5G Network Architecture Research Articles

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.

Single Valued Neutrosophic HyperSoft Set based on VIKOR Method for 5G Architecture Selection

This work introduces the framework for selecting architecture in 5G networks, considering various technological, performance, economic, and operational factors. With the emergence of 5G technology, the architecture selection process has become pivotal in meeting diverse requirements for ultra-high-speed connectivity, low latency, scalability, and diverse service demands. The evaluation comprehensively analyses different architecture options, including centralized, distributed, cloud-based, and virtualized architectures. Factors such as network performance, scalability, cost-effectiveness, security, and compatibility are considered within a multi-criteria decision-making framework. Findings reveal each architecture option's diverse strengths and limitations, emphasizing the importance of aligning architectural choices with specific use cases, deployment scenarios, and business objectives. We used the concept of multi-criteria decision-making (MCDM) methodology to control the various criteria. We used the single-valued neutrosophic set (SVNS) to deal with vague and inconsistent data. The SVNS is integrated with the hyperSoft set. The proposed methodology uses a single-valued neutrosophic hyperSoft set (SVNHSS) to select the best 5G architecture. We used the VIKOR method as an MCDM method to rank the alternatives. The proposed framework provides stakeholders with a structured methodology to evaluate and prioritize architecture options, facilitating informed decision-making in the complex landscape of 5G network deployments.

Deep Reinforcement Learning Based Reliable Data Transmission Scheme for Internet of Underwater Things in 5G and Beyond Networks

The Internet of Underwater Things (IoUT) is an interconnected communication ecosystem for underwater devices in maritime environments. IoUT devices range from seabed sensors to ships and boats in oceans which help in diverse practical applications of underwater information ranging from marine transportation, navigation, and underwater exploration to disaster prevention with intelligent monitoring. There exist significant obstacles within the present architecture of the IoUT. This article proposes three distinct methodologies aimed at enhancing the robustness and reliability of the communication architecture for 5G and future networks. Firstly, the employment of the Deep Reinforcement Learning approach is advocated for the identification of anomalies and faulty sensors. Secondly, energy consumption is identified as a crucial factor for IoUT devices. To address this concern, the integration of renewable energy sources, namely oxygen rechargeable batteries, with nano-generators is employed. This integration allows for the replenishment of the batteries through the harnessing of kinetic energy from water. Thirdly, the process by which information can be efficiently transmitted from IoUT sensors located on the seabed to the final terrestrial network is delineated, with an emphasis on minimizing the number of hops required. Additionally, a case study is presented, focusing on the mitigation of interference within the IoUT. Lastly, the article delves into the various research challenges and unresolved matters that persist within the realm of IoUT.

Software Defined Networking Controller (SDNC): a robust security architecture for SDN-based 5G networks

The efficacy of Wireless Sensor Networks (WSNs), a subset of Wireless Ad-hoc Networks, is significantly impacted by application, lifetime, storage capacity, processing power, topology changes, communication medium, and bandwidth. These constraints necessitate a robust data transport control in WSNs that considers service quality, energy efficiency, and congestion management. Congestion is a significant issue for wireless networks. Congestion in WSNs has deleterious effects on loss rate, channel quality, link utilization, number of retransmissions, traffic flow, network lifetime, latency, energy, and throughput. The predominance of WSNs necessitates the development of more efficient congestion control algorithms. Since it has been demonstrated that the routing problem is NP-hard and that heuristic-based methods outperform their traditional counterparts, routing is one of the most prevalent techniques for reducing the energy consumption of nodes and increasing throughput in WSNs. This study presents Rate Aware Congestion Control (RACC), an efficient method for avoiding congestion that improves network performance by employing Modified Harris Hawks Optimisation (MHHO). Initially, nodes are clustered utilizing the DBSCAN clustering algorithm. The simulation results of the developed technique indicate superior service, low latency, high energy, a high packet delivery ratio and an increasing number of living nodes when compared to existing approaches.

Complex security architecture in 5G networks based on the construction of domains of trust

The article discusses key approaches to building a security system in 5G networks. It is determined that the security architecture in 5G networks is based on the use of 3G and 4G technologies in combination with new protocols and functions. It is shown that the list of vulnerabilities of 5G networks expands due to decentralization, which creates an opportunity to attack the computing resources of local devices, which are a priori less protected than the central nodes of the network core. The concept of building trust domains, which allow building complex protection taking into account the possibility of attacks at different levels, has been studied.

Resource orchestration in 5G and beyond: Challenges and opportunities

5G networks have strict constraints regarding the services in terms of latency, reliability, and availability, which pose additional challenges to the traditional orchestration solutions, and 6G networks will increment the number of slices and services deployed over different technological domains, adding more difficulties for the orchestrator. Distributed and automated solutions will be essential for this context. This article identifies the main challenges in 5G/6G orchestration and then describes the utility of Artificial Intelligence-driven solutions, outlining an orchestrator architecture for 5G networks. The architecture is then explored as an orchestration solution for two ongoing research projects focused on the deployment of critical services over 5G networks.

An efficient packet parser architecture for software-defined 5G networks

Software-defined networks (SDN) has emerged with the capability to program in order to enhance flexibility, management, and testing of new ideas in the next generation of networks by removing current network limitations. Network virtualization and functionalization are critical elements supporting the delivery of future network services, especially in 5G networks. With the integration of virtualization and functionalization, network resources can be provisioned on-demand, and network service functions can be composed and chained dynamically to cater to various requirements. 5G networks are expected to rely heavily on SDN, which has been widely applied in core network design. To have a software-defined 5G network, not only is new spectrum and interface needed from SDN, but also a programmable and efficient hardware infrastructure is required. Admittedly, hardware components and infrastructure play an important role in supporting 5G networks. In other words, the software-defined 5G network data plane must have the required flexibility and programmability to support upcoming needs and technologies. Technological solutions need to respond to actual requests in infrastructure. Packet parsers in the data plane of software-defined 5G networks are one of the most important components because of the variation in the type of network headers and protocols. Each SDN switch needs to identify headers for processing input packets in the data plane, where the packet parser operates. Multiple implementations of packet parsers have been done on different substrates that occupy large hardware resources and areas on chip. However, they are not suitable for software-defined 5G networks. Certain architectures have been presented for packet parsing, aimed at accelerating the process of header parsing, however no attention has been paid toward reducing the area and the volume of the needed hardware resources and programmability in the data plane. This paper presents a new and efficient architecture for packet parsers on Field Programmable Gate Arrays (FPGA), called Efficient FPGA Packet Parser (EFPP) in a designed software-defined 5G network. This architecture emphasizes the removal of Ternary Content Addressable Memory (TCAM) to decrease hardware resources and efficiency in the data plane. Moreover, this architecture uses the chip’s processing speed and reconfiguration capabilities to support new protocols and network headers while maintaining flexibilities on software-defined 5G networks. EFPP is applied to chips on FPGA Xilinx ZedBoard Zynq, and the resources consumed around 7.5% LookUp Table, 1.9% Flip-Flops, and 5.8% of the memory. EFPP was also more area efficient. According to our results, EFPP would reduce the area and volume of hardware compared to other peer works.

A New Optimization Technique in Massive MIMO and LSAS using Hybrid Architecture and Channel Estimation Algorithm for 5G Networks

Massive Multiple Input Multiple Output (m-MIMO) or Large Scale Antenna System (LSAS) is the latest version of cellular network technology with the purpose to send data from the base station to different users. The huge determined expansion in the mobile equipment and data rate requirement has created the rigid necessity for future wireless communication networks. The m-MIMO envisages a significant increase in the capacity but at the verge of excessive hardware complication. In this paper, we put forward a less complex precoding scheme based on the hybrid architecture to achieve a performance higher than the conventional baseband Minimum Mean Square Estimation (MMSE) precoding. In this paper, we propose a precoding schema namely amplitude and phase MMSE (APMMSE) to attain the performance of traditional MMSE precoding. The informed greedy best-first search has offered to estimate the baseband precoding matrix. It formulates the amplitude of the baseband precoder. Radio Frequency Precoder modifies the phase and provides an optimal signal-to-interference -noise ratio SINR and thus improves spectral efficiency of hybrid architecture.

Smart Contracts in the 5G Roaming Architecture: The Fusion of Blockchain with 5G Networks

The rollout of fifth generation (5G) cellular network technology has generated a new surge of interest in the potential of blockchain to automate various use cases involving cellular networks. 5G is indeed expected to offer new market opportunities for small and large enterprises alike. In this article, we introduce a new roaming network architecture for 5G based on a permissioned blockchain platform with smart contracts. The proposed solution improves the visibility for mobile network operators of their subscribers' activities in the visited network, as well as enabling quick payment reconciliation and reducing fraudulent transactions. The article further reports on the methodology and architecture of the proposed blockchain-based roaming solution using the Hyperledger platform.

BLOCKCHAIN-BASED NETWORK FUNCTIONS VIRTUALIZATION FOR 5G NETWORK SLICING

The paper proposes a new blockchain-based network architecture for 5G network functions virtualization. By using a combination of AI and blockchain technologies, proposed system provides flexible network deployment, interoperability between different mobile network operators and effective management of radio resources. Experimental testbed of the proposed system has been implemented by using cloud and edge computing infrastructure and software defined radio peripheral NI USRP 2900. Simulation results of the network slicing and radio resource management shows that proposed system is able to double the capacity of the physical network infrastructure, while ensuring the target quality of service for all users.

Next Generation 5G Mobile Health Network for User Interfacing in Radiology Workflows

5G is the next-generation mobile cellular network that offers significant advantages over other wireless network technologies, such as data throughput, latency, real-time multicasting, ad hoc peer-to-peer, and data encryption, to name a few. A critical sector for potentially disruptive 5G solutions is healthcare and its current IoMT infrastructure. This paper analyses the current pain points associated with the general radiology workflow for X-ray imaging in terms of user interfaces and network technologies. By understanding this workflow and the modern 5G technology standards, we have designed a system-level architecture for a private 5G network within a hospital that includes additional services over the core and a different architecture for telecommunication networks. In addition, we have designed a lower-level architecture for a 5G collimator interfacing use case, with a network protocol stack designed for use case realization. With these 5G architectures implemented, a new, novel radiology workflow, was visualized, with clear benefits arising from the 5G innovations highlighted. We also highlighted the resulting limitations of the current design and outlined the next development steps and hypothesized future visions.

A QoE-Aware Energy Supply Scheme over a FiWi Access Network in the 5G Era.

Integrated fiber-wireless (FiWi) should be regarded as a promising access network architecture in future 5G networks, and beyond; this due to its seamless combination of flexibility, ubiquity, mobility of the wireless mesh network (WMN) frontend with a large capacity, high bandwidth, strong robustness in time, and a wavelength-division multiplexed passive optical network (TWDM-PON) backhaul. However, the key issue in both traditional human-to-human (H2H) traffic and emerging Tactile Internet is the energy conservation network operation. Therefore, a power-saving method should be instrumental in the wireless retransmission-enabled architecture design. Toward this end, this paper firstly proposes a novel energy-supply paradigm of the FiWi converged network infrastructure, i.e., the emerging power over fiber (PoF) technology instead of an external power supply. Then, the existing time-division multiplexing access (TDMA) scheme and PoF technology are leveraged to carry out joint dynamic bandwidth allocation (DBA) and provide enough power for the sleep schedule in each integrated optical network unit mesh portal point (ONU-MPP) branch. Additionally, the correlation between the transmitted optical power of the optical line terminal (OLT) and the quality of experience (QoE) guarantee caused by multiple hops in the wireless frontend is taken into consideration in detail. The research results prove that the envisioned paradigm can significantly reduce the energy consumption of the whole FiWi system while satisfying the average delay constraints, thus providing enough survivability for multimode optical fiber.

Software Defined Network-Based Management for Enhanced 5G Network Services

Due to the fast development in communication technology and the emerging usage of Internet of Things (IoT) devices that produce a huge amount of data, the fifth generation (5G) mobile network is introduced to support this development. This mobile network can provide many advanced communication features in cellular phones. But unfortunately, this technology faces many challenges. One of its defective challenges is the management of a massive number of devices running different services, so Software Defined Network (SDN) is proposed as a key technology to overcome this drawback. SDN architecture provides higher flexibility, scalability, cost-effectiveness, and energy efficiency in 5G mobile networks. There are usually different architectures for the SDN control plane. We study some of these architectures, and we conciliate the usage of Logically Centralized-Physically Distributed (LC-PD) controller management architecture in 5G networks. This architecture enables providing higher throughput, and lower latency compared to other control plane architectures. In this paper, we focus on the demonstration that the LC-PD control plane architecture improves communication efficiency and the Quality of Services (QoS) of running internet services in the 5G mobile network. We use the Mininet-WIFI emulator in our simulation tests. Our conducted simulations show that employing the LC-PD control plane architecture in 5G networks enhances the QoS of Internet services compared to other SDN implementations.

An Authenticated Key Exchange Protocol for Multi-Server Architecture in 5G Networks

Currently, the popularity of the Internet of Things (IoT) has brought about an increase in the amount of data, so multi-server distributed cloud computing has been widely used in various applications that have brought convenience to our daily lives. At the same time, the development of the fifth generation (5G) of mobile communication technology has gradually become the main driving force for the popularization of the IoT. Because the 5G network is a heterogeneous network with multiple servers and small cells, the mutual authentication protocol under multiple servers is also applicable to the 5G network environment. However, much of the data will have serious storage and security issues during transmission. Aiming at the security issues in a multi-server (M-S) architecture, in 2018, Wu et al. proposed an authentication protocol in a distributed cloud environment. They claimed that their protocol is secure and resistant to various known types of attacks. However, we found that their protocol does not guarantee perfect forward secrecy (PFS) and suffers from privileged insider (PI) attacks. Such attacks will cause data to be out of sync. Therefore, we improved Wu et al. ’s protocol and proposed an improvement in the 5G network environment. Finally, we performed a security analysis on the proposed protocol, including the automatic encryption protocol tool ProVerif, BAN logic, and informal security analysis, which proved that our protocol is secure. Compared with similar existing schemes, we have proved the efficiency of the scheme and achieved higher security standards.

Fast Switching With VM Migration in 5G Cloud Radio Access Networks

Cloud radio access network (C-RAN) is an important architecture for 5G networks. In C-RAN systems, baseband units (BBUs) are centralized in a BBU pool and remote radio heads (RRHs) are connected with the BBU pool through front-haul links. The BBU-RRH peer switching scheme is quite a key point in C-RAN especially for fast switching scenarios. A typical C-RAN system based on software defined radio (SDR) and virtual machine migration is introduced as the system model. Then we analyze the factors, including packet delay, and power consumption, that influence the performance of a C-RAN system. We conclude backlogs, idle computation resources, and switching costs could reflect the system performance adequately. They can evaluate radio resource usage, computation resource usage, and extra computation resource usage, respectively. Based on the evaluation model, the optimization algorithm is studied. In this paper, we propose a method to find the optimized load range for the BBUs. Taking switching quality into consideration, we propose a scheme that can adjust the BBU working load dynamically in an optimized range with less switching cost. The system performance variation under different switching intervals is also investigated. Finally, the effectiveness of the proposed optimization scheme is validated by simulation results.

A Cloud-Enabled Small Cell Architecture in 5G Networks for Broadcast/Multicast Services

The evolution of 5G suggests that communication networks become sufficiently flexible to handle a wide variety of network services from various domains. The virtualization of small cells as envisaged by 5G, allows enhanced mobile edge computing capabilities, thus enabling network service deployment and management near the end user. This paper presents a cloud-enabled small cell architecture for 5G networks developed within the 5G-ESSENCE project. This paper also presents the conformity of the proposed architecture to the evolving 5G radio resource management architecture. Furthermore, it examines the inclusion of an edge enabler to support a variety of virtual network functions in 5G networks. Next, the improvement of specific key performance indicators in a public safety use case is evaluated. Finally, the performance of a 5G enabled evolved multimedia broadcast multicast services service is evaluated.

A Robust Security Architecture for SDN-Based 5G Networks

5G is the latest generation of cellular mobile communications. Due to its significant advantage in high data rate, reduced latency and massive device connectivity, the 5G network plays a vital role in today’s commercial telecommunications networks. However, the 5G network also faces some challenges when used in practice. This is because it consists of various diverse ingredients, termed heterogeneity. The heterogeneity of the 5G network has two consequences: first, it prevents us to use this technology in a uniform way, preventing the wide use of 5G technology; second, it complicates the structure of the 5G network, making it hard to monitor what is going on in a 5G network. To break through this limitation, researchers have worked in this field and design their own protocol, in which software-defined networking (SDN) is one key design concept. By separating control and data plane, SDN can make the 5G network functional and programmable, such that we can handle the heterogeneity in traditional 5G networks. In light of this, we say that SDN-5G network is attractive, but its advantages are not free. The intelligence centralization used in SDN has its own drawbacks when it comes to security. To break through this limitation, we propose a robust security architecture for SDN-based 5G Networks. To find the illegal request from malicious attackers, we add extra cryptographic authentication, termed synchronize secret. The basic idea of our scheme is leveraging preload secrets to differ attacks from regular network communications. The simulation results indicate that our work can completely handle the security problem from SDN with a low disconnect rate of 0.01%, which is much better than that from state of the art.

Novel QoE monitoring and management architecture with eTOM for SDN-based 5G networks

The 5th Generation (5G) network design is still under exploration and will require an innovative approach to network monitoring and management with a relentless focus on customer needs. Among the recent technologies, software-defined networking (SDN) and network functions virtualization (NFV), which are already offering network programmability and automation, have been proposed to improve resource management in 5G systems. Furthermore, the enhanced telecom operations map (eTOM) can be used to manage both End-to-End (E2E) service and end-customer experience. In this paper, we illustrate a novel SDN-based architecture for 5G networks that will be able to enhance quality-of-experience (QoE) monitoring and management by integrating SDN and eTOM. This architecture is deployed and evaluated by simulations of a service-level agreement (SLA) verification scenario. As a result, the implemented platform is capable of identifying SLA violation and can successfully enforce suitable mechanisms to dynamically adjust network parameters, thereby satisfying the SLA constraints.

Performance evaluation of millimeter wave 5G networks for variable antennas configurations

In this paper, two scenarios have been considered for millimetre wave base station configuration. In the first scenario, the approach of Distributed Base Station (DBS) with remote radio units (RRU) is chosen as the envisioned architecture for future 5G network. This approach is compatible with cloud radio access network (C-RAN), as it has easier scalability and compatibility with future network expansions and upgrades. RRU has been used in this work as a way to sidestep the limited coverage and poor channel condition, which characterise millimetre wave band. This will minimise the number of required sites installation for the same quality of service (QoS). The results of this approach have shown significant improvements in terms of User Equipment (UE) throughput, average cell throughput, and spectral efficiency. In the second scenario, optimising antenna element spacing is considered in the base station array. The results show significant improvement in the network performance and provide better performance for cell-edge users in terms of data throughput.

An Energy-Efficient Collaborative Caching Scheme for 5G Wireless Network

CCN (Content-centric network) has emerged as a promising architecture for future 5G network due to its in-network caching capability and receiver-driven content retrieval paradigm. Recently, the explosive increase in energy consumption driven by the rapid growth of network traffic has become a fundamental issue in CCN and caused widespread academic concern. In this paper, we proposed an energy-efficient scheme for the future 5G network. The aim of our scheme is to minimize the energy consumption by considering some important constraints, including limited storage, content popularity, placement and access to contents. Our proposed scheme provides efficient utilization of hotspot cache, minimizing transportation cost by using Zipf and knapsack which ensure local availability of cache contents and minimizing energy consumption. Finally, simulation results reveal that our proposed scheme outperform in term of saving energy, the impact of content popularity, cache size, placement, and device-to-device communication.