Ultra-dense 5G Research Articles

An optimal siting and economically optimal connectivity strategy for urban green 5G BS based on distributed photovoltaic energy supply

The emergence of ultra-dense 5G networks and a large number of connected devices will bring with them significant increases in energy consumption, operating costs, and CO2 emissions. At the same time, the deployment of distributed photovoltaic (DPV) in megacities plays an important role in promoting the integration of “building-photovoltaic”, adjusting the city's clean energy supply system, and building a green, and low-carbon smart city. The development of a new “DPV-5G Base Station-Energy Storage (DPV-5G BS-ES)” coupled DC microgrid system and its pre-deployment investment costs are fundamental factors to be considered when the problem of large-scale DPV and BS deployment in cities has to be addressed. There are almost no published papers on this issue in the literature, which only consider the problem of maximizing the deployment of 5G BS service coverage or only perform optimization analyses for the performance of microgrid systems without considering the economic optimality and low-carbon green issues in the construction of urban utilities. In order to solve the problem of 5G BS deployment and economic optimization of topology in the “DPV-5G BS-ES” coupled DC microgrid system, a novel deployment strategy is proposed in this paper. The strategy is divided into: (a) The Geographic Information System (GIS) for extracting and analyzing 3D data from all buildings in the area. (b) A GIS-based formulation of a mixed integer quadratic constrained planning model (BSSCP) under discrete fixed radius coverage constraints is used to delineate building clusters within the area and determine the optimal deployment location of 5G BS under each sub-cluster. (c) An Improved Self-Organizing Mapping (ISOM) model combines GIS and microgrid performance parameters to address the economically optimal connection of grid lines for DPV in 3D space. (d) Simulation experiments were conducted for the power output and profitability of eight different PV panels and tracking systems to calculate the economically optimal type of DPV generation hardware. The experimental results show that the BSSCP model proposed in this study reduced the 5G BS deployment cost input by up to 35.8974 % compared to that of the control experimental model. Meanwhile, the ISOM model obtained an average reduction of 52.3741 % in the cost of connecting cables for the optimized 25 DPV planning and DC microgrid topology.

A Hyper Heuristic Algorithm for Efficient Resource Allocation in 5G Mobile Edge Clouds

Emergence of intelligent devices and mobile edge clouds (MECs) in 5G networks has exponentially increased the number of applications that demand low latency services. However, their resource heterogeneity, limited computing power and storage including congestion in the ultra-dense 5G network, make the real-time services challenging. Existing works are limited either by addressing application delay requirements or computational load balancing. This paper develops an efficient resource allocation framework for selecting optimal servers and routing paths in the 5G MEC network by jointly optimizing latency, computational, and network load variances. First, we formulate the above multi-objective problem as a mixed-integer non-linear programming problem. Further, we adopt a hyper-heuristic (AWSH) algorithm by leveraging the combined powers of <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> nt Colony, <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">W</b> hale, <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</b> ine-Cosine, and <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</b> enry Gas Solubility Optimization algorithms. The proposed AWSH algorithm works at the higher level, and it explores and exploits one of the three lower-level heuristics in each iteration to efficiently capture the dynamically varying environmental parameters and thereby address the resource allocation problem. Their collaborative effort helps to achieve a global optimum in allocating resources of 5G MEC network. Simulation results prove the superiority of the AWSH algorithm compared to state-of-the-art solutions in terms of service latency, successful offloading ratio, and load balancing.

Energy Management and Optimal Allocations of Resource in Ultra-dense 5G Networks Using OGDNG Theory with GWO Method

Energy Management and Optimal Allocations of Resource in Ultra-dense 5G Networks Using OGDNG Theory with GWO Method

XAuth: Secure and Privacy-Preserving Cross-Domain Handover Authentication for 5G HetNets

5G networks are highly heterogeneous, with ultradense base stations (BSs), due to the low penetration of millimeter waves and the availability of different access technologies. However, the continuous heterogeneity and densification of 5G networks pose great challenges to network security, especially for user mobility support. In the process of user handover between BSs or between different network domains, user access authentication and security session establishment are far riskier compared to 4G networks. On one hand, the overhead of handover authentication increases significantly as handovers become more frequent in an ultradense network. On the other hand, the differentiation of security schemes in heterogeneous networks poses a big challenge to handover authentication. Successfully designing a secure, privacy-preserving, and efficient handover authentication protocol for heterogeneous and ultra-dense 5G networks would substantially expand the prospects of future 5G network applications. Although numerous solutions (e.g., challengeresponse-based, public key cryptography-based, physical layer information-based, and blockchain-based solutions) have been proposed to solve the cross-domain handover authentication problem, most of them surfer from security and privacy vulnerabilities and unreasonable performance overhead. In this paper, we propose XAuth, a secure and privacy-preserving authentication protocol for both intra-domain and inter-domain handover in 5G Heterogeneous Networks (HetNets) based on blockchain. The proposed protocol can achieve mutual authentication, key agreement between User Equipment (UE) and target network, and is characterized by forward secrecy, backward secrecy, user anonymity, and conditional privacy preservation. Formal security analysis and comprehensive performance evaluation demonstrate the security and effectiveness of the proposed protocol.

Designing problem-specific operators for solving the Cell Switch-Off problem in ultra-dense 5G networks with hybrid MOEAs

Designing problem-specific operators for solving the Cell Switch-Off problem in ultra-dense 5G networks with hybrid MOEAs

Hybrid Learning based Radio Resource Management in 5G Heterogeneous Networks

Ultradensification using different types of small cells (SCs) is one of the key enabling solutions to meet the multiple stringent requirements of 5G cellular networks. However, radio resource management (RRM) in ultra-dense heterogeneous networks (HetNets) is not easy due to interferences in multi-tiered architecture and dynamic network conditions. Interferences in 5G HetNets can be efficiently managed only through the techniques which are adaptive and self-organizing to handle dynamic conditions in 5G HetNets. In this article, a machine learning (ML) based self-adaptive resource allocation scheme is proposed based on the combination of independent and cooperative learning and evaluated for ultra-dense 5G HetNets. The proposed scheme aims to improve the QoS of all users associated with different network tiers in ultra-dense HetNets simultaneously. The proposed solution adaptively optimizes the SCs transmit power either through independent learning or cooperative learning based on the varying density of small cells to minimize the interferences and ensure minimum QoS requirements for all users in different network tiers. The proposed scheme not only maintains the minimum required capacities for QoS provision to all users simultaneously but has also shown a significant improvement in the capacities of users in different network tiers in high interference scenarios as compared to the use of a single learning scheme.

Multiuser Computation Offloading for Long-Term Sequential Tasks in Mobile Edge Computing Environments

Mobile edge computing has shown its potential in serving emerging latency-sensitive mobile applications in ultra-dense 5G networks via offloading computation workloads from the remote cloud data center to the nearby network edge. However, current computation offloading studies in the heterogeneous edge environment face multifaceted challenges: Dependencies among computational tasks, resource competition among multiple users, and diverse long-term objectives. Mobile applications typically consist of several functionalities, and one huge category of the applications can be viewed as a series of sequential tasks. In this study, we first proposed a novel multiuser computation offloading framework for long-term sequential tasks. Then, we presented a comprehensive analysis of the task offloading process in the framework and formally defined the multiuser sequential task offloading problem. Moreover, we decoupled the long-term offloading problem into multiple single time slot offloading problems and proposed a novel adaptive method to solve them. We further showed the substantial performance advantage of our proposed method on the basis of extensive experiments.

Problem Statement for the Developing a New Training Course «5G Smart Antennas Technologies»

Interest in smart antenna technologies is due to the development of ultra-dense networks of the fifth 5G and subsequent B5G (Beyond 5G) generations of the millimeter-wave band (MMW, millimeter-wave – mmWave), which is confirmed by the high publication activity of recent years both in the native, and in foreign scientific community. Together with scientific publications in foreign literature, textbooks in this area are published and republished. At the same time, in the native scientific and methodological literature, there is currently no textbook that reveals new approaches to studying the issues of adaptive beamforming using smart antennas in relation to ultra-dense 5G and B5G networks. In this paper, an analysis of the state of the problem in the field of intelligent antennas is carried out and a task is formulated for the development of an appropriate training course. Subject of study. The article is devoted to a contemporary review of the state of the problem in the field of smart antennas based on the analysis of Russian sources. Method. Analysis of the evolution of the development of methods and means of smart antenna technologies. Main results. The result of this work is the setting of the task for the development of a new training course "Technologies of smart antennas 5G". Practical significance. The analysis carried out serves as a rationale for the relevance and necessity of developing a new training course "Technologies of smart antennas 5G".

Resilient Topology Design for Wireless Backhaul: A Deep Reinforcement Learning Approach

Ultra-dense 5G and beyond deployments are setting significant burden on cellular networks, especially for wireless backhauls. Today, a careful planning for wireless backhaul is more critical than ever. In this letter, we study the hierarchical wireless backhaul topology design problem. We introduce a Deep Reinforcement Learning (DRL) based algorithm that can solve the problem efficiently. We compare the quality of the solutions derived by our DRL approach to the optimal solution, derived according to the Integer Linear Program (ILP) formulation in our previous work. A simulation using practical channel propagation scenarios and different network densities proves that our DRL-based algorithm is providing a sub-optimal solution with different levels of resiliency. Our DRL algorithm is further shown to scale for larger instances of the problem.

A Clustered PD-NOMA in an Ultra-Dense Heterogeneous Network with Improved System Capacity and Throughput

In the current era of exponentially growing demand for user connectivity, spectral efficiency (SE), and high throughput, the performance goals have become even more challenging in ultra-dense 5G networks. The conventional orthogonal frequency division multiple access (OFDMA) tech-niques are mature but have not proven sufficient to address the growing user demand for high data rates and increased capacity. Therefore, to achieve an improved throughput in an ultra-dense 5G network with an expanded network capacity, the unified non-orthogonal multiple access (NOMA) technique is considered to be a more promising and effective solution. Throughput can be im-proved by implementing PD-NOMA, as the interference is managed with the successive inter-ference cancellation (SIC) technique, but the issue of increased complexity and capacity with compromised data rate persists. This study implements the clustered PD-NOMA algorithm to enhance user association and network performance by managing the users in clusters with fewer users per cluster with the implementation of the cooperative PD-NOMA within the clusters. In this study, we enhanced the user association in a network and ultimately improved the throughput, sum rate, and system capacity in an ultra-dense heterogeneous network (HetNet). By imple-menting the proposed clustered PD-NOMA scheme, the system throughput has improved by 23% when compared to the unified PD-NOMA scheme and 65% when compared to the OFDMA scheme with a varied number of randomly deployed users, along with an improvement in system capacity of 8% as compared to the unified PD-NOMA and almost 80% as compared to the conventional OFDMA scheme in a randomly deployed ultra-dense multi-tier heterogeneous network. Thus, we improved the network performance with the proposed algorithm and achieved increased capacity, throughput, and sum rate by outperforming the unified PD-NOMA scheme in an ultra-dense heterogeneous network.

QoS-aware hybrid cloudlet placement over joint fiber and wireless backhaul access network

Over the last decades, the emerging paradigms, e.g., centralized mobile cloud computing (MCC), multi-access edge computing (MEC), and collaborative computing offloading (CCO), have attracted extensive attention in adaptive 5G low latency communication for Tactile Internet. Besides, a novel integrated wireless optical transport network emerges in access networks and supports joint fronthaul and backhaul services. Therefore, considering that the task offloading response time, the needs of proximity, and the ultra-dense 5G small cell deployment, a novelty hybrid cloudlet deployment scheme over fiber and wireless backhaul-aware infrastructure is created with efficient cost optimization in mind. In this work, the envisioned Fiber Wireless networks (FiWi) consists of optical backhaul and wireless fronthaul (i.e., integrated access network and backhaul link), whereby base stations (BSs) with fiber and wireless backhauls are referred as wired-BS (WBS) and unwired-BS (UBS), respectively. Therefore, to meet the quality of service (QoS) delay constraints, cloudlets can be deployed in either UBSs, WBS, or remote node (RN). However, we apply mixed-integer line programming (MILP) to resolve the convex optimization problem in terms of minimization deployment cost. Besides, we describe the QoS-aware hybrid cloudlet placement cost algorithm for WBS and UBS coverage areas against different network conditions. It was shown through experimental measurements that the proposed architecture can achieve the scalability in different deployment scenarios. Also, the dependency of minimization cloudlet deployment cost on variable network parameters in terms of user density, network framework, and network QoS can be validated.

A sequential approach with machine in ultra-dense 5G D2D networks

A sequential approach with machine in ultra-dense 5G D2D networks

МОДЕЛИРОВАНИЕ СВЕРХПЛОТНЫХ СЕТЕЙ РАДИОДОСТУПА 5G С ДИАГРАММООБРАЗОВАНИЕМ

In this paper, we investigate the connectivity and probability of successful radio reception in the Poisson model of a 5G ultra-dense radio access network formed by devices with the possibility of location aware beamforming. The difference be-tween the proposed model and the existing prototypes is the complex account for the gains of devices, as well as the influence of radio wave propagation losses, slow and fast fading in the radio channel on the performance of the radio access network. The study is carried out for sessions of directional and omni-directional radio communication, and the beamforming mode is based on the preliminary positioning of neighboring devices. Mathematical modeling of a set of simultaneously operating radio lines in the Poisson model of an ultra-dense 5G radio access network makes it possible to estimate the gain in connectivity and the probability of successful radio reception when forming a beam based on preliminary positioning of devices in comparison with the case of omnidirectional antennas. The results of mathematical modeling of a ultra-dense radio access network with devices equipped with six-element circular antenna arrays showed a significant increase in connectivity indicators and the probability of successful radio reception in comparison with the case of omnidirectional antennas and confirmed the possibility of spatial multiplexing of simultaneous transmissions with a territorial separation of devices on 20% of the range of radio coverage based on the signal-to-noise ratio criterion. The result of the study is the establishment of the dependences of the connectivity and the probability of successful radio reception for an ultra-dense 5G radio access network, built on the basis of devices operating in the adaptive diagramming mode, as well as confirmation of the possibilities of spatial multiplexing of simultaneously operating transceiver devices with their territorial separation by 20% of the range of radio coverage based on the signal-to-interference ratio criterion. The obtained dependences of connectivity and the probability of successful radio reception allows to scientifically substantiate construction of an initial approximation of ultra-dense 5G radio access network from devices with the possibility of beamforming based on positioning, taking into account practical recommendations for their territorial diversity with an ultra-dense distribution.

Energy-Efficient Ultra-Dense 5G Networks: Recent Advances, Taxonomy and Future Research Directions

The global surge of connected devices and multimedia services necessitates increased capacity and coverage of communication networks. One approach to address the unprecedented rise in capacity and coverage requirement is deploying several small cells to create ultra-dense networks. This, however, exacerbates problems with energy consumption and network management due to the density and unplanned nature of the deployment. This review discusses various approaches to solving energy efficiency problems in ultra-dense networks, ranging from deployment to optimisation. Based on the review, we propose a taxonomy, summarise key findings, and discuss operational and implementation details of past research contributions. In particular, we focus on popular approaches such as machine learning, game theory, stochastic and heuristic techniques in the ultra-dense network from an energy perspective due to their promise in addressing the issue in future networks. Furthermore, we identify several challenges for improving energy efficiency in an ultra-dense network. Finally, future research directions are outlined for improving energy efficiency in ultra-dense networks in 5G and beyond 5G networks.

Evaluation of Interference in Ultra-Dense 5G Radio Access Networks with Beamforming

In this paper, we investigate the dependence of the level of intersystem interference&#x0D; on the beam width of the adaptively formed antenna radiation pattern and the territorial separation of neighboring devices in ultra-dense 5G radio access networks. The results of simulation modeling of a radio access network based on 19 base stations with the parameterization of the antenna array gain by the width of the radiation pattern in the horizontal plane show that when the base station beam is di-rected to the user device and narrowed from 360° to 5°, the level of intrasystem interference decreases by 15 dB compared with the case of omnidirectional antennas. The results of simulation&#x0D; of a radio access network based on 19 three-sector base stations with planar antenna arrays&#x0D; of 64 elements illustrate a significant reduction in the level of interference in comparison with the case of omnidirectional antennas and, in order to obtain zones of a positive signal-to-noise ratio, confirm the need for a territorial separation of neighboring devices by 10–20 % of the range of radio coverage.

FiVH: A solution of inter-V-Cell handover decision for connected vehicles in ultra-dense 5G networks

The Fifth Generation (5G) cellular network requires new solutions to new network requirements, for example, support for high-speed mobility. This paper presents a handover decision solution for connected vehicles to 5G Ultra-Dense Networks (5G-UDN). Its main goal is to treat high vehicular mobility and provide performance gains in handover for vehicles, since the densification of the cellular network causes, despite the expected capacity gain, difficulties in the cells selection, a greater number of failed and unnecessary handovers (ping-pong effect), longer delays and energy consumption, and high packet losses. The solution is based on Virtual Cells (V-Cells). The selection of the best cells is made based on complex network metrics to compose a V-Cell, as well as other criteria such as signal strength, distance, and speed. The solution relies on the Software-Defined Network (SDN) controller which has centralized network information. Simulations were conducted in Network Simulator, ns-3. The results show that the solution is effective in the treatment of vehicle handover.

Optimizing the ultra-dense 5G base stations in urban outdoor areas: Coupling GIS and heuristic optimization

Due to the high propagation loss and blockage-sensitive characteristics of millimeter waves (mmWaves), constructing fifth-generation (5G) cellular networks involves deploying ultra-dense base stations (BSs) to achieve satisfactory communication service coverage. However, ultra-densely deployed BSs are associated with extremely high construction and operation costs for 5G cellular networks. Reducing the construction cost and decreasing the energy consumption of BSs under the premise of ensuring the quality and coverage of services have become major challenges for the rollout of 5G technology. Essentially, the location optimization of 5G BSs can be regarded as a type of maximum coverage location problem (MCLP). Hence, this study coupled geographic information system (GIS) and a heuristic optimization algorithm to spatially explicit simulate the propagation of 5G signals and to optimize the service coverage of 5G BSs. The developed model was applied to search for the optimal solutions in 5G cellular network planning for an urban outdoor area in Wuhan, China. The optimal solutions and comparative experiments demonstrate that the proposed model can provide reasonable and robust results to support 5G cellular network planning. Therefore, this approach can help address the cost and energy consumption challenges faced in constructing 5G infrastructures and facilitate the rollout of 5G technology.

Dynamic Scheduler Management Using Deep Learning

The ability to manage the distributed functionality of large multi-vendor networks will be an important step towards ultra-dense 5G networks. Managing distributed scheduling functionality is particularly important, due to its influence over inter-cell interference and the lack of standardization for schedulers. In this paper, we formulate a method of managing distributed scheduling methods across a small cluster of cells by dynamically selecting schedulers to be implemented at each cell. We use deep reinforcement learning methods to identify suitable joint scheduling policies, based on the current state of the network observed from data already available in the RAN. Additionally, we also explore three methods of training the deep reinforcement learning based dynamic scheduler selection system. We compare the performance of these training methods in a simulated environment against each other, as well as homogeneous scheduler deployment scenarios, where each cell in the network uses the same type of scheduler. We show that, by using deep reinforcement learning, the dynamic scheduler selection system is able to identify scheduler distributions that increase the number of users that achieve their quality of service requirements in up to 77% of the simulated scenarios when compared to homogeneous scheduler deployment scenarios.

Interference Management, Backhaul Routing &amp; Switching off in 5G Hetnets with Mmwave Backhaul Links: A Relative Perspective

Today most of the next generation wireless communication systems(5G) faces the challenge of supporting the demands for higher data rates growing exponentially and ensuring to provide a stable quality of service (QoS) throughout the network. Over the next 2 years meeting up these requirements need to maximize the capacity of the network by a factor which will multiply it by thousands. Moreover, the most important societal as well as economical concerns include the power usage of data and communication technology industry and pollution mostly energy-related. On 5G two contrary requirements of providing capacity to support higher cellular networks along with consuming less energy needs to be focused upon. Due to the scarcity of spectral sources, a wide consensus can only be achieved by increasing significantly the number of antennas operating per unit area. Here a heterogeneous network named HetNet is analysed, comprising a macro base station (BS) along with several antennas and an overlaid dense tier possessing SCAs(small cell access points)through a wireless backhaul to get data traffic. The SCAs mostly associate with static as well as low mobility user equipment whereas macro BS serve the medium-to-high mobility. This work analyses the methods of the ultra-dense wireless 5G heterogeneous networks considering the interference management along the mm-Wave backhaul links to utilize the spectrum and network densification to operate mm-Wave 5G HetNet. The study reviews several literature works, their drawbacks and developing a joint model by combining base station switch-off technique with interface mitigation. This study further throws light on the scope of managing the backhaul-aware interference which in turn enhances potential capacity of the system and depending on the suitable backhaul the capacity is improved. Millimetre wave(mm-Wave) has proved to be a remarkable candidate to overcome the issue of ensuring a broad bandwidth having secure link transmission. The ultra-dense heterogeneous networks are discussed along with discussing the role interference management algorithms to minimize energy consumption. The importance of interference management is discussed along with discussing issues related. The research problem is formulated following a comparative analysis.

Skipping-based handover algorithm for video distribution over ultra-dense VANET

Next-generation networks will pave the way for video distribution over vehicular Networks (VANETs), which will be composed of ultra-dense heterogeneous radio networks by considering existing communication infrastructures to achieve higher spectral efficiency and spectrum reuse rates. However, the increased number of cells makes mobility management schemes a challenging task for 5G VANET, since vehicles frequently switch among different networks, leading to unnecessary handovers, higher overhead, and ping-pong effect. In this sense, an inefficient handover algorithm delivers videos with poor Quality of Experience (QoE), caused by frequent and ping-pong handover that leads to high packets/video frames losses. In this article, we introduce a multi-criteria skipping-based handover algorithm for video distribution over ultra-dense 5G VANET, called Skip-HoVe. It considers a skipping mechanism coupled with mobility prediction, Quality of Service (QoS)- and QoE-aware decision, meaning the handovers are made more reliable and less frequently. Simulation results show the efficiency of Skip-HoVe to deliver videos with Mean Opinion Score (MOS) 30% better compared to state-of-the-art algorithms while maintaining a ping-pong rate around 2%.