D2D Communication In 5G Networks Research Articles

A Weighted AIMD Congestion Control Algorithm for Device-to-Device Communication in 5G Network

ABSTRACT Device-to-Device (D2D) communication offers promising benefits in 5G networks in terms of improved throughput and reduced latency. However, efficient congestion control remains a critical challenge to ensure optimal performance and resource utilization. Existing congestion control mechanisms often struggle with adapting to dynamic network conditions, leading to inefficiencies, such as underutilization of network resources or excessive packet loss. This paper addresses these challenges by proposing a novel Weighted AIMD congestion control algorithm tailored specifically for D2D communication in 5G networks (WACC-D2DC-5GN). Here, the Weighted AIMD Congestion Control Algorithm is proposed for estimating available bandwidth and Hunger Games Search Optimization to optimize the weight parameter of WACC. The proposed algorithm integrates weighted factors that dynamically adjust congestion window sizes based on real-time network feedback. Simulations are run on the NS3-mmWave module, NS3 LTE-A module. The simulation outcomes show that the proposed WACC-D2DC-5GN method attains 27.26%, 20.41%, and 23.26% higher SNR and 16.20%, 26.97%, and 30.34% higher Throughput when analysed with existing techniques like NexGen D-TCP: next generation dynamic TCP congestion control approach (NGD-TCP-CCA), user-centric channel allocation system for 5G higher-speed users by using ML to decrease handover rate (UCC-HSU-MLA), and efficient with reliable hybrid deep learning-allowed method for congestion control in 5G/6G networks (HDL-EMC-CN) respectively.

A Novel Approach to Reduce Video Traffic Based on Understanding User Demand and D2D Communication in 5G Networks

Mobile network customers today prefer video news updates than text. However, the conventional cellular base stations may have challenges in simultaneously managing video transmission for all users, particularly in extensive network deployments. To address the aforementioned challenge discussed in this article, a proposed solution is presented. To lessen the burden of video traffic, we intend to improve the efficiency of D2D multicast network transmission in cellular D2D communications. A scalable video multicast strategy that accounts for user demand and makes use of device-to device (D2D) communication is offered as a means to this end. In the first step, we analyze the users' interests by looking at things like their video viewing habits and criteria like video popularity. The purpose of this research is to ascertain whether or not users are inclined to share movies, which would increase the number of viewers who receive multicast clusters. In the next stage, an algorithm for selecting cluster heads will be developed, taking into account criteria including channel quality, social metrics, and the requirements for video quality. In comparison to similar systems without multiplexing capacity, the proposed method exhibits superiority in three distinct aspects. The initial modification exhibits a surge ranging from 70% to 375 %. Furthermore, the overall growth rate of the entire system ranges from 32% to 64%. Furthermore, it is worth noting that there has been a significant rise of 90% in the number of network recipients, indicating a substantial boost in customer satisfaction.

Multi-Objective Binomial Scrambled Bumble Bees Mating Optimization for D2D Communication in 5G Networks

Device-to-Device (D2D) communication is a gifted component for 5G as it has two innate returns such as traffic reduction and consistent quality of services. Also, D2D is more elastic and efficient and exploits less power than other techniques. Few research works have been designed to provide better D2D communication but, providing maximum throughput is still a demanding one. A novel nature-inspired approach called Multi-Objective Binomial Scrambled Bumble Bees Mating Optimization (MOBSBBMO) technique is proposed to perform D2D communication with higher throughput and lesser loss rate. The MOBSBBMO technique uses multiple objective functions to obtain the optimal mobile device for D2D communication. First, the population (i.e. number of mobile devices) gets initialized arbitrarily. The fitness function is calculated for the number of mobile devices depending on multiple objectives such as energy efficiency, bandwidth capacity, and device cooperativeness. According to the fitness, tournament selection is applied to determine the optimal mobile device. If the fitness criterion is satisfied, then the mobile device is said to be optimal. The MOBSBBMO technique uses the binomial crossover applied to obtain broods by the mating process. Next, scramble mutation is employed to get the best drone bees. Yet, again the mating process is carried out to obtain the optimal solution for the best mobile device. The proposed MOBSBBMO technique is compared with benchmark methods in terms of throughput, data delivery rate, energy efficiency, packet loss rate, and latency. Simulation results show that the proposed MOBSBBMO can notably improve network throughput.

Data traffic reduction for D2D communications in 5G networks using a multilink approach

With the increase in the number of devices connected to the network and the increase in data rates, data traffic has also increased dramatically. This increase in traffic can lead to the development of network resources, increase in energy consumption and decrease in service quality. When compared to other forms of communication, video traffic is the most prevalent among mobile users and plays a significant influence in the expansion of network traffic. In recent years, networks containing content storage devices have caught the interest of academics due to users' exceptional desire to view live video feeds. In these gadgets, video content is pre-stored on edge gadgets (smart gadgets and small stations) for quick delivery. Device-to-device (D2D) communication technology, in which users receive their requests through a high-speed link and another device near them without a central station, is one of the proposed solutions to minimize traffic in 5G networks. The main areas of research in this field include the two approaches of traffic reduction and content storage. The multi-link communication approach is used in this study to evaluate the effectiveness of the system, and the findings contradict the results of previous research in this field. The proposed approach performs better than traffic reduction in similar systems without multicast support. First, there are 60% to 350% more links. Second, the average rate across the entire system increases by approximately 40% to 50%. Third: The number of satisfied recipients (satisfied users in the network) increases by about 90%. Therefore, the results of the findings show a significant improvement in how the content is distributed when the user shares it with multiple recipients. So that if we store the most visited files among users with different zeta coefficients in a content delivery network, we can make significant improvements in the system in terms of the number of possible links, the average rate in the system and the number of satisfied users, and ultimately reduce the traffic in Create a system.

Artificial Intelligence Assisted Enhanced Energy Efficient Model for Device-to-Device Communication in 5G Networks

Device-to-device (D2D) communications promise spectral and energy efficiency, total system capacity, and excellent data rates. These improvements in network performance led to much D2D research, but it revealed significant difficulties before their full potential could be realized in 5G networks. D2D communication in 5G networks can bring about performance gains regarding spectral and energy efficiency, total system capacity, and data rate. The major challenge in the 5G network is to meet latency, bandwidth, and traffic density requirements. In addition, the next generation of cellular networks must have increased throughput, decreased power consumption, and guaranteed Quality of Service. This potential, however, is associated with substantial difficulties. To address these challenges and improve the system capabilities of D2D networks, a deep learning-based Improved D2D communication (DLID2DC) model has been proposed. The proposed model is explicitly intended for 5G networks, using the exterior public cloud to replace automation with an explainable artificial intelligence (XAI) method to analyze communication needs. The communicated needs allow a selection of methodologies to transfer machine data from the remote server to the smart devices. The model utilizes deep learning algorithms for resource allocation in D2D communication to maximize the utilization of available spectrum resources. Experimental tests prove that the DLID2DC model brings about better throughput, lower end-to-end delay, better fairness, and improved energy efficiency than traditional methods.

Interference Mitigation Strategy for D2D Communication in 5G Networks

Device-to-Device (D2D) communication is one of the most promising developments in 5G networks. D2D communication can reduce communication latency and increase spectrum efficiency and system capacity. However, implementing D2D communication in reuse mode with a traditional cellular network can result in severe interference that can significantly reduce network performance, as both networks share the same resources. It is essential to mitigate interference to improve network capacity when D2D communication coexists with traditional cellular networks. An effective power control strategy can help mitigate the potential detrimental impact of interference and maximize the potential benefits of D2D communication. In this study, a dynamic transmission power control strategy was proposed for D2D transmitters to allow them to dynamically adjust transmission power, aiming to minimize interference and maximize network capacity. The distance between and the number of D2D pairs that experience interference were the primary parameters considered for the proposed strategy, while its complexity was in polynomial time. A simulation was carried out to evaluate the proposed strategy and compare it with fixed and ranged-based approaches, and the results validated its effectiveness.

Reinforcement Learning Based Efficient Power Control and Spectrum Utilization for D2D Communication in 5G Network

There are billions of inter-connected devices by the help of Internet-of-Things (IoT) that have been used in a number of applications such as for wearable devices, e-healthcare, agriculture, transportation, etc. Interconnection of devices establishes a direct link and easily shares the information by utilizing the spectrum of cellular users to enhance the spectral efficiency with low power consumption in an underlaid Device-to-Device (D2D) communication. Due to reuse of the spectrum of cellular devices by D2D users causes severe interference between them which may impact on the network performance. Therefore, we proposed a Q-Learning based low power selection scheme with the help of multi-agent reinforcement learning to detract the interference that helps to increase the capacity of the D2D network. For the maximization of capacity, the updated reward function has been reformulated with the help of a stochastic policy environment. With the help of a stochastic approach, we figure out the proposed optimal low power consumption techniques which ensures the quality of service (QoS) standards of the cellular devices and D2D users for D2D communication in 5G Networks and increase the utilization of resources. Numerical results confirm that the proposed scheme improves the spectral efficiency and sum rate as compared to Q-Learning approach by 14% and 12.65%.

Performance analysis in overlay-based cognitive D2D communications in 5G networks

With the advent of fifth-generation 5G networks, mobile communication data rates are steadily rising. The existing base stations (BSs) must reduce the loads with minimal cost and effort. With traffic demands constantly rising, available spectrum resources must be utilized effectively. One of the most exciting developments in 5G networks, particularly cellular networks, is the potential for devices to communicate directly with one another through a technology called device-to-device communication (D2D). With the transmission split between D2D users on one side and cellular users and the BS on the other, it will be effective in the rapidly expanding capacity and offload traffic from the BS. With the dynamic spectrum access in mind, this article proposes using cognitive radio direct-to-device (CRD2D) communication in 5G networks to make use of the unused spectrum. Throughput and latency are examined, for a carrier sense multiple access (CSMA) based medium access control (MAC) protocol that uses a common control channel (CCC) for device users to negotiate the data channel and to address contention among device users. Device users can take advantage of cognitive radio to access multiple data channels simultaneously in a shared interference zone. Since this property has not been utilized, in prior works, we use it to measure the possible delay and throughput. Cognitive radio capability applied to D2D communication and the allocation of a common control channel for device users significantly increases aggregated network throughput by more than 60% compared to individual D2D throughput without causing any harmful interference to cellular users. The wait time can also be scale back using this method.

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.

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.

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.

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.

Evaluation of D2D Communications in 5G Networks

5G networks are being tested today. 5G networks are capable of improving existing services and delivering new quality of service through low latency, such as tactile internet. Existing technologies do not meet the requirements of 5G, which necessitates the development of new technologies. These include new connectivity methods that depend on the quality of the network's functioning. One of the most famous D2D communications. 5G networks use millimeter-band technologies. As the radio signal energy of the millimeter range is strongly absorbed by the environment, this range has a short communication range, so a large number of base stations must be installed in the network. But this is not always effective as their use decreases. D2D device-to-device technology is used to solve this problem. In order to ensure a high quality of network service, attention must be paid to the structure of the D2D organization. The basic structural parameters are the communication distance, the communication radius and the number of repeaters. This can be solved by selecting the relay node correctly. For this purpose it is necessary to take into account the change of the allowed data rate in the channel due to the allocation of its resources by the network node, used as a repeater. In order for the route to provide the necessary bandwidth, it is necessary to change the distance between the network nodes. This ensures network connectivity and the required level of quality of service. This is achieved by choosing the optimal algorithm that is considered in the article.

Handover Management for D2D Communication in 5G Networks

This study addresses the handover management issue for Device-to-Device communication in fifth-generation (5G) networks. The Third Generation Partnership Project (3GPP) drafted a standard for proximity services (ProSe), also named device-to-device (D2D) communication, which is a promising technology in offering higher throughput and lower latency services to end users. Handover is an essential issue in wireless mobile networks due to the mobility of user equipment (UE). Specifically, we need to transfer an ongoing connection from an old E-UTRAN Node B (eNB) to a new one, so that the UE can retain its connectivity. In the data plane, both parties of a D2D pair can communicate directly with each other without the involvement of the base station. However, in the control plane, devices must be connected to the eNB for tasks such as power control and resource allocation. In the current standard of handover scheme, the number of unnecessary handovers would be increased by the effect of shadowing fading on two devices. More important, the handover mechanism for D2D pairs is not standardized yet. LTE-A only considers the handover procedure of a single user. Therefore, when a D2D pair moves across cell boundaries, the control channels of the two UEs may connect to different base stations and result in increased latency due to the exchange of D2D related control messages. Hence, we propose a handover management scheme for D2D communication to let both parties of a D2D pair handover to the same destination eNB at the same time. By doing so, the number of unnecessary handovers, as well as the handover latency, can be reduced. In the proposed method, we predict the destination eNB of D2D users based on their movements and the received signal characteristics. Subsequently, we make a handover decision for each D2D pair by jointly factoring in the signal quality and connection stability. Expected improvement can be attained, as revealed in the simulation. Unnecessary handover can be avoided. Consequently, both UEs of a D2D pair reside in the same cell and, therefore, result in increased throughput and decreased delay.

Towards Ensuring Reliability of Vehicular Ad Hoc Networks Using a Relay Selection Techniques and D2D Communications in 5G Networks

Benefiting from unlimited power supply, vehicular ad hoc networks (VANETs), in a 5G platform, can deal superiorly with the challenges of providing high reliability. As a prerequisite for ensuring reliability, reducing message delivery delay is pursued by improving the performance of message broadcast protocol. The amount of exchanged overhead to select a relay node, and the time consumed to forward a message are the two foremost factors in this regard. In the other hand, cognitive radio (CR) and device-to-device (D2D) communication techniques have been considered inherently in 5G to overcome bandwidth shortage, coverage limitation and excessive delay. So, in this article, we study some relay selection algorithms appropriate for 5G-VANET and classify them based on network reliability requirements. Considering the capabilities of CR and D2D communications in 5G-VANET, a method is proposed to select the farthest available node to forward a message without any need to exchange control messages with other vehicles. Unlike other existing works, we decrease the impact of control data overhead on network reliability in terms of message delivery hops and delay. Our simulation results show the proposed method can significantly increase network reliability by reducing message delivery delay, as well as the number of hops needed to deliver a message to the furthermost vehicles in a platoon.

Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

Device to Device (D2D) Communication is one of the technology components of the evolving 5G architecture, as it promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. The above noted improvements in network performance spearheaded a vast amount of research in D2D, which have identified significant challenges that need to be addressed before realizing their full potential in emerging 5G Networks. Towards this end, this paper proposes the use of a distributed intelligent approach to control the generation of D2D networks. More precisely, the proposed approach uses Belief-Desire-Intention (BDI) intelligent agents with extended capabilities (BDIx) to manage each D2D node independently and autonomously, without the help of the Base Station. The paper includes detailed algorithmic description for the decision of transmission mode, which maximizes the data rate, minimizes the power consumptions, while taking into consideration the computational load. Simulations show the applicability of BDI agents in jointly solving D2D challenges.

A Novel Access Control and Energy-Saving Resource Allocation Scheme for D2D Communication in 5G Networks

This paper investigates access link control and resource allocation for the device-to-device (D2D) communication in the fifth generation (5G) cellular networks. The optimization objective of this problem is to maximize the number of admitted D2D links and minimize the total power consumption of D2D links under the condition of meeting the minimum transmission rate requirements of D2D links and common cellular links. This problem is a two-stage nondeterministic polynomial (NP) problem, the solving process of which is very complex. So, we transform it into a one-stage optimization problem. According to the monotonicity of objective function and constraint conditions, a monotone optimization problem is established, which is solved by reverse polyblock approximation algorithm. In order to reduce the complexity of this algorithm, a solution algorithm based on iterative convex optimization is proposed. Simulation results show that both algorithms can maximize the number of admitted D2D links and minimize the total power consumption of D2D links. The proposed two algorithms are better than the energy efficiency optimization algorithm.

Incentive scheme for slice cooperation based on D2D communication in 5G networks

In the 5th generation (5G) wireless communication networks, network slicing emerges where network operators (NPs) form isolated logical slices by the same cellular network infrastructure and spectrum resource. In coverage regions of access points (APs) shared by slices, device to device (D2D) communication can occur among different slices, i.e., one device acts as D2D relay for another device serving by a different slice, which is defined as slice cooperation in this paper. Since selfish slices will not help other slices by cooperation voluntarily and unconditionally, this paper designs a novel resource allocation scheme to stimulate slice cooperation. The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput. The proposed incentive scheme for slice cooperation is formulated by an optimal problem, where cooperative activities are introduced to the objective function. Since optimal solutions of the formulated problem are long term statistics, though can be obtained, a practical online slice scheduling algorithm is designed, which can obtain optimal solutions of the formulated maximal problem. Lastly, the throughput isolation indexes are defined to evaluate isolation performance of slice. According to simulation results, the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively, and the isolation of slice is also simulated and discussed.

Virtual mesh networking for achieving multi-hop D2D communications in 5G networks

In 5G networks, when D2D communications or the quality of a cellular link fails to support data transmission of a terminal, it is indispensable to exploit data transmission opportunities via multi-hop D2D communications. However, to achieve multi-hop D2D communications, two problems need to be solved: 1) A routing and packet forwarding protocol is required to enable terminals to forward data packets across multi-hop D2D or cellular links; 2) This protocol must conform to the existing specifications of D2D communications. To this end, a framework of virtual mesh networking is developed in this paper to support multi-hop D2D communications in 5G networks. More specifically, based on the 5G network architecture, routing and packet forwarding are split into two separate mechanisms in the control plane and the user plane, respectively. In the control plane, base stations collect link and topology information of terminals and then form a virtual mesh network among terminals accordingly. The routing path for end-to-end communications is then determined by a virtual mesh routing algorithm, which also takes into account terminal mobility and link failure. In the user plane, a packet forwarding mechanism is designed to deliver data packets following the routing path as determined by the routing algorithm in the control plane. This mechanism extends but also conforms to the existing specifications of D2D communications. The virtual mesh networking protocol and its underlying algorithms are evaluated via simulations. Performance results demonstrate the effectiveness of multi-hop D2D communications via virtual mesh networking.

Enabling Trustworthy Multicast Wireless Services through D2D Communications in 5G Networks

Device-to-device (D2D) communication is considered as one of the key enabling technologies for fifth-generation (5G) networks as it allows data offloading generated by the huge number of connected devices. In this respect, group-oriented services are among the most interesting usage scenarios. Indeed, D2D can improve the performance of the conventional multicast scheme (CMS) in cellular networks, which is known to suffer from low spectral efficiency. Security is a further key field of investigation for 5G systems, as any threat to privacy and security may lead to both deteriorated user experience and inefficient network resources’ utilization. Security issues are even more in focus for D2D connections between devices that are in mutual proximity. To improve the CMS performance and also sustain security requirements of the 5G network, this work proposes a secure D2D data transmission algorithm. Making use of mechanisms such as encryption and signature, this algorithm aims to protect the exchanged data and the privacy of the devices involved in the communication. A simulation campaign conducted using MATLAB shows the ability of the proposed solution to take advantage of the establishment of secure D2D communications and efficiently utilize network resources.