5G Communication Networks Research Articles

A security protocol for D2D communications in 5G networks using elliptic curve cryptography

Advancements in the field of wireless and mobile communication motivate academia, industry, and standardisation organisations to explore new technologies to improve overall efficiency, spectrum utilisation, power consumption, and security. One of the most essential technologies proposed for short-range communications, which will play a key role in 5G wireless networks, is device-to-device (D2D) communications. D2D communication enables direct communication between two devices when they are in close proximity without requiring the help of a fixed infrastructure like base stations. Despite the significant benefits provided by D2D communications, this new networking communication paradigm introduces unique security threats to D2D services that should be solved in order to limit any malicious attacks. Towards this end, in this paper, we focus on secure D2D communications and propose a protocol for establishing secure D2D communication using elliptic curve cryptography. The protocol utilises: (i) specific Mobile Identifiers acquired from the hardware of the mobile phone (i.e. IMEI) and the SIM card (i.e. IMSI, MSISDN) provided by the mobile operator and (ii) the SIM storage for saving private keys or signature data. The proposed security protocol is verified and validated with the help of the Scyther tool, and the performance is evaluated in terms of resiliency analysis.

Power Coordination based Efficient Resource Allocation for Device-to-Device Communication in 5G Networks

Device to device communication for mobile networks establishes connections between parameters of mobile devices. As the number of D2D connections and resources are increasing, optimization of power allocation and spectrum feasibility is required. Most of the proposed algorithm schemes for resource allocation support slow-moving D2D terminals in a cellular network, therefore causing huge amount of signaling loss and reducing the efficiency of the cellular network. In energy and spectrum efficiency for the wireless network to meet the power requirement in D2D communication for better resource allocation in upcoming 5G technology is required. The proposed approach outplays the older power distribution approach using MATLAB simulation. The optimal allocation of resources and spectrum can enhance the system throughput with resource allocation techniques. D2D nodes not only perform better frequency resources but also provide better energy-efficient communication by using power control.

Smart Grid based Wireless Communication in 5G Network for Monitoring and Control Systems in Renewable Energy Management

Wireless networks are becoming ubiquitous and as the cost of equipment decreases and performance increases, it becomes both economically and technologically feasible to deploy wireless networks in power systems and industrial environments for a wide range of applications. They have advantage of providing diverse controlling features through a unified communication platform. Application of such networks in the smart grid/industrial environments is under active research and expected to become an integral part of the power system. This research propose novel technique smart grid communication in wireless 5G networks for monitoring and controlling management. Here the smart grid designing has been done based on wireless communication networks. The smart grid network for renewable energy has been controlled using Stackelberg equilibrium based SCADA (supervisory control and data acquisition) method. The control method based collected data has been monitored for detection of malicious activities in the network using supervised radial basis fuzzy systems. The experimental analysis has been carried out based on control system and network malicious activities. Here the control system based parameters analysed are Scalability of 65%, QoS of 71%, Power consumption of 41%, Network Efficiency of 92%. Then machine learning based malicious activities detection in terms of accuarcy of 96%, network security of 88%, throughput of 94%, Network delay of 41%. Proposed method supports interoperability of multiple types of inverters, is scalable and flexible, and transmits data over a secure communication channel.

Energy Efficient Underlaid D2D Communication for 5G Applications

With the increasing importance of reduced-energy wireless communication in 5G networks, maximizing the energy efficiency of device-to-device (D2D) communication has gained a lot of research interest. But so far, the methods have only been able to address the single-cell scenario. This paper proposes an algorithm to improve the non-convex problem in underlaid D2D communication for multiple band scenarios. In 5G wireless communications, device to device is one of the methods used for achieving better energy efficiency. It also reduces the throughput latency. The optimization problem is formulated with a derivative algorithm and proposed modified derivative algorithm. Both the algorithms are compared, and this comparison shows that the modified derivative algorithm is more efficient than the derivative algorithm.

Device-to-Device Communication in 5G Networks

Device-to-device communication produces a new dimension in the mobile environment, easing the data exchange process between physically neighboring devices. 5G wireless networks are expected to carry large traffic volumes due to the growth of mobile devices and the increasing demand for high data rates from applications. Device to device communication is one of the suggested technologies to support this increasing load and enhance the capacity of networks. However, the implementation of D2D communication reveals many barriers that include communication scheduling, for which the architecture remains complex and obscure. The mobile operator’s action to collect the short-range communications for maintenance of the proximity-based services and improve the performance of networks drives the development of D2D. Through direct communication, device-to- device technology can increase the overall throughput, enhance the coverage, and reduce the power consumption of cellular communications There are popular low- level D2D techniques available for short- range wireless transmissions, such as Bluetooth and WiFi -Direct, and typically they use license-exempt bands. Most of the cellular technologies, however, do not support direct over-the-air communication between end users.

Multi‐layer neural network algorithm for vehicle‐to‐everything communication in 5G networks

SummaryInternet of Vehicles (IoVs), the emerging trend of Internet of Things (IoTs), has undoubtedly become a promising trend to improve communication among vehicles on the roads. Vehicle‐to‐everything (V2X) communication that is based on 5G technology enables vehicle users to communicate and collaborate with each other to enhance road traffic efficiency and safety. Owing to the increased traffic load and restricted resources of existing network substructure, a channel that responds to the latency and reliability needs of V2X communication must be designed. Thereby, several intelligent spectrum allocation techniques have been proposed to improve the system's overall effectiveness. In this paper, we discuss the spectrum sharing issue of V2X communication in Device‐to‐Device (D2D)‐based cellular networks. We propose a new multi‐layer neural network (MLNN)‐based Resource Allocation and sharing approach (MNNRA) for D2D‐based V2X communications. According to the main advantages of MLNN, the proposed algorithm takes several profits by improving system performance while reducing computational complexity. Numerical analysis is presented to approve the effectiveness of our proposed solution in terms of network sum rate, packet reception ratio, resource utilization ratio, and time complexity.

Holographic communication in 5G networks

Holographic communication refers to real-time capturing, encoding, transporting and rendering of 3D representations, anchored in space, of remote persons shown as stereoscopic images or as 3D video in extended reality (XR) headsets that deliver a visual effect similar to a hologram.

Optimal Resource Allocation Method for Device-to-Device Communication in 5G Networks

With the rapid development of the next-generation mobile network, the number of terminal devices and applications is growing explosively. Therefore, how to obtain a higher data rate, wider network coverage and higher resource utilization in the limited spectrum resources has become the common research goal of scholars. Device-to-Device (D2D) communication technology and other frontier communication technologies have emerged. Device-to-Device communication technology is the technology that devices in proximity can communicate directly in cellular networks. It has become one of the key technologies of the fifth-generation mobile communications system(5G). D2D communication technology which is introduced into cellular networks can effectively improve spectrum utilization, enhance network coverage, reduce transmission delay and improve system throughput, but it would also bring complicated and various interferences due to reusing cellular resources at the same time. So resource management is one of the most challenging and importing issues to give full play to the advantages of D2D communication. Optimal resource allocation is an important factor that needs to be addressed in D2D communication. Therefore, this paper proposes an optimization method based on the game-matching concept. The main idea is to model the optimization problem of the quality-of-experience based on user fairness and solve it through game-matching theory. Simulation results show that the proposed algorithm effectively improved the resource allocation and utilization as compared with existing algorithms.

On the Cost of Achieving Downlink Ultra-Reliable Low-Latency Communications in 5G Networks

We determine the cost of serving Ultra-Reliable Low-Latency Communications (URLLC) traffic (1 ms one-way latency, 99.999% reliability) in 5G New Radio (NR) Macro cellular networks. The cost is measured as the degradation of the enhanced Mobile Broadband (eMBB) downlink system capacity when serving a certain offered load of URLLC traffic on the same radio carrier. A methodology for assessing the cost of URLLC is presented, which takes into account all the aspects related to configuring a suitable resource allocation and link adaptation strategy, as well as the associated control channel overhead due to the use of mini-slots with very frequent control channel resources for monitoring downlink data assignments. When taking a holistic view on the performance, advanced system-level simulation results show that 1 Mbps of URLLC traffic results in an eMBB throughput reduction of up to 60 Mbps, i.e. URLLC traffic can be up to 60 times more costly than traditional best-effort. The presented results can be used by cellular service providers, such as operators, for understanding and dimensioning the tradeoffs and impact towards traditional network services when adding URLLC services to their portfolio.

Lyapunov optimization machine learning resource allocation approach for uplink underlaid D2D communication in 5G networks

AbstractDevice‐to‐device (D2D) communication plays a vital role in communication technologies with resource management and power control, which are the major issues for researchers in the era of 2020. In 5G networks, machine learning algorithms play a crucial role to manage these issues. In the proposed work, the problem is formulated for the uplink underlaid model of D2D communication. The Lyapunov optimization technique is utilized with a combination of machine learning techniques for resource allocation in D2D communication. First, the maximization of uplink and overall system capacity is formulated with resource management, which guarantees the signal to interference noise ratio for the D2D users. The optimization is a mixed integer non‐linear problem which uses the Lyapunov optimization method to optimize the bit error rate value and iterative algorithm to optimize the power value with different constraints. After attaining the optimized value, the support vector machine technique is utilized to ensure the spectral efficiency of an overall system in autonomous mode. Simulation results show that the proposed method provides higher reliability and power efficiency with higher system capacity in comparison to prevailing technologies.

Adaptive Relay Selection Scheme Based on Bayesian Inference (AS-BI) for Cooperative Communication in 5G Networks

In this paper, a Bayesian inference-based relay selection scheme, also called Adaptive Selection on Bayesian Inference (AS-BI) for cooperative networks in 5G networks is invoked. This scheme works on the principle of Amplify-and-Forward (AF) protocol which selects the most optimal relay towards the destination. This paper proposed a probabilitybased relay selection scheme in which posterior probability is calculated for the selection of relay node based on the prior and conditional probabilities. The proposed scheme has been accepted as optimal solution for relay selection, which significantly enhances the network performance by reducing (BER) for constant SNR.

Subtractive Gradient Boost Clustering for Mobile Node Authentication in Internet of Things Aware 5G Networks

The 5G mobile wireless network systems faces a lot of security issues due to the opening of network and its insecurity. The insecure network prone to various attacks and it disrupts secure data communications between legitimate users. Many works have addressed the security problems in 3G and 4G networks in efficient way through authentication and cryptographic techniques. But, the security in 5G networks during data communication was not improved. Subtractive Gradient Boost Clustered Node Authentication (SGBCNA) Method is introduced to perform secure data communication. The subtractive gradient boost clustering technique is applied to authenticate the mobile node as normal nodes and malicious nodes based on the selected features. The designed ensemble clustering model combines the weak learners to make final strong clustering results with minimum loss. Finally, the malicious nodes are eliminated and normal mobile nodes are taken for performing the secured communication in 5G networks. Simulation is carried out on factors such as authentication accuracy, computation overhead and security level with respect to a number of mobile nodes and data packets. The observed outcomes clearly illustrate that the SGBCNA Method efficiently improves node authentication accuracy, security level with minimum overhead than the state-of-the-art-methods.

LEES: a Hybrid Lightweight Elliptic ElGamal-Schnorr-Based Cryptography for Secure D2D Communications

Device-to-device (D2D) communications in 5G networks will provide greater coverage, as devices will be acting as users or relays without any intermediate nodes. However, this arrangement poses specific security issues, such as rogue relays, and is susceptible to various types of attacks (impersonation, eavesdropping, denial-of-service), due to the fact that communication occurs directly. It is also recommended to send fewer control messages, due to authenticity- and secrecy related prevailing requirements in such scenarios. Issues related to IoT applications need to be taken into consideration as well, as IoT networks are inherently resource-constrained and susceptible to various attacks. Therefore, novel signcryption algorithms which combine encryption with digital signatures are required to provide secure 5G IoT D2D communication scenarios in order to protect user information and their data against attacks, without simultaneously increasing communication costs. In this paper, we propose LEES, a secure authentication scheme using public key encryption for secure D2D communications in 5G IoT networks. This lightweight solution is a hybrid of elliptic curve ElGamal-Schnorr algorithms. The proposed scheme is characterized by low requirements concerning computation cost, storage and network bandwidth, and is immune to security threats, thus meeting confidentiality, authenticity, integrity and non-repudiation-related criteria that are so critical for digital signature schemes. It may be used in any 5G IoT architectures requiring enhanced D2D security and performance

Lagrange's multiplier based resource management for energy efficient D2D communication in 5G networks

Device to device communication is the predominantly renowned trait for the 5G network and IoT applications. In the work, proposed novel joint low power/energy efficient resource allocation with mode selection for the D2D communication underlay in-band with transmit power, interference, data rate constraints are investigated with formulation of a novel problem which integrates the three major modules (resource management, mode selection, and power management) of D2D communication into one. To achieve the low power/energy efficient resource allocation with mode selection, we formulate novel optimization problem with objective of maximizing the energy efficiency using the subtractive form method to solve fractional objective function and form an iterative algorithm. The formulated fractional optimization problem is transformed into min–max problem and solved by the Lagrange dual function with low transmit power, interference, data rate constraints as a lagrange multipliers via an iterative process to achieve the optimal low power. Numerical analysis exemplifies and validates the optimal low power and the energy efficient characteristics of the novel proposed algorithm with all constraints to ensure the quality of the communication for the D2D communication, 5G, and IoT applications with the industrial need of low power/energy efficient devices to promote the conservation of energy and green communication.

Energy-Efficient Device Discovery Mechanism for Device-to-Device Communications in 5G Networks

The conventional direct device discovery scheme which uses the random access protocol and encounters contentions or collisions is highly energy and time-consuming. To reduce the energy consumption of user equipments (UEs), this work proposes a two-phase hybrid device discovery mechanism for device-to-device (D2D) communications. In the first phase, the evolved packet core (EPC) or base station (BS) uses the location information of UEs to judge whether two UEs are able to establish a D2D link. In the second phase, UEs use Wi-Fi Direct to discover their target UEs. The BS directly assigns UEs’ states and allocates appropriate Wi-Fi channels to UEs. UEs no longer have to search or listen to all channels, thus reducing the discovery delay. The proposed mechanism saves cellular spectrum resources because it uses unlicensed bands for D2D discovery and communications. The performance of the proposed hybrid D2D discovery mechanism is also theoretically analyzed in this paper. Evaluation results show that the proposed D2D discovery mechanism has better performance in terms of energy consumption, discovery delay and discovery success rate, compared with the conventional direct D2D discovery scheme, especially in the network scenarios with smaller cells such as 5G networks. Additionally, the analytic results coincide with simulation results, demonstrating that our theoretic analysis is accurate.

Trusted and secured D2D-aided communications in 5G networks

The design of the forthcoming fifth generation (5G) system shall meet the severe requirement of managing an always increasing amount of traffic generated by both humans and machines, while guaranteeing data security. Among the enabling technologies that will turn 5G into a reality, Device-to-Device (D2D) and Multicasting will certainly play a key role because of their capability to largely improve network resources utilization and to address emerging use cases requiring the delivery of the same content to a large number of devices. D2D communications can help to improve traditional point-to-multipoint transmissions by reducing the multicast coverage area and exploiting properly selected relay nodes as data forwarders toward users with worse channel conditions. However, security issues are even more challenging for D2D connections, as data exchange happens directly between nodes in proximity. To enhance performance and security of delivered traffic in 5G-oriented networks, in this paper we design SeT-D2D (Secure and Trust D2D), according to which trustworthiness inferred from both direct interactions and social-awareness parameters is exploited to properly select relay nodes. Main contributions of our research consist in the introduction of a model for the assessment of network nodes’ trustworthiness and the implementation of security mechanisms to protect the data transmitted in D2D communications and the privacy of the involved users. The conducted simulation campaign testifies to the ability of the proposed solution to effectively select relay nodes, which leads to an improved network performance.

Securing Public Safety Communications on Commercial and Tactical 5G Networks: A Survey and Future Research Directions

The forthcoming communication networks for public safety authorities rely on the fifth generation (5G) of mobile networking technologies. Police officers, paramedics, border guards, as well as fire and rescue personnel, will connect through commercial operator's access network and rapidly deployable tactical bubbles. This transition from closed and dedicated infrastructure to hybrid architecture will expand the threat surface and expose mission-critical applications and sensitive information to cyber and physical adversaries. We explore and survey security architecture and enablers for prioritized public safety communication in 5G networks. We identify security threat scenarios and analyze enabling vulnerabilities, threat actors, attacks vectors, as well as risk levels. Security enablers are surveyed for tactical access and core networks, commercial infrastructure, and mission-critical applications, starting from push-to-talk and group video communication and leading to situational-awareness and remote-controlled systems. Two solutions are trialed and described in more detail: remote attestation enhanced access control for constrained devices, and securing of satellite backhauls. We also discuss future research directions highlighting the need for enablers to automate security of rapid deployments, for military-grade cost-effective customizations of commercial network services to ensure robustness, and for hardening of various types of public safety equipment.

LEGA: A Lightweight and Efficient Group Authentication Protocol for Massive Machine Type Communication in 5G Networks

LEGA: A Lightweight and Efficient Group Authentication Protocol for Massive Machine Type Communication in 5G Networks

Social-aware spectrum sharing for D2D communication by artificial bee colony optimization

Next-generation cellular networks must handle an increasing demand for data transmission resources, which requires the study of new technologies, such as Device-to-Device (D2D) communications. D2D expands the use of resources from a location perspective, and takes advantage of the geographical proximity of users to perform data transmission at high rates and low propagation delays. On the other hand, the widespread use of social networks establishes the degree of social relations among users and facilitates the efficient management of D2D communication networks. The integration of social networks and D2D communications into 5G networks has posed important challenges (e.g., exploitation of the social relationships of mobile users and management of interference and resources towards a better performance of D2D communications). This article proposes a social-aware Radio Resource Allocation (RRA) optimization solution for D2D communications in 5G networks that considers partial Channel State Information (CSI). A selected-NM Maximum Distance Ratio (MDR) q-bit feedback scheme designed reduces feedback overhead, since each D2D receiver sends only q-bit feedback CSI of N cellular User Equipment (CUE) and M D2D pairs with the largest MDR metric. The RRA problem is solved by an Artificial Bee Colony (ABC) algorithm for the obtaining of number of D2D connections in each evolved NodeB (eNB) and maximization of the system throughput.

Energy efficient power control for device to device communication in 5G networks

Next generation cellular networks require high capacity, enhanced energy efficiency and guaranteed quality of service (QoS). In order to meet these targets, device-to device (D2D) communication is being considered for future 5th generation especially for certain applications that require the proximity gain, the reuse gain, and the hop gain. In this paper, we investigate energy efficient power control for the uplink of an OFDMA (orthogonal frequency-division multiple access) single-cell communication system composed of both regular cellular users and device to device (D2D) pairs. Firstly, we analyze and mathematically model the actual requirements forD2D communications and traditional cellular links in terms of minimum rate and maximum power requirement. Secondly, we use fractional programming in order to transform the original problem into an equivalent concave one and we use the non-cooperative Game theory in order to characterize the equilibrium. Then, the solution of the game is given as a water-filling power allocation. Furthermore, we implement a distributed power allocation scheme using three ways: a) Fractional programming techniques b) Closed form expression (the novelty is the use of wright omega function). c) Inverse water filling. Finally, simulations in both static and dynamic channel setting are presented to illustrate the improved performance in term of EE, SE (spectral efficiency) and time of execution of the iterative algorithm (Dinkelbach) than the closed form algorithms.