D2D Connections Research Articles

Efficient machine learning‐based hybrid resource allocation for device‐to‐device underlay communication in 5G wireless networks

SummaryDevices in close proximity can directly communicate with each other through device‐to‐device (D2D) communication, bypassing the need for base stations. To minimize the delay for D2D active clients, we use a sequential approach to reuse cellular‐type resources. Unlike conventional methods that focus solely on uplink or downlink resource distribution, our study introduces a novel optimization technique to maximize network throughput. Our proposal incorporates a hybrid approach that combines both downlink and uplink techniques for resource allocation. We utilize random forest and game theory algorithms to ensure smooth D2D communication while reducing interference between cellular and D2D pairings. Our hybrid structure effectively addresses challenges arising from intra‐ and inter‐cell interferences resulting from spectrum reusability and deployment. This approach also improves power control and quality of service. Traditionally, NP‐hard optimization solutions are proposed for mixed‐integer nonlinear problems. In our study, the critical stages include channel assignment and energy allocation. The objective problem in resource allocation considers parameters such as the transmission power of D2D active clients, cellular users, connection distance, base stations, and quality of service constraints. Our proposed hybrid method aims to enhance overall spectrum efficiency and network throughput. Simulated results demonstrate the superiority of our modified hybrid technique compared to existing joint resource allocation methods. This comprehensive approach represents a significant advancement in addressing the complexities associated with D2D communication, offering improved efficiency and performance in contemporary network environments.

Methods of building fifth generation networks based on existing networks

This article discusses the development of a new approach to the creation of fifth generation (5G) communication networks. Various methods are used for this, such as teletraffic theory, mass service theory, optimization theory and simulation modeling. The basic idea is to use additional routers to create a network of D2D (Device-to-Device) connections, which allows for improved network efficiency. In addition, the article discusses methods of network clustering for better management and distribution of resources, as well as methods of choosing the location and number of transit nodes for optimal organization of the communication network. These studies are important for the further development of 5G technologies and ensuring better and more reliable communication in the future.

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.

Socially-Aware Energy-Efficient Task Partial Offloading in MEC Networks With D2D Collaboration

The future wireless network will face demands of massive connectivity and intensive computation with the increase of mobile devices. Mobile edge computing (MEC) and Device-to-Device (D2D) have emerged as promising technologies to address the above challenges, and implementing social relationships in D2D-MEC networks can improve the reliability of D2D links. Exploiting these benefits, we investigate the energy-efficient task offloading problem in socially-aware D2D-assisted MEC networks, where the user devices can offload tasks to the nearby device or further forward to the MEC server based on social relationships. Specifically, we design a task partial offloading scheme of joint D2D connection selection, transmit power control and task allocation, to maximize the long-term network utility with considering dynamic system status and random task arrival. First, the social relationship among users is quantified into a social trust matrix. As the formulated socially-aware energy-efficient problem is a long-term stochastic optimization problem that is directly intractable, we thus employ the Lyapunov optimization to transform it into a series of short-term problems, each of which can be solved by the Karush-Kuhn-Tucker method and a pricing-based matching algorithm. Finally, we verify the performance optimality and the long-term network stability through numerical simulations as well as theoretical analysis.

An adaptive social-aware device-to-device communication mechanism for wireless networks

Device-to-Device (D2D) communication is an essential element in 5G networks and beyond. It enables users to communicate either directly without network assistance or with minimum signaling through a base station. The enormous number of connected devices to the networks with high velocity of these users increases the complexity of establishing an effective and stable D2D connection when the user is moving among different available peers and modes in the network. So, the main objective for this research was to design an adaptive social-aware D2D communication mechanism to enhance the performance of D2D connection by improving procedures and efficiency of peer and mode selection. The mechanism consists of two schemes, namely the peer and mode selection schemes. The peer selection scheme includes two parts. Firstly, the peer evaluation is based on social choice theory through verifying the relationship between peers, and dividing the available peers into trusted peers and untrusted peers. The technical evaluation is based on HAW algorithm by including multi-attributes related to the connection quality to find the optimum trusted peer while excluding untrusted peers from the ranking. Secondly, the mode selection scheme evaluates the available modes based on the connection status while considering multi-attributes based on SAW algorithm to select and switch among available modes intelligently, based on the highest-ranking, to select the optimum mode. In this study, the proposed scenario considers the status of different numbers of users in the network to evaluate the proposed mechanism, and compared with two other recent approaches. The obtained results showed that the proposed mechanism outperforms other approaches in terms of delay, signal-to-noise ratio, delivery ratio, and throughput with better performance. It provides smooth switching between different modes and employs an automatic peering selection with trusted peers only.

The Design of User-Centric Mobile Crowdsensing with Cooperative D2D Communications

Ubiquitous sensor-rich smartphones have promoted MCS, an emerging people-centric sensing paradigm for urban IoT. However, using cellular networks to transmit the big data collected by MCS would incur expensive financial costs for both participating phone users and the MCS organizer. A promising solution to this is to integrate the low-cost D2D communication into the MCS design. However, using D2D in MCS will require cooperative interactions among self-interested and strategic participating phone users, which significantly complicates the “human-in-the-loop” MCS design in both the digital and human dimensions, and brings a branch of new challenges: data communication and networking become more complex; D2D connections among opportunistically encountered phone users must be secure, fast, and user-transparent; and participating phone users need to be properly incentivized. In dealing with these challenges, this article covers recent developments of D2D-enabled MCS from both the theoretical and practical perspectives. Future research questions in this rapidly growing field are also discussed.

A Fuzzy Method for Joint Resource Allocation and Stable Pairing in D2D Communications

In this paper, a device-to-device (D2D) communications multiple-metric scenario for resource allocation and pairing is studied. To improve the D2D connection stability, a fuzzy method based on the data rate and battery levels of potential D2D pairs is proposed in such a way that the set of D2D transmitters is considered as a fuzzy set. A single cell scenario with a cellular user and some co-channel D2D nodes consists of D2D receivers, and transmitters are taken into account. Furthermore, a stable fuzzy pairing criterion is proposed for the selection of the best D2D transmitter. The proposed method is compared with three other pairing methods named the maximum sum rate, constant pairing method, and random pairing method. The simulation results show that the mentioned pairing method outperforms the other three methods in terms of stability and fairness criteria and follows the maximum sum-rate method from the sum-rate criteria point of view.

A novel D2D\u2013MEC method for enhanced computation capability in cellular networks

Device-to-device (D2D) communications and mobile edge computing (MEC) used to resolve traffic overload problems is a trend in the cellular network. By jointly considering the computation capability and the maximum delay, resource-constrained terminals offload parts of their computation-intensive tasks to one nearby device via a D2D connection or an edge server deployed at a base station via a cellular connection. In this paper, a novel method of cellular D2D–MEC system is proposed, which enables task offloading and resource allocation meanwhile improving the execution efficiency of each device with a low latency. We consider the partial offloading strategy and divide the task into local and remote computing, both of which can be executed in parallel through different computational modes. Instead of allocating system resources from a macroscopic view, we innovatively study both the task offloading strategy and the computing efficiency of each device from a microscopic perspective. By taking both task offloading policy and computation resource allocation into consideration, the optimization problem is formulated as that of maximized computing efficiency. As the formulated problem is a mixed-integer non-linear problem, we thus propose a two-phase heuristic algorithm by jointly considering helper selection and computation resources allocation. In the first phase, we obtain the suboptimal helper selection policy. In the second phase, the MEC computation resources allocation strategy is achieved. The proposed low complexity dichotomy algorithm (LCDA) is used to match the subtask-helper pair. The simulation results demonstrate the superiority of the proposed D2D-enhanced MEC system over some traditional D2D–MEC algorithms.

Joint Resource Allocation for Device-to-Device Communication Assisted Fog Computing

In this paper, joint resource management for device-to-device (D2D) communication assisted multi-tier fog computing is studied. In the considered system model, each subscribed mobile end user can choose to offload its computation task to either an edge server deployed at the base station via the cellular connection or one nearby third-party fog node via the direct D2D connection. After receiving offloading requests from all end users, the network operator determines the optimal management of the fog computing system, including both computation and communication resource allocations, according to its service agreements with end users, energy cost of edge-server processing and total expense in renting third-party fog nodes. With the objective of maximizing the network management profit, a joint multi-dimensional resource optimization problem, integrating link scheduling, channel assignment and power control, is formulated. An optimal solution algorithm is proposed based on the idea of branch-and-price for addressing this complicated mixed integer nonlinear programming problem. To facilitate the practical implementation in large-scale systems, a suboptimal greedy algorithm with significantly reduced computational complexity is also developed. Simulation results examine the efficiency of the proposed D2D-assisted fog computing framework, and demonstrate the superiority of the proposed resource allocation algorithm over the counterparts.

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.

SAFE: A General Secure and Fair Auction Framework for Wireless Markets With Privacy Preservation

With the prosperity of wireless and mobile communications, the allocation of wireless resources, e.g., spectrum channels, femtocell access permissions, and resource blocks of D2D connections, has become a matter of great concern, which leads to the emergence and popularity of electronic auction. However, the lack of privacy protection and fairness guarantee in the existing market has posed great obstacles to user participation in electronic auctions. Without privacy protection, users will be worried about the unauthorized exposure of their commercial secrets, which may hurt their payoffs in the long run. Without fairness guarantee, selfish/malicious users may prematurely abort the auction to avoid unsatisfactory payment, thus causing loss to honest users and wasting system resources. Furthermore, the lack of fairness guarantee will incur an exchange dilemma, where mutually distrusting parties may refuse to initiate the goods/money exchange, hindering the market-clearing of auctions. Although extensive efforts have been made to develop privacy-preserving auction mechanisms for wireless markets, the fairness issue, to the best of our knowledge, has never been taken into account in the context of auctions. Moreover, a truly practical framework that can be applied to most mainstream auction formats is also missing in the literature. In this article, we present the first general framework, named SAFE, for representative auctions in (but not limited to) wireless markets. SAFE achieves a wide range of security goals with much higher efficiency than existing solutions. Furthermore, SAFE ensures auction fairness in a trust-free manner by developing a full set of carefully-designed modular protocols that can be easily adapted to any auction format. We implement the SAFE framework over a simulated Ethereum network. Extensive experimental results confirm that SAFE can indeed achieve high economic efficiency in terms of social welfare and participation satisfaction at very low computation and communication overheads.

Система вивантаження даних за технологією D2D у неліцензованому діапазоні частот у складі систем зв’язку 5G

With a constant increase in the number of users and the amount of data that they transmit among themselves, modern communication system networks cannot cope with the download. As an alternative to network compression, to increase the capacity of the network, mobile traffic is unloaded in the form of a direct connection D2D (device-to-device) between the equipment of users who are in close proximity to each other. Thus, D2D interaction is one of the most promising areas of development of communication systems, because it is becoming a new component in addition to the mobile network. It is important that this technology ensures the interaction of mobile network users without the use of a centralized infrastructure, which reduces its load. This interaction allows you to upload data streams from the mobile network to the D2D system, which can operate at unlicensed frequencies. As a result, the D2D system provides shorter connections for communications, increased energy efficiency and better traffic flow management. The development of D2D technology is a simple and reliable way to increase the bandwidth of mobile networks without the need to change its structure. But at the same time, several features arise that are related to the consideration of the interference and the distribution of radio channel resources. In this work, we consider a model of a D2D direct connection system with mobile support that serves streams of user data (sessions), as well as a way to control the downloading of traffic from mobile network to a D2D connection. The above theoretical and simulated results allow us to study communication system with the possibility of D2D interaction, to evaluate their capacity and energy efficiency. The presented mathematical approach takes into account the dynamics of user traffic in time and the placement of system nodes in space, which is confirmed by simulation results.

PageRank-Based Multi-Hop Computation Offloading in D2D Networks

In a D2D network, the tasks of a user device (UD) can be offloaded to other UDs to improve the UD’s performance. We propose a novel computation offloading scheme to efficiently alleviate the delay of task processing and the energy consumption of UDs. Inspired by PageRank algorithm, the strategies of computation offloading for UDs are determined by their steady ranking values, which reflect the overall influence of UDs’ performance in the network. Firstly, we model the network as a directed weighted graph, where the weight of each vertex is obtained by integrating the computing ability, battery energy, and available storage capacity of the corresponding UD, and the weight of each directed edge is obtained by integrating the data rates and potential interference of the D2D connection between the corresponding two UDs. Secondly, a power iteration algorithm, which satisfies Markov convergence, is designed to compute the steady ranking values of UDs. Finally, we design an algorithm to obtain one-hop strategies and multi-hop routing strategies for computation offloading among UDs. The superiority of our scheme is demonstrated in simulations and by comparisons.

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.

Probabilistic Cache Placement in UAV-Assisted Networks With D2D Connections: Performance Analysis and Trajectory Optimization

With the exponential growth of data traffic, caching is regarded as a promising solution to combine with unmanned aerial vehicle (UAV)-assisted networks, which can offload cellular traffic and improve the system performance. Moreover, the cache capacity at user side can be leveraged, e.g., through local data storage or device-to-device (D2D) sharing. In this paper, we focus on the performance analysis and trajectory optimization of cache-enabled UAV-assisted networks with underlaid D2D communications. We consider both static and dynamic UAV deployments. For static UAV deployment, we first formulate an optimization problem to design the cache placement in order to maximize the cache hit probability. Then, the successful transfer probability (STP) and sum-rate are analyzed by using stochastic geometry, and their closed-form expressions are derived. For dynamic UAV deployment, the UAV moves over the cell and stops at several path points to serve users. To shorten the time required for the UAV to cover all users, a spiral algorithm is proposed to optimize the UAV trajectory, aiming at minimizing the number of UAV path points. Moreover, since at different locations, the UAV communication will incur different interference on D2D users, we derive the outage probability for the D2D users. Simulation results show the significant performance gain of our proposed probabilistic cache placement over existing strategies. For a given user density, we show that the optimal values for the UAV height which lead to the maximum UAV-STP and sum-rate exist.

Smart Technique for Cache-Assisted Device to Device Communications

The emergence of smart terminals with the consequence of higher network traffic growth rates, has increased the demand for new techniques that are needed to meet user requirements for high-quality communication and social media services. One of these techniques is Device-to-Device (D2D) communication, allowing direct data transmission of popular files between users. This is an advantage during rush hours where there is no access to the traffic via a base station (BS), thereby reducing network loads. In this article, we propose a new caching paradigm for D2D communication to achieve the goal of rising network offloading. A Smart Adaptive Algorithm (SAA) is proposed that smartly selects users with higher probabilities of sharing more data, then places popular files in their cache. This is done to optimize network offloading at minimal consumed energy by the user (user cost), taking into account the user speed, location, predicted zones, interests, and the size of the requested file. The data offloading ratio is taken as a performance metric in evaluating network offloading. It is defined as the proportion of requested data that can be delivered via D2D links. The offloading ratio is calculated in different scenarios in order to assess the influence of proactive caching on core network load. To minimize the complexity of the algorithm, and to respond in a shorter time period to the number of requests, user demand shall be handled with both the base station and the user’s device application. For the simulation and implementation of the proposed algorithm, a human mobility model that predicts different human mobility behaviors is used. The simulation results reveal that the offloading ratio is significantly affected by the size of the file transmitted via D2D connection as well as the user speed. The amount of increase in the offloading ratio due to the increase in the user speed is based on the size of the files transmitted through D2D connection. The smaller files transmitted via D2D connection would result in a significant increase in the offloading ratio, whereas the larger file size would result in a less change in the offloading ratio for higher speed users. The simulation results also reveal that higher speed users share more data at a high bit rates compared to users with lower speeds. Simulation results also show that the proposed SAA has superior performance as compared to other algorithms available in literature.

Privacy Protection and Energy Optimization for 5G-Aided Industrial Internet of Things

The 5G is expected to revolutionize every sector of life by providing interconnectivity of everything everywhere at high speed. However, massively interconnected devices and fast data transmission will bring the challenge of privacy as well as energy deficiency. In today’s fast-paced economy, almost every sector of the economy is dependent on energy resources. On the other hand, the energy sector is mainly dependent on fossil fuels and is constituting about 80% of energy globally. This massive extraction and combustion of fossil fuels lead to a lot of adverse impacts on health, environment, and economy. The newly emerging 5G technology has changed the existing phenomenon of life by connecting everything everywhere using IoT devices. 5G enabled IIoT devices has transformed everything from traditional to smart, e.g. smart city, smart healthcare, smart industry, smart manufacturing etc. However, massive I/O technologies for providing D2D connection has also created the issue of privacy that need to be addressed. Privacy is the fundamental right of every individual. 5G industries and organizations need to preserve it for their stability and competency. Therefore, privacy at all three levels (data, identity and location) need to be maintained. Further, energy optimization is a big challenge that needs to be addressed for leveraging the potential benefits of 5G and 5G aided IIoT. Billions of IIoT devices that are expected to communicate using the 5G network will consume a considerable amount of energy while energy resources are limited. Therefore, energy optimization is a future challenge faced by 5G industries that need to be addressed. To fill these gaps, we have provided a comprehensive framework that will help energy researchers and practitioners in better understanding of 5G aided industry 4.0 infrastructure and energy resource optimization by improving privacy. The proposed framework is evaluated using case studies and mathematical modelling.

Outage Performance Improvement by Selected User in D2D Transmission and Implementation of Cognitive Radio-Assisted NOMA.

In this paper, we investigate the outage performance in secondary network of cognitive radio (CR) employing non-orthogonal multiple access (NOMA) wireless networks over Rayleigh fading channels. The considered system model adopts device-to-device (D2D) transmission together with traditional communication to form a new system model, namely CR-D2DNOMA network. The specific user is selected from multiple D2D-Tx users (D2Ds) to communicate with far NOMA users to form qualified D2D connection with assistance of the Relay user (). The main metric in such CR-D2DNOMA network needs to be considered and we particularly introduce the closed-form expressions for outage probability in the secondary network where it is designed to serve two far NOMA users. The perfect Successive Interference Cancellation (SIC) and imperfect SIC can be further examined at the second NOMA user who detects signal based on the ability of SIC. The results show the positive impact of increasing the fading parameters on the system performance. More importantly, numerical results are provided to verify the correctness of our derivations. Additionally, the effects of asymptotic expressions on insights evaluation are also further analyzed.

Dynamic Spectrum Algorithm Based on D2D Communication

Device-to-device (D2D) communication is a concept that promises the overall performance enhancement by allowing direct communication between the devices which are in proximity. The idea of implementing in-band and out-band spectrums together in a D2D assisted mobile users will be relevant to the landscape of the 5G networks. Nevertheless, limited research works are available on efficient transmission of the data when both spectrums are used simultaneously. In this paper, we propose an efficient dynamic spectrum that utilize the licensed and unlicensed bands, based on the distance between the D2D link, in such a way that it selects the best band for establishing the D2D links in the network. The proposed algorithm is based on the distance between the D2D link, where it selects the most efficient band that reduces the interference of the D2D connection and maximizes the network throughput. The simulation results show that the proposed algorithm, using dynamic spectrum, achieves a higher network performance compared with other static spectrums.

Multi-node D2D communications for wireless video delivery over cellular networks

Video service is one of the popular services among mobile users, which plays an important role in network traffic growth and owns the largest data traffic compared to other types of communications. Over the last few years, users’ considerable enthusiasm to watch live video streams has captivated the attention of researchers to the networks equipped with content saving devices. In these devices the video content is saved beforehand within the edge devices (small stations and smart devices) for fast delivery. In this study, we propose a new method for sending video content, based on Device-to-Device (D2D) communications and providing multi-relational and multi-user opportunities. Based on the random nature of the popularity of video content and the random requests from users on the network, the authors investigate the probability of sending content to multiple users using the random distribution of popularity of users simultaneously. In this method, several users’ requests are responded by a single transmission. Extensive simulations result of the proposed method reveals the significant effect of the random distribution of video content popularity and shows that using multi-link D2D connections can cause considerable improvements in the efficiency of the network in terms of the network throughput.