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This work analyzes the effect of positioning small cells (SC) on an existing heterogeneously scattered macro cellular (MC) network. The impact of SC deployment based on the planned blend of K-means and user density (KUD) algorithms on an existing MC network is explored. With an application of the Cox process, heterogeneous and uneven distributions of 50 and 100 users were generated for investigation. The simulated outcomes and plotted graphs illustrate a gradual increment in the average user throughput, sum rate, and energy efficiency with the overlaying of 8 SCs using the proposed KUD algorithm in an existing MC. [ABSTRACT FROM AUTHOR]

The ubiquitous proliferation of small cells (SCs) is for boosting system capacity, coverage, and quality of services (QoS) for smart applications. However, interference from the adjacent SCs is inevitable due to their dense deployments — satisfying the low signal-to-interference-plus-noise ratio (SINR) regime. In this paper, we quantify the minimum interference constraint (IC) for SCs, which is critical for the multiplexing gain in the low SINR regime. The iterative steepest ascent (SA) method is used to quantify ICs for SCs. With the proof of convergence and the comparative analysis of the ideal and real cases, supported by the simulated results, we show that the expected quantization error of SCs is the best IC to be considered for SC systems.

The focus of this study is to examine how Artificial Intelligence (AI) influences the deployment of resources in the context of Beyond 5G (B5G) communications for modern applications. Employing a range of machine learning techniques, including neural networks and graph-based approaches, the investigation utilizes a small cell open dataset from the United States. The results highlight the exceptional performance of neural network models in streamlining small cell deployment, a pivotal aspect for improving both Internet of Things (IoT) connectivity and efficiency across expansive networks and critical applications. The study's insights are relevant for telecommunications professionals and policymakers, offering practical perspectives on the transformative impact of AI in B5G scenarios within highly connected information systems. [ABSTRACT FROM AUTHOR]

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions, vulnerabilities, and assaults. Complex security systems, such as Intrusion Detection Systems (IDS), are essential due to the limitations of simpler security measures, such as cryptography and firewalls. Due to their compact nature and low energy reserves, wireless networks present a significant challenge for security procedures. The features of small cells can cause threats to the network. Network Coding (NC) enabled small cells are vulnerable to various types of attacks. Avoiding attacks and performing secure "peer" to "peer" data transmission is a challenging task in small cells. Due to the low power and memory requirements of the proposed model, it is well suited to use with constrained small cells. An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code (HHMAC) hash between transmissions since the HMAC function is generated using the shared secret. In this research, a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure "peer" to "peer" data transmission model using lightweight H-MAC (1D-LM-P2P-LHHMAC) is proposed with accurate intrusion detection. The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels, Key Pair Generation Time Levels, Chaotic Map Accuracy Levels, Intrusion Detection Accuracy Levels, and the results represent that the proposed model performance in chaotic map accuracy level is 98% and intrusion detection is 98.2%. The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high. [ABSTRACT FROM AUTHOR]

Cost efficiency is an essential metric in the design of major part of what is expected to be the 5G network. Some of the 5G solutions, mainly those involving mmWave technology and network densification, are extremely expensive. Much of what was said about 5G rollout strategies has been said with regard to the world's major leaders in 5G technology and telecom infrastructure investment. However, a much more numerous group of countries often referred as emerging markets or middle-income economies has never hold a leadership in the development of cellular technologies. To date, few of them have fully leveraged the potential of 4G systems while many still have not ensured a return on investment in 3G. This gave rise to the views that these countries are not ready for 5G challenges. However, all of them are doomed to enter the era of another industrial revolution, where exactly 5G is to become the main driver. Yet, the use cases and the portfolio of services of the future networks will apparently depend on economic realities of the country where it will be deployed. There is a rather vague picture at the moment of how the 5G rollout may take place in this part of the world and that is the main reason for this study. In this paper, we outline the technical challenges and economic tensions associated with the developing of 5G physical infrastructure and address spectrum allocation issues with a particular focus on the needs of the future enhanced mobile broadband component. Then we discuss the role of government in establishing favorable regulatory framework, providing supportive policies and finding local drivers to facilitate 5G rollout and the challenges, confronting the operators paving their way to 5G. [ABSTRACT FROM AUTHOR]

In wireless communication, small cells are low-powered cellular base stations that can be used to enhance the coverage and capacity of wireless networks in areas where traditional cell towers may not be practical or cost-effective. Unmanned aerial vehicles (UAVs) can be used to quickly deploy and position small cells in areas that are difficult to access or where traditional infrastructure is not feasible. UAVs are deployed by telecommunication service providers to provide aerial network access in remote rural areas, disaster-affected areas, or massive-attendance events. In this paper, we focus on the scheduling of beaconing periods as an efficient means of energy consumption optimization. The conducted study provides a sub-modular game perspective of the problem and investigates its structural properties. We also provide a learning algorithm that ensures convergence of the considered UAV network to a Nash equilibrium operating point. Finally, we conduct extensive numerical investigations to assist our claims about the energy and data rate efficiency of the strategic beaconing policy (at Nash equilibrium). [ABSTRACT FROM AUTHOR]

Summary: The heterogeneous ultra‐dense network (UDN) is a complex network environment where the small cells (SCs) are densely populated to acquire data transmission. The UDN is mainly adopted to deal with the explosive growth of mobile data and its consequential energy consumption issues. The UDN consists of mobile users, restricting the SCs from offering seamless services as the movement may disrupt the transmissions. To provide an effective solution, this paper introduces an energy‐efficient framework that enables effective data transmissions irrespective of the users' mobility. The proposed model considers the clustered SC deployment where the four‐tiered architecture is adopted. The architecture includes a macro base station (BS), microcells, picocells, and femtocells. The SCs are responsible for transferring the data received from the mobile users to the macro BS. The proposed model introduces the hybrid algorithm called the firefly oriented multiverse optimization (FF‐MVO) algorithm to identify the most optimal path for data transmission. This algorithm works iteratively to identify the optimal path to reach the macro BS for each transmission from the user. The proposed model is simulated in the network simulator 3 (NS3) platform, and the results are evaluated with the existing models. The outcomes proved that the proposed algorithm is more optimal than the other models in finding the optimal path to result in energy‐efficient transmissions. The proposed method achieved an average energy consumption of 0.24 J, an average energy efficiency of 10.965 bits/s/J and an average network throughput of 33.907 Gbps. [ABSTRACT FROM AUTHOR]

A typical 5G Ultra-Dense Network (UDN) comprises different types of Base Stations (BSs) in its structure. Dense deployment of small-cell BSs within a macrocell BS's coverage offers significant benefits, as the distance between a User Equipment (UE) and its small-cell BS is shorter with robust signals. Thus, the network capacity will increase dramatically. However, selecting an appropriate small-cell BS for a particular UE becomes a challenge in 5G UDNs. This study proposed a mechanism to address the cell selection problem and maximize fairness among UEs when making the cell selection decision. The proposed mechanism considered different parameters. The load balance for each small-cell BS was considered to fairly distribute UEs and avoid traffic congestion. Moreover, the signal strength was considered with the achievable data rate for all small-cell BSs to stimulate idle small-cell BSs to be in operating mode. A simulation was carried out in MATLAB to evaluate the proposed mechanism. Signal-to-Interference-Ratio (SINR) and Signal Strength (SS) -based strategies were also simulated for comparison. The proposed solution outperformed the other schemes in terms of fairness, as the UEs attached to the system were fairly distributed among small-cell BSs. Furthermore, the proposed mechanism achieved the best radio resource distribution in terms of fairness compared to the two other schemes. [ABSTRACT FROM AUTHOR]

Towards the 5Gnetworks and beyond, there are a lot of emerging technologies. These technologies include but not limited to; multiple input multiple output (MIMO), cell-Free networks, and millimeter wave bands. The cellular MIMO can provide a satisfied performance for users except the shadowed and the cell-edge ones. In order to overcome this disadvantage, the cell-Free networks are deployed. Through applications of distributed access points (APs), the cell-Free networks can provide a ubiquitous coverage for users as whole. Therefore, they can provide a high throughput for users. Moreover, the applications of millimeter wave bands can provide a high bandwidth and hence, a high throughput for users. In other words, the application of the cell-Free technology combined with the millimeter wave bands can extremely enlarge the users' throughput. This is the motivation of our manuscript. The purpose of this manuscript is to provide mathematical model and simulation for the cell-Free mMIMO network, operating in the millimeter wave bands. The performance metrics can include; the spectral efficiency (SE), bit error rate (BER), and energy efficiency (EE). It is observed that the centralized cooperation among the APs can let users have a satisfied throughput even the system employs the maximal ratio combining (MRC). Furthermore, all cooperation levels, among APs, can perform well even for non-light of sight (NLOS) environment. [ABSTRACT FROM AUTHOR]

The combination of high-precision indoor positioning technology and small cell communication network can effectively reduce the cost of deployment and operation and maintenance, and provide important solutions for various positioning application scenarios. Firstly, the common positioning technologies were summarized and compared, and the feasibility of different positioning technologies in small cells was further analyzed. Then, an indoor positioning scheme based on small cells was proposed, and its architecture was described in detail. The scheme had the advantages of easy expansion of transmission network, flexible transmission path and open positioning interface. Finally, the application scenarios and positioning processes of the two positioning technologies selected based on this scheme were presented. The results show that the indoor positioning scheme based on small cells can meet the positioning needs of the consumers and a wider range of vertical industries, which has great significance and application prospects.

Heterogeneous ultra-dense networks (HUDNs) are one of the key enabling technologies for the fifth-generation (5G) networks. They aim to provide high capacity, low installation cost, and distributed traffic loads. The cell selection is a challenging issue in HUDNs, due to the different characteristics of base stations (BSs) and the existence of a large number of them. Thus, the traditional cell selection scheme is not applicable in such a network. In this paper, a novel adaptive cell selection strategy is proposed, called adaptive two-tier based on adaptive boosting (A2T-Boost). It can adapt to the various characteristics of base stations, as well as the different movement features of mobile stations such as vehicles and pedestrian. It is a software-defined networking (SDN)/machine learning (ML)-based scheme. A real-world case is considered in the downtown of Los Angeles city. Simulation results demonstrate that A2T-Boost achieves high prediction performance and it outperforms other related schemes in terms of average number of handovers (HOs) by up to 50%. Moreover, it enhances the average achievable downlink sum-rates and network energy efficiency achieved by vehicles by up to 33.76%. Furthermore, the average packet delay is decreased using the proposed scheme by up to 12.87%.

Ultra-reliable and low-latency communications (URLLC) is one of the cornerstone services of fifth-generation and beyond (B5G) wireless networks. The URLLC use cases demand strict block error probability and very low-latency targets, and thus even a small 32 byte of payload corruption could be detrimental to the user experience and the overall system performance. Ideally, the current heterogeneous network model and innovative technologies have paved the way for the seamless optimization of B5G URLLC applications. Yet, unprecedented interference issues due to the uncoordinated nature of modern wireless networks, innovative radio access techniques, and frequency reuse methods can significantly affect the performance of the URLLC systems. Therefore, understanding and mitigation of all types of interference associated with each URLLC technology, deployment scenario, and wireless transmission mode are prudent. In this regard, many authors have recently presented interpretative and analytical studies on the management of interference issues; however, the discussion was limited to application-centric approaches and earlier research trends. In this review article, we primarily discuss different types of interference challenges related to the URLLC systems using contemporary designs, frameworks, access modes, and enabling technologies for B5G and sixth-generation (6G) communication networks. We present state-of-the-art research work, in-depth analysis of interference problems, and guidance on the futuristic 6G URLLC technologies and communication networks. This study intends to provide a holistic vision of B5G/6G URLLC systems, their empirical aspects, limitations, essential techniques, and an outlook toward future research avenues.

A demand-based deployment strategy has been recently proposed for e-Um5G in the industrial market. This study measured the transmission loss between buildings at a frequency of 4.7 GHz to initiate small cell deployment in certain areas. A local average apparatus was utilized to remove fading effects, and data were acquired at discrete points one or two meters apart. The transmission losses for buildings 39 m and 95 m from the transmitter were 56.6 dB and 69.1 dB, respectively, excluding free-space loss. The transmission loss was found to be sensitive to building structure and transmitter location, as the loss for a building 39 m away decreased to 49.5 dB when the transmitter was moved closer to the building entrance. The measured results were analyzed in terms of the ITU-R SG3 (International Telecommunication Union-Radiocommunication Sector, Study Group 3) definition of building entry loss and can be used for frequency sharing and building-level small cell deployment in the e-Um5G frequency band. [ABSTRACT FROM AUTHOR]

In next-generation heterogeneous networks, device-to-device communications are a key enabler to support a wider and diverse range of applications. They play an important role to guarantee the performance and quality of service requirements for the future ultra-dense networks. D2D-enabled cellular networks allow user equipment to communicate directly without any or with a partial association with macro base stations or with small base stations. In this paper, we propose a distance-based dynamic approach to minimize the interference and to guarantee QoS for diverse types of users equipment, such as macro user, small user and D2D user. The mode selection is used for minimize the interference and to guarantee QoS for both cellular and D2D communication links. Moreover, we investigated hybrid simultaneous wireless information and power transfer to achieve the higher data rates while guaranteeing the minimum harvested energy. Additionally, our scheme employs a transmit antenna selection criterion to exploit the spatial diversity gain of a multiple antennas for small base station. Results obtained show that coverage probability is improved in macro and small base stations links, when compared with traditional neighbor-based methods, we validate the theoretical findings and demonstrate that significant performance gain over orthogonal multiple access scheme in terms of spectral efficiency can be achieved by the proposed algorithms in a SWIPT-enabled NOMA system where we show the energy efficiency. [ABSTRACT FROM AUTHOR]

With the rapid growth of data traffic and mobile devices, it is imperative to provide reliable and stable services during mobility. Heterogeneous Networks (HetNets) and dense networks have been identified as potential solutions to address the upcoming capacity crunch, but they also pose significant challenges related to handover optimization. This paper presents a comprehensive review of recent handover decision algorithms in HetNets, categorizing them based on their decision techniques and summarizing their input parameters, techniques, and performance evaluations. Our study highlights the technical challenges and opportunities related to handovers in HetNets and dense cellular networks and provides key findings from recent studies. The significance of this survey is to provide a comprehensive overview of handover decision algorithms in HetNets and dense cellular networks, which can aid in the development of more advanced handover optimization approaches. [ABSTRACT FROM AUTHOR]

Fifth generation (5G) is a recent wireless communication technology in mobile networks. The key parameters of 5G are enhanced coverage, ultra reliable low latency, high data rates, massive connectivity and better support to mobility. Enhanced coverage is one of the major issues in the 5G and beyond 5G networks, which will be affecting the overall system performance and end user experience. The increasing number of base stations may increase the coverage but it leads to interference between the cell edge users, which in turn impacts the coverage. Therefore, enhanced coverage is one of the future challenging issues in cellular networks. In this survey, coverage enhancement techniques are explored to improve the overall system performance, throughput, coverage capacity, spectral efficiency, outage probability, data rates, and latency. The main aim of this article is to highlight the recent developments and deployments made towards the enhanced network coverage and to discuss its future research challenges. [ABSTRACT FROM AUTHOR]

With the exponential increase in mobile users, mobile data demand has grown tremendously. To meet these demands, cellular operators are constantly innovating to enhance the capacity of cellular systems. Consequently, operators have been reusing the licensed spectrum "spatially," by deploying 4G/Long-term Evolution (LTE) small cells (e.g., Femto Cells) in the past. However, despite the use of small cells, the licensed spectrum will be unable to meet the consistently rising data traffic because of data-intensive applications such as augmented reality/virtual reality (AR/VR) and on-the-go high-definition video streaming. Applications such as AR/VR and online gaming not only place extreme data demands on the network but are also latency-critical. To meet the QoS guarantees, cellular operators have begun leveraging the unlicensed spectrum by coexisting with Wi-Fi in the 5 GHz band. The standardizing body Third Generation Partnership Project, has prescribed cellular standards for fair unlicensed coexistence with Wi-Fi, namely LTE Licensed Assisted Access (LAA), New Radio in unlicensed (NR-U), and NR in Millimeter. The rapid roll-out of LAA deployments in developed nations like the USA offers an opportunity to study and analyze the performance of unlicensed coexistence networks through real-world ground truth. Thus, this paper presents a high-level overview of past, present, and future of research in small cell and unlicensed coexistence communication technologies. It outlines the vision for future research work in the recently allocated unlicensed spectrum: The 6 GHz band, where the latest Wi-Fi standard, IEEE 802.11ax, will coexist with the latest cellular technology, 5G New Radio in unlicensed. At the end, we present a comparison of the performance between standards ranging from LTE to NR-U based on realistic assumptions. [ABSTRACT FROM AUTHOR]

The fifth generation of broadband wireless telecommunications will increase the speeds of upload and download with decreasing the access network latency and enable bandwidth in excess of 100s of Megabits per second (Mb/s) with latency of less than 1 millisecond (ms), as well as provide access network to billions of subscribers. In this paper the innovations and challenges of 5G are described such as mm-waves, small cells, Massive MIMO, Beamforming, Full Duplex FD, Non-Orthogonal Multiple Access NOMA, and Mobile Edge Computing MEC. The results show that the millimeter waves development is the dominant innovation of 5G technology, which increases the data traffic 1000 times more data than 4G and offer manufacturing of products with cheaper prices. It is concluded that 5G, represents a big step forward in increasing the flexibility of the network infrastructure, and improve scalability and service. Also 5G is not limited to telecommunication services but it represents the Beyond technology in research, automotive, energy, e-business, e-government, vertical industry, security, e-Health, improving human being's life. 5G will be the future benchmark of smart city. [ABSTRACT FROM AUTHOR]

Today's modern enterprises are adjusting to new realities of connectivity. As companies become more distributed and autonomous, emerging applications demand more bandwidth, low latency, more spectrum, and higher reliability. 5G technology can aid many industries or enterprises to make quicker and better business decisions. Private 5G networks, also called 5G Non-Public Networks (5G-NPN), is a 3GPP-based standalone 5G network positioned for a particular enterprise or use case that delivers dedicated network access. It sets to transform industry landscapes with networks capable of rapidly deploying modern use cases and the scalability to meet constantly increasing demands of data capacity and speed. They help generate more revenue for operators who can partner with enterprises to build and manage networks on-premise or in the cloud. The objective of this work is to offer a thorough summary of private 5G networks to assist academicians, researchers, and network developers to quickly grasp their functionalities without needing to go through the standards, specifications, or documentation. This paper discusses various key private 5G network design goals and requirements, examines its deployment scenarios, and explores spectrum considerations and security aspects. The paper presents several enterprise use cases to illuminate how the networks can deliver the demands and services expected by the industries. It also provides an overview of some of the open-source projects considered by various organizations for private network deployment. Finally, several research directions are introduced, emphasizing enterprise challenges to deploying 5G networks. [ABSTRACT FROM AUTHOR]

In order to fit the requirements of future enterprise management networks with multiple service providers, conventional mobile edge computing enabled small cells (MEC-SCs) peer-offloading requires research efforts towards fully-decentralized computation-efficient global-optimal quality of service (QoS) aware load balancing, while ensuring service providers’ privacy protection. In this article, we propose a new fully-decentralized on-demand MEC-SC peer-offloading NETwork (named DEEP-NET), targeting QoS-aware load balancing with enhanced latency and service providers’ privacy protection. Newly developed federated gradient descent based algorithm is fully decentralized to MEC-SCs, which only requires local data and privacy-free inter-MEC-SC data sharing to achieve global optimal QoS-/latency-aware fairness. Result analysis for convergence of the proposed DEEP-NET provides guidance to the future topology optimization of fully-decentralized on-demand MEC-SC deployment. Besides, DEEP-NET outperforms the benchmarks with dynamic user demand to achieve optimal load balancing, with enhanced QoS, latency, and service providers’ privacy. [ABSTRACT FROM AUTHOR]

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Mobility management is an essential process in mobile networks to ensure a high quality of service (QoS) for mobile user equipment (UE) during their movements. In fifth generation (5G) and beyond (B5G) mobile networks, mobility management becomes more critical due to several key factors, such as the use of Millimeter Wave (mmWave) and Terahertz, a higher number of deployed small cells, massive growth of connected devices, the requirements of a higher data rate, and the necessities for ultra-low latency with high reliability. Therefore, providing robust mobility techniques that enable seamless connections through the UE's mobility has become critical and challenging. One of the crucial handover (HO) techniques is known as mobility robustness optimization (MRO), which mainly aims to adjust HO control parameters (HCPs) (time-to-trigger (TTT) and handover margin (HOM)). Although this function has been introduced in 4G and developed further in 5G, it must be more efficient with future mobile networks due to several key challenges, as previously illustrated. This paper proposes a Robust Handover Optimization Technique with a Fuzzy Logic Controller (RHOT-FLC). The proposed technique aims to automatically configure HCPs by exploiting the information on Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and UE velocity as input parameters for the proposed technique. The technique is validated through various mobility scenarios in B5G networks. Additionally, it is evaluated using a number of major HO performance metrics, such as HO probability (HOP), HO failure (HOF), HO ping-pong (HOPP), HO latency (HOL), and HO interruption time (HIT). The obtained results have also been compared with other competitive algorithms from the literature. The results show that RHOT-FLC has achieved considerably better performance than other techniques. Furthermore, the RHOT-FLC technique obtains up to 95% HOP reduction, 95.8% in HOF, 97% in HOPP, 94.7% in HOL, and 95% in HIT compared to the competitive algorithms. Overall, RHOT-FLC obtained a substantial improvement of up to 95.5% using the considered HO performance metrics. [ABSTRACT FROM AUTHOR]

Heterogeneous networks (HetNets) are one of the key enabling technologies for next-generation networks. They aim to provide high capacity, low installation cost, and distributed traffic loads. The cell selection issue is an open research problem in HetNets, due to the different characteristics of base stations and the existence of a large number of them. In this paper, a novel software-defined networking (SDN)/machine learning (ML)-based adaptive algorithm is proposed, called adaptive two-tier, based on the K-nearest neighbor (A2T-KNN) algorithm. It is designed for millimeter wave (mmWave)-based HetNets and it has the ability to adapt to the various movement features of moving vehicles, as well as the different characteristics of the base stations. A real-world case is considered in the center of London. Simulation results demonstrate that A2T-KNN achieves high prediction performance in association with different vehicle features and configuration information. It outperforms other related schemes in terms of average number of handovers by up to 45.83%. Moreover, it was found to enhance the average achievable downlink data rate and network energy efficiency achieved by vehicles by up to 17.18% and 16.86%, respectively.

Long-Term Evolution cellular networks are the main enabler for the massive Machine-Type Communications service and therefore must handle a large number of Machine-Type Devices (MTDs). To control the number of devices allowed to contend on the Physical Random Access Channel (PRACH), the group paging scheme that divides the MTDs into smaller groups and lets the network sequentially trigger the groups has been studied. However, as the number of PRACH preambles is limited, a group’s size must be kept relatively small compared to the MTD population. This paper exploits the possibility that a significant portion of the MTDs is also covered by densely deployed small-cells such that a Small-cell Base Station (SBS) may act as a representative for its MTDs during the preamble transmission step to reduce the load on PRACH. Once the SBS succeeds, its MTDs then contend locally to send their own signaling messages on the corresponding reserved uplink resources. Computer simulations show that the manageable group size can be significantly increased at a reasonable cost on the Physical Uplink Shared Channel. A theoretical model to quickly predict the effect of the ratio of MTDs that are under the coverage of the SBSs is also derived and verified.

Small cells are low-power and low-range radio access nodes that can be used to increase network capacity in reduced areas with high traffic demand and to provide coverage to small isolated zones. As their number is expected to be very high, connecting them to the aggregation point in a cost-efficient manner is a key challenge, and there is consensus that none of the current technologies is valid for all scenarios. Since lamp-posts are one of the most convenient locations for outdoor small cells, this work analyzes the use of power line communications (PLC) over outdoor public lighting networks (OPLN) as a backhaul technology for outdoor small cell deployments. To this end, the characteristics of the PLC channels established in OPLN are firstly assessed. The analysis combines noise measurements performed in existing OPLN and channel responses obtained from a multiconductor transmission line (MTL) model. The attenuation, delay spread and spatial correlation of the multiple-input multiple-output (MIMO) channels are investigated and their influence in the physical layer parameters of PLC systems is discussed. Afterward, the performance achieved by state-of-the-art PLC systems is assessed. To this end, estimations obtained by means of simulations and measurements taken in actual networks are included. Data throughput achieved by PLC systems based on the ITU-T G.hn standard, as well as the expected improvements obtained by 3 x 3 MIMO systems, are given. Results indicate that PLC can be an interesting technology for coverage-driven small cell deployments with backhaul length shorter than 150 m, offering throughput values similar to existing Sub-6 GHz wireless solutions in non-line-of-sight (NLOS) conditions and wired ones like G.fast.

Microgrids in smart grid development create a new era towards resilient energy supply. In turn, They also render complicated cyber-physical system development towards high scalability and comprehensiveness. Heterogeneous Small Cell based Networks (HSCNs) endow a suitable cyber infrastructure for microgrid based cyber-physical systems. To tackle this emerging research area, this paper proposes a Spatiotemporal Device-to-device communication based HSCN Deployment scheme for Microgrid based Smart grid Development (3xSD), to achieve high energy efficiency with high quality-of-service, chronically and dynamically. Concretely, a joint optimization for long-term energy efficiency and achievable data rate maximization with interference mitigation is formulated for spatial small cell positioning, which models both cyber and physical characteristics of Smart Grid User Equipment (SGUE). A Temporal On-demand Small cell Powering and work-Offloading scheme (TOSPO) is proposed on top of the determined small cell positioning. TOSPO considers the real-time heterogeneous features and demands of SGUEs to maximize energy and cost efficiency, for both communication and computation perspectives. To evaluate the performance of 3xSD, spatial analysis, temporal analysis, and selected case study are simulated. Numerical results showcase that 3xSD is capable of providing both long-term and on-demand optimal energy efficiency and quality-of-service solution for microgrids, outperforming existing benchmarks in the literature.

In 5G ultra-dense networks, a distributed wireless backhaul is an attractive solution for forwarding traffic to the core. The macro-cell coverage area is divided into many small cells. A few of these cells are designated as gateways and are linked to the core by high-capacity fiber optic links. Each small cell is associated with one gateway and all small cells forward their traffic to their respective gateway through multi-hop mesh networks. We investigate the gateway location problem and show that finding near-optimal gateway locations improves the backhaul network capacity. An exact $p$ -median integer linear program is formulated for comparison with our novel K-GA heuristic that combines a Genetic Algorithm (GA) with $K$ -means clustering to find near-optimal gateway locations. We compare the performance of K-GA with six other approaches in terms of average number of hops and backhaul network capacity at different node densities through extensive Monte Carlo simulations. All approaches are tested in various user distribution scenarios, including uniform distribution, bivariate Gaussian distribution, and cluster distribution. In all cases, K-GA provides near-optimal results, achieving average number of hops and backhaul network capacity within 2% of optimal while saving an average of 95% of the execution time.

The fifth generation of wireless networks is expected to provide high capacity, low latency, high reliability, and massive connectivity services. Ultra-dense network (UDN) is a clear trend for enhancing capacity, coverage, and load balancing. In UDNs, the cell selection issue for moving vehicles should be addressed. In this paper, a cell selection strategy known as a dwell time estimation (DTE) scheme is proposed, which is based on Vehicle-to-Everything (V2X) communications. It selects small cells that have the longest dwell time in a vehicle’s direction to decrease handover (HO) rate. The proposed DTE scheme is evaluated using two datasets, which are 5G small cells and vehicles datasets, that were collected in the city of Los Angeles in California. The simulation result shows that our DTE algorithm outperforms other recent related schemes in terms of the mean number of HOs by up to 36.26% because it prolongs the dwell time of the vehicle within the serving small cell. Consequently, it reduces the average number of HO failures and unnecessary HOs. In addition, it gives improvements in terms of the average achievable downlink throughput and network energy efficiency. Furthermore, it has superiority over the other schemes in terms of the mean packet delay by up to 16.49%.

Fifth-generation (5G) cellular networks are a promising technology to meet the rapid growth in wireless traffic. Small cells are critical in fulfilling the requirements of 5G networks. A heterogeneous ultra-dense network (HUDN) is an enabling technology consisting of several types of small cells to enhance the performance of 5G networks effectively. A critical issue of HUDN is the cell selection method because the traditional technique for cell selection is inapplicable in such a network. This study proposes a novel adaptive cell selection (ADA-CS) scheme. It adapts to various characteristics of HUDNs and vehicle movements. It performs six phases to select the best base station with which to be associated. Simulation results show that, with low- and medium-speed vehicles, the ADA-CS scheme outperforms the traditional protocol in terms of the average number of handovers by 42.39%. In addition, it is superior to some relevant recent schemes by up to 36.53%. The adaptation feature of the proposed protocol provides additional improvements regarding the average number of handovers with high-speed vehicles. Therefore, it achieves superiority in terms of the average number of handover failures and unnecessary handovers. In addition, the ADA-CS scheme enhances the average achievable downlink data rates and spectral efficiency per vehicle by 3.98% and 2.79% compared with the traditional and the relevant recent schemes.

The small cell technology is considered as a key technology for 5G networks. The capacity expansion and coverage extension are both achieved through this deployment. However, the ultra-dense small cells deployment can cause a severe interference, a high number of frequent unnecessary handovers and/or handover failure and hence, high power consumption is expected due to the signalling overhead. Placing some small cells into idle mode, without causing degradation to the quality of service, is a good strategy to enhance the energy efficiency in the network. In this paper, we propose an energy efficient game theoretical method to reduce the energy consumption in dense small cells network. The proposed method enables the small cells to adjust their transmitting power while considering to balance the load among themselves. A non-cooperative game is formulated among the cells in the network to solve the cost function which considers both the power mode and its load. The game is solved using the regret matching-based learning distribution approach in which each cell chooses its optimal transmit power strategy to reach the equilibrium. The cell selection for handover is then made using a multiple attribute TOPSIS technique. Results show that the proposed method significantly reduces the power consumption and unnecessary handovers, in addition to improving the average small cell throughput compared to the conventional method. [ABSTRACT FROM AUTHOR]

The fifth generation (5G) wireless technology emerged with marvelous effort to state, design, deployment and standardize the upcoming wireless network generation. Artificial intelligence (AI) and machine learning (ML) techniques are well capable to support 5G latest technologies that are expected to deliver high data rate to upcoming use cases and services such as massive machine type communications (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low latency communications (uRLLC). These services will surely help Gbps of data within the latency of few milliseconds in Internet of Things paradigm. This survey presented 5G mobility management in ultra-dense small cells networks using reinforcement learning techniques. First, we discussed existing surveys then we are focused on handover (HO) management in ultra-dense small cells (UDSC) scenario. Following, this study also discussed how machine learning algorithms can help in different HO scenarios. Nevertheless, future directions and challenges for 5G UDSC networks were concisely addressed. [ABSTRACT FROM AUTHOR]