G networks: ultra-flexibility through extensive stateless functional split

With the increase in hardware performance, the 5G mobile network architecture shifted from physical components to software-only micro-services. The very modular network functions can be deployed flexibly on commodity hardware. However, the extensive modularity of these network functions is increasing the number of managed entities, and the core network request latency. Also, it requires extensive procedures to be able to re-select the components for specific devices, a fundamental condition for a potential system scale-down. In this paper, we propose a new organic 6G network architecture that handles these challenges through a new functionality split based on the experience of IT software services. Furthermore, we provide an analysis based on main 5G procedures, showing that the newly proposed architecture is handling the re-selection of functionality significantly better, which is a cornerstone of high-speed scaling (especially scaling-out), as well as migration of functionality and users.

The effect of urban environment on large-scale path loss model’s main parameters for mmWave 5G mobile network in Iraq

Abstract The high speeds resulting from the use of millimeter waves (mmWave) in 5G mobile networks are accompanied by high path loss. The issue of generating a reliable propagation model of radio waves is crucial to the development of cellular networks since it reveals essential information regarding the properties of the wireless channel. The received signal strength, the coverage area, and the outage probability in certain places may all be determined through theoretical or empirical radio frequency propagation models, which offer essential valuable information regarding signal path loss and fading. This work analyzes a comprehensive three-dimensional ray-tracing method at 28 GHz for Najaf city, Iraq. The optimum path loss model for the city of Najaf is evaluated using the close-in (CI) model. On average, the values of the main parameters of CI model n n , X σ CI {X}_{\sigma }^{{\rm{CI}}} accomplished, respectively, 3.461866667 and 11.13958333. The lowest achievable path loss exponent was 3.0619 across all analyzed scenarios, while the highest possible value was 4.1253. The results of this work can serve as a baseline for mmWave measurement campaigns conducted in comparable conditions, and they provide a new avenue for future research into mmWave at 28 GHz in Iraq.

Performance analysis of massive MIMO using various transmit precoding schemes for a wireless network

SummaryAn evaluation of various transmit precoding schemes is proposed in this thesis on basis of spectral efficiency (SE) of massive MIMO (m‐MIMO) system in 2 GHz spectrum. The present generation of wireless networks must be rethought due to the rapidly rising user base, huge volume data transfer, wide coverage requirement, and exponential rise in data rate. 5G mobile network includes a multi‐fold increase in network capacity, energy conservation, decreased latency, higher coverage probability, and a seamless connection. m‐MIMO has provided good solution for enhancing the data rate with the coverage, overcoming the effects of multipath fading and has also increased diversity of the system. Massiveness of MIMO system along with 5G network is the key technology to address the issue of SE, throughput, improvement of QoS (quality of service), coverage probability, power delay profile, diversity simulation, energy efficiency, and improvement in bit error rate. Parameters such as SE, throughput, and coverage probability are important for any communication system, and their improvement can increase overall capacity of cellular network system and could meet the requirement of upcoming demand for mobile network. The research paper is focused on performance analysis of m‐MIMO with reference to the SE of various transmit precoding schemes. Simulation results show that SE provided by M‐MMSE (multi‐cell minimum mean‐squared error) technique of precoding ranks highest for the same number of antennas and pilot reuse factor as compared to other schemes.

Case studies for binary decision diagram for 5G mobile networks optimization

In this paper, we study the binary decision diagrams and mobile network optimization. As we see about the binary decision diagrams, Lee and Akers first introduced the general concept of binary decision diagrams but later spread by Bryant. It turns out that, according to the European Interactive Digital Advertising Alliance (EDAA) order and reduction rules, binary decision diagrams are a standard form of representation. After that, we study the spanning trees and binary decision diagrams. An advantage of binary decision diagrams-based methods is that binary decision diagrams provide a concise and separate description of system success or failure. The effectiveness of binary decision diagram methods is measured by the size of them, which depends heavily on the selected series.

Blockchain-enabled authentication framework for Maritime Transportation System empowered by 6G-IoT

In recent years, Maritime Transportation Systems (MTS) have experienced significant advancements through the adoption of Internet of Things (IoT) technology. The introduction of 6G mobile networks has further expanded possibilities by offering enhanced communication services and additional functionalities such as processing, caching, sensing, and control for a wide array of IoT devices. Despite these technological advancements, the integration of IoT and 6G has introduced new risks and challenges in terms of safety and reliability. The involvement of various maritime stakeholders in scheduling and managing marine transportation exacerbates these challenges. Moreover, the MTS has encountered escalating security and privacy concerns with unauthorized data access and message tampering pose significant vulnerabilities in the 6G-IoT-enabled MTS environment. Therefore, a shared and controlled access mechanism that cannot be manipulated or tampered with by unauthorized parties is also an essential requirement in MTS. To address these issues, this paper presents an authentication framework leveraging blockchain technology, specifically designed for 6G-IoT-enabled MTS. The objective is to handle real-time data using decentralized peer-to-peer cloud servers with minimal latency, all while addressing security and privacy concerns specific to MTS. This integration also serves to mitigate various security threats. The protocol’s security and privacy are verified through rigorous evaluations, including the ROR model, Scyther tool, and informal security analysis. A simulation of the proposed protocol using MIRACL is conducted, offering a comprehensive assessment of its computational costs and security features when compared to existing protocols, demonstrating its superior security and efficiency.

Risk-Aware Continuous Control with Neural Contextual Bandits

Recent advances in learning techniques have garnered attention for their applicability to a diverse range of real-world sequential decision-making problems. Yet, many practical applications have critical constraints for operation in real environments. Most learning solutions often neglect the risk of failing to meet these constraints, hindering their implementation in real-world contexts. In this paper, we propose a risk-aware decision-making framework for contextual bandit problems, accommodating constraints and continuous action spaces. Our approach employs an actor multi-critic architecture, with each critic characterizing the distribution of performance and constraint metrics. Our framework is designed to cater to various risk levels, effectively balancing constraint satisfaction against performance. To demonstrate the effectiveness of our approach, we first compare it against state-of-the-art baseline methods in a synthetic environment, highlighting the impact of intrinsic environmental noise across different risk configurations. Finally, we evaluate our framework in a real-world use case involving a 5G mobile network where only our approach satisfies consistently the system constraint (a signal processing reliability target) with a small performance toll (8.5% increase in power consumption).

Dominance of Smartphone Exposure in 5G Mobile Networks

The deployment of 5G networks is sometimes questioned due to the impact of ElectroMagnetic Field (EMF) generated by Radio Base Station (RBS) on users. The goal of this work is to analyze such issue from a novel perspective, by comparing RBS EMF against exposure generated by 5G smartphones in commercial deployments. The measurement of exposure from 5G is hampered by several implementation aspects, such as dual connectivity between 4G and 5G, spectrum fragmentation, and carrier aggregation. To face such issues, we deploy a novel framework, called <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5G-EA</small> , tailored to the assessment of smartphone and RBS exposure through an innovative measurement algorithm, able to remotely control a programmable spectrum analyzer. Results, obtained in both outdoor and indoor locations, reveal that smartphone exposure (upon generation of uplink traffic) dominates over the RBS one. Moreover, Line-of-Sight locations experience a reduction of around one order of magnitude on the overall exposure compared to Non-Line-of-Sight ones. In addition, 5G exposure always represents a small share (up to 38%) compared to the total one radiated by the smartphone.

Impact of 5G on Internet of Things and its Challenges

In this era of rapid technological growth, the Internet of Things (IOT) refers to a system of interrelated, internet-connected objects that are able to collect and transfer data over a wireless network without human intervention. We see the IOT as billions of smart, connected things (a sort of ―universal global neural network in the cloud) that will encompass every aspect of our lives, and its foundation is the intelligence that embedded processing provides. The IOT is comprised of smart machines interacting and communicating with other machines, objects, environments and infrastructures. As a result, huge volumes of data are being generated, and that data is being processed into useful actions that can ―command and control things to make our lives much easier and safer—and to reduce our impact on the environment. The creativity of this new era is boundless, with amazing potential to improve our lives. The following thesis is an extensive reference to the possibilities, utility, applications and the evolution of the Internet of Things. The rollout of commercial 5G cellular networks has commenced, marking a significant milestone in the adoption of 5G and the Internet of Things (IoT). This adoption is propelled by various factors, such as rising consumer and enterprise demands, coupled with the availability of cost-effective devices. Notably, substantial investments by operators in 5G technology, spectrum allocation, and infrastructure development, alongside the establishment of global standards, are key drivers fuelling growth and generating heightened market interest in the IoT. The substantial investments made by operators in 5G technology, spectrum allocation, and infrastructure, coupled with the adoption of global standards, play a pivotal role in stimulating growth and generating heightened market interest in the Internet of Things (IoT). The ongoing evolution of 5G mobile cellular networks, derived from existing 4G frameworks, underscores their adaptability to diverse use cases, both present and future-oriented. With a forward- looking approach, 5G infrastructure is poised to address current demands like smart energy applications while proactively accommodating forthcoming innovations such as autonomous vehicles. In navigating this technological transition, mobile operators face the challenge of ensuring that their networks remain adept at supporting a spectrum of present and future use cases. Strategic investment management is imperative for operators to seamlessly transition their networks to 5G while upholding the continuity of service for their customers Key Words: Scalability, safety, security, rapid growth, interoperability, devices, interconnections, 5G with Internet of things, healthcare, smart city