Heterogeneous Mobile Networks Research Articles

Energy-Efficient Deployment in Static and Mobile Heterogeneous Multi-Hop Wireless Sensor Networks

We study a heterogeneous wireless sensor network (WSN) where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> heterogeneous access points (APs) gather data from densely deployed sensors and transmit their sensed information to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> heterogeneous fusion centers (FCs) via multi-hop wireless communication. The heterogeneous optimal deployment of APs and FCs is modeled as an optimization problem with total wireless communication power consumption of the network as its objective function. We consider both static WSNs, where APs and FCs retain their deployed position, and mobile WSNs where APs and FCs can move from their initial deployment to their optimal locations. Based on the derived necessary conditions for the optimal deployment in static WSNs, we propose an iterative algorithm to deploy APs and FCs. In addition, we study the necessary conditions of the optimal movement-efficient deployment in mobile WSNs with constrained movement energy and present iterative algorithms to find such deployments, accordingly. Simulation results show that our proposed deployment algorithms outperform the existing methods in the literature, and achieve a lower total wireless communication power in both static and mobile WSNs.

A novel heuristic for handover priority in mobile heterogeneous networks based on a multimodule Takagi–Sugeno–Kang fuzzy system

H2RDC (heuristic handover based on RCC-DTSK-C), a heuristic algorithm based on a highly interpretable deep Takagi–Sugeno–Kang fuzzy classifier, is proposed for suppressing the mobile heterogeneous networks problem of frequent handover and handover ping-pong in the multibase-station scenario. This classifier uses a stack structure between subsystems to form a deep classifier before generating a base station (BS) priority sequence during the handover process, and adaptive handover hysteresis is calculated. Simulation results show that H2RDC allows user equipment to switch to the best antenna at the optimal time. In high-BS density load and mobility scenarios, the proposed algorithm's handover success rate is similar to those of classic algorithms such as best connection (BC), self tuning handover algorithm (STHA), and heuristic for handover based on AHP-TOPSIS-FUZZY (H2ATF). Moreover, the handover rate is 83% lower under H2RDC than under BC, whereas the handover ping-pong rate is 76% lower.

A Novel Link-Network Assignment to Improve the Performance of Mobility Management Protocols in Future Mobile Networks

5G is expected to support new services and applications that will change the user experience and will drive to a new business landscape. Moreover, most of the services will require optimum connectivity and seamless mobility in heterogeneous networks. To cope with these challenges, network mobility management and network densification are envisioned to be key factors in the emerging 5G architectures. By deploying a large number of cells, 5G architectures can provide users with high throughput and flexible access services, an improvement of the network scalability and optimized network coverage. However, with this densification, seamless mobility support can lead to significant increasing in signaling overhead due to frequent handovers. In this context, network operators need to efficiently plan the deployment of the base stations taking into account the mobility management of the users, and the service degradation that this mobility process could cause. This article aims to optimize the assignment of the base stations to the access routers in the mobile network to improve the network performance. The results obtained show that our proposed Link-Network Assignment algorithm based on clustering techniques achieve significant gains in terms of signaling and data forwarding costs. These simulation results demonstrate that the proposed algorithm can successfully reduce signaling cost and packet delivery cost by up to 56% and 5%, respectively, on average, compared with baseline algorithms.

Performance evaluation of the eICIC technique applied to a heterogeneous 4G mobile network

The evolution of LTE-A (Long Term Evolution -Advanced) has enabled the development of the Heterogeneous Network (HetNet) which uses multiple cell types due to the explosion in the number of connected subscribers. Different cell types of different sizes are deployed to share the load in the heterogeneous network. Unplanned deployment of small cells with low power, planning of the existing network, the power difference between cells; physical and meteorological phenomena affect the signal quality of radio links; crowded areas of metropolises with extremely high traffic hotspots force operators to increase the network capacity in a more economical way by installing small cells Several techniques have been developed in the literature. Among them, eICIC has emerged as the best and is used to overcome these interference problems in the heterogeneous 4G network. The performance evaluation of eICIC has been performed analytically and numerically in the time domain due to its use with the ABS (Almost Blank Subframe) of the OFDM system. The simulation areas are in center of the picocells, in the cell range extension (CRE) areas and in the macrocells. Analytically, we used the signal-to-interference-plus-noise ratio (SINR) to evaluate the bit rate, RSRP and RSRQ. The numerical method consists in proposing an algorithm for calculating the analytical parameters using Matlab software. The results obtained from the simulations are convincing and are not far from those obtained in the literature. The values obtained from the SINR correspond to the SINR-CQI table found in the literature. The throughput calculated in this work in relation to radio conditions (RSRP, RSRQ) reflects everyday realities.

Self-Optimizing Data Offloading in Mobile Heterogeneous Radio-Optical Networks: A Deep Reinforcement Learning Approach

In addition to the exploration of more spectrum at high-frequency bands, next-generation wireless networks will witness an intelligent convergence of radio frequency (RF) and non-RF links such as optical and visible light communication. Optical attocell (OAC) networks provide an additional layer to RF-based wireless networks with gigabit-per-second data transmission rate and centimeter-level location accuracy. However, the directionality, line-of-sight constraints, as well as strong sensitivity to the location and orientation of user terminals challenge the stringent requirements for throughput and latency. In this article, we consider mobile heterogeneous networks (HetNets) incorporating indoor OAC with femtocells and macrocells to provide a low-cost and energy-efficient solution. The HetNets solution satisfies diverse service requirements in terms of user-experienced data rate, mobility, latency, accuracy, and security in the Internet of Things. To support seamless connectivity and optimal resource allocation in the proposed HetNets with mobility awareness, handover in dynamic environments needs to be addressed efficiently. Incorporating rich environmental parameters into such a decision making problem facilitates the self-optimization process, but extensively expands the state space. To achieve a fast convergence speed, a deep reinforcement learning approach is proposed to optimize the handover parameters (e.g., time-to-trigger and hysteresis margin). This is a model-free and off-policy reinforcement setting that trains and employs a deep neural network to predict future rewards for successions of states and actions. Thus, the optimal parameters are obtained by selecting the best actions to take. Through numerical simulation and performance analysis, we discover the gain from enriching the state space and the adaptability of the system to dynamic environments.

5G multi-tier radio access network planning based on voronoi diagram

Network planning of multi-layer heterogeneous mobile networks with complex topology is an important task. In this paper the spectral and energy efficiency of integrated LTE/Wi-Fi technologies for 5G are improved. A method of adaptive formation of the structure of radio access level (RAL) with the provision of the required quality of service (QoS) and the possibility of broadband data transmission is proposed. The Voronoi tessellation is used for designing the RAL of 5G mobile networks for the placement of base stations, which allowed optimum delimiting the coverage area for each base station and provide users the cell interface services. To minimize interference there was proposed a method of dynamic frequency reuse for different sizes of Voronoi cells. Modelling shows the developed method is effective both at low and at high network load, however, at high load there is a slightly smaller gain in energy efficiency than at low load.

Mobility Induced Multi-Hop LEACH Protocol in Heterogeneous Mobile Network

Heterogeneous mobile networks are a vital cue for Internet of Things (IoT) networks and their applications. Therefore, an optimal routing protocol is essential for the heterogeneous network to realize energy efficiency and robustness. However, designing an optimal routing protocol is more complex due to uneven energy depletion and dynamic event generation. The complexity further increases with the node mobility. In this context, the multi-hop routing approach with a controlled mobility pattern provides an energy efficient network by improving memory and storage utilization. This work proposes a new energy-efficient model for heterogeneous network, considering the effect of mobility and residual energy of nodes for cluster head selection in multi-hop-LEACH (M-LEACH). The performance of the proposed mobility induced multi-hop LEACH (Mob M-LEACH) protocol is further compared with existing baseline methods. The robustness of the network is evaluated considering static and dynamic environments for multiple network technologies. The simulation results show that the proposed method reduces network latency by 25% and enhances the throughput by 75%, improving energy consumption and network lifetime when compared with the state-of-art methods.

Enhance Vertical Handover Security During Execution Phase in Mobile Networks

The Vertical Handover (VHO) is one of the most vital features provided for the heterogeneous mobile networks. It allows Mobile Users (MUs) to keep ongoing sessions without disruption while they continuously move between different Radio Access Technologies (RATs) such as Wireless Fidelity (Wi-Fi), Global System for Mobile Communication (GSM), Universal Mobile Telecommunications System (UMTS), Long Term Evolution (LTE) and Fifth Generation (5G). In order to fulfill this goal, the VHO must comply to three main phases: starting of collecting the required information and then passing it for decision phase to obtain the best available RAT for performing VHO by execution phase eventually. However, the execution phase still encounters some security issues which are exploited by hackers in launching malicious attacks such as ransomware, fragmentation, header manipulation, smurf, host initialization, reconnaissance, eavesdropping, Denial of Service (DoS), spoofing, Man in the Middle (MITM) and falsification. This paper thoroughly studies the recent security issues for hundreds VHO approaches found in the literature and comes up with a secure procedure to enhance VHO security during execution phase. A numerical analysis results of the proposed procedure are effectively evaluated in terms of security and signaling cost. Compared with the recent related work found in literature, the analysis demonstrates that the security is successfully improved by 20% whereas signaling cost is maintained as in non-proposed procedure.

Reachability-Based Packet Scheduler of Multipath QUIC for Heterogeneous Mobile Networks

In recent years, we need more bandwidth to enjoy entertainment contents such as video streaming, music and online gaming. To gain enough bandwidth, technologies that combine bandwidth by using multiple interfaces at same time are desired. Multipath transport protocols which combine multiple paths for packet delivery at the transport layer are a promising technology. Such protocols have a mechanism, called “packet scheduler”, to select the interface to send a packet. However, existing studies of the packet scheduler have not explicitly considered the compatibility of mobility with bonding of bandwidth. Therefore, when smartphone users move out of coverage of communication networks such as wireless Local Area Network (LAN) and Long Term Evolution (LTE) by vehicle, packet loss occurs, leading to a decrease of throughput. In this study, we propose a packet scheduler that selects an appropriate communication path so that packets can reach the peer before it moves out of the coverage. Based on routes of a vehicle and the position and communication range of the access point, the time at which a communication path will be lost is predicted. In addition, we employ MPQUIC (Multipath QUIC (Quick UDP Internet Connections)), which is a multipath transport protocol proposed as the extension of QUIC protocol, to reduce the ACK packet loss in multipath communication, and to reduce the time until the starts of retransmission. We evaluated the number of packet losses, the throughput and the time until starts of retransmission using a simulator and show the superiority of proposed method.

Mobility Support for Millimeter Wave Communications: Opportunities and Challenges

Millimeter-wave (mmWave) communication technology offers a potential and promising solution to support 5G and B5G wireless networks in dynamic scenarios and applications. However, mobility introduces many challenges as well as opportunities to mmWave applications. To address these problems, we conduct a survey of the opportunities and technologies to support mmWave communications in mobile scenarios. Firstly, we summarize the mobile scenarios where mmWave communications are exploited, including indoor wireless local area network (WLAN) or wireless personal area network (WPAN), cellular access, vehicle-to-everything (V2X), high speed train (HST), unmanned aerial vehicle (UAV), and the new space-air-ground-sea communication scenarios. Then, to address users&#x2019; mobility impact on the system performance in different application scenarios, we introduce several representative mobility models in mmWave systems, including human mobility, vehicular mobility, high speed train mobility and ship mobility. Next we survey the key challenges and existing solutions to mmWave applications, such as channel modeling, channel estimation, anti-blockage, and capacity improvement. Lastly, we discuss the open issues concerning mobility-aware mmWave communications that deserve further investigation. In particular, we highlight future heterogeneous mobile networks, dynamic resource management, artificial intelligence (AI) for mobility and integration of geographical information, deployment of large intelligent surface and reconfigurable antenna technology, and finally, the evolution to Terahertz (THz) communications.

Mobility Robustness Optimization in Future Mobile Heterogeneous Networks: A Survey

Ensuring reliable and stable communication during the movements of mobile users is one of the key issues in mobile networks. In the recent years, several studies have been conducted to address the issues related to Handover (HO) self-optimization in Heterogeneous Networks (HetNets) for Fourth Generation (4G) and Fifth Generation (5G) mobile networks. Various solutions have been developed to determine or estimating the optimum and ideal settings of Handover Control Parameters (HCPs), such as Time-To-Trigger (TTT) and Handover Margin (HOM). However, the complexity, high requirements, and the upcoming structure of ultra-dense HetNets require more advanced HO self-optimization techniques for future implementation. This paper studies HO self-optimization techniques that may implemented in the next-generation mobile HetNets by reviewing state-of-the-art algorithms. The solutions discussed in this survey are more focus on Mobility Robustness Optimization (MRO), which is a significant self-optimization function in 4G and 5G mobile networks. The applied solutions will preserve the continuous connection between the User Equipment (UE) and eNBs during UE mobility, thereby enhancing connection quality. The various algorithms and techniques applied to HO have revealed different outcomes. This paper discusses the pros and cons of these techniques, and further examines HO self-optimization challenges and solutions. New future directions for the implementation of HO self-optimization are also identified. This survey will contribute to the understanding of the issues related to mobility management, particularly in relation to the self-optimization of HO control parameters in future mobile HetNets.

Quality of service management for an intent-based heterogeneous network using mobile QoE application

Traditional Service Level Agreement (SLA) based on the quality of service (QoS) management methods are insufficient to ensure quality-related contracts between service providers and users. This article proposes a user-centric method for QoS management in heterogeneous mobile networks. Based on a new QoE metric on a scale of 1 to 5, this method considers the commercial value of electronic services to end-users. With this approach, the configuration and functionality of the network automatically change depending on the requirements of the end-users. The work proposes a conceptual model for constructing an intent-based software-defined heterogeneous network, which effectively manages shared resources and adapts to users’ needs. A prototype of a mobile and operator application for adaptive client-oriented service delivery in a heterogeneous network has been developed, which makes it possible to obtain the ordered QoE based on the feedback between the user and the network operator. Using this approach will allow network operators to provide individualization of service users with a certain level of QoS by analyzing their estimates of QoE (ordered through the developed mobile application). And the use of machine learning algorithms will allow to react to unfavorable combinations of values of quality indicators and prevent the situation when the user is not satisfied with the quality of services received for adaptive prediction of the moment of network reconfiguration. We propose a method for managing the QoS provision in a heterogeneous wireless network using Big Data technology and a mobile QoE application, which considers and analyzes the estimates of the ordered QoE and allows users QoS improvement according to the demand. It is demonstrated that using the proposed method in a heterogeneous wireless network allows reducing the number of dissatisfied users with the quality of service by up to 60% using an experimental study.

Hierarchical and Hybrid Cell Load Balancing in 5G Heterogeneous Mobile Networks

SummaryIn Fifth Generation (5G) Heterogeneous Mobile Networks (HetNets), deploying dense small cell networks makes user association more challenging. The process of collecting cell load information from the User Equipments (UEs) and broadcasting the feedback message involves significant overhead and time complexity. Moreover, the UEs may not know the optimum cell to reselect, satisfying its data rate requirements. In order to overcome these drawbacks, in this paper, we propose to design an Hierarchical and Hybrid Cell Load Balancing (HHCLB) technique using Selective Handoff. In this technique, the UEs of each cell are grouped into clusters depending on their proximity distance. Each cluster contains a cluster controller (CC) which is in charge of determining the intra‐cell load and redirecting the cell‐reselection request of a UE. If the data rate of any UE in a cluster becomes less than its required rate, then the cell reselection process is performed. By simulation results, it is shown that load balancing can be done proactively (implicitly) by the CCs when the load is unbalanced or can be done on demand (explicitly) when a UE send a request for cell reselection. In the case of Macro cells, HHCLB attains 71% higher throughput for low load scenario and 59% higher throughput for high load scenario. Similarly, in the case of Femto cells, HHCLB attains 19% higher throughput for low load scenario and 27% higher throughput for high load scenario.

A survey on sleep mode techniques for ultra-dense networks in 5G and beyond

The proliferation of mobile users with an attendant rise in energy consumption mainly at the base station has requested new ways of achieving energy efficiency in cellular networks. Many approaches have been proposed to reduce the power consumption at the base stations in response to the contribution of energy cost to the increase of OPEX of the mobile operators and the rise of the carbon footprint on global climate. As a springboard to the application of sleep mode methods in ultra-dense cellular networks, this paper provides a comprehensive survey of the base station sleep mode strategies in heterogeneous mobile networks from perspectives of modeling and algorithm design. Specifically, the sleep mode enabling strategies and sleep wake-up schemes are reviewed. The base station sleep-mode techniques in ultra-dense networks are further discussed as well as the challenges and possible solutions.

Heterogeneous Mobile Networking for Lightweight UAV Assisted Emergency Communication

Due to the frequent natural disasters in recent two years, UAV assisted disaster networks have attracted attention due to the flexible information storage and favorable computation capacity in technical rescue. The previous studies concentrate on dynamically optimizing the service coverage to improve the system performance. However, the continually changing of energy cost, time cost, and the social connections between users are not jointly considered in previous studies. In this paper, we propose a social relationship-based timeliness aware message splitting scheme for the energy-friendly UAV assisted delay tolerant networks. Firstly, we put forward our social network based splitting optimization problem and use social network closeness and message's decaying with time to quantify the messages' value. Next, a social optimization copy splitting algorithm (SOCS) is designed to guarantee the lower expected delay and higher message delivery ratio through UAV assisted interesting areas (IAs). Finally, the extensive simulations show the optimality of the proposed SOCS algorithm using the enhanced social relationship based forwarding scheme.

An Agile and Distributed Mechanism for Inter-Domain Network Slicing in Next Generation Mobile Networks

Network slicing is emerging as a promising method to provide sought after versatility and flexibility to cope with ever-increasing demands. To realize such potential advantages and to meet the challenging requirements of various network slices in an on-demand fashion, we need to develop an agile and distributed mechanism for resource provisioning to different network slices in a heterogeneous multi-resource multi-domain mobile network environment. We formulate inter-domain resource provisioning to network slices in such an environment as an optimization problem which maximizes social welfare among network slice tenants (so that maximizing tenants’ satisfaction), while minimizing operational expenditures for infrastructure service providers at the same time. To solve the envisioned problem, we implement an iterative auction game among network slice tenants, on one hand, and a plurality of price-taking subnet service providers, on the other hand. We show that the proposed solution method results in a distributed privacy-saving mechanism which converges to the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">optimal solution</i> of the described optimization problem. In addition to providing analytical results to characterize the performance of the proposed mechanism, we also employ numerical evaluations to validate the results, demonstrate convergence of the presented algorithm, and show the enhanced performance of the proposed approach (in terms of resource utilization, fairness and operational costs) against the existing solutions.

A New Secure Algorithm for Upcoming Sensitive Connection between Heterogeneous Mobile Networks

One of the most important concepts in the heterogeneous mobile networks is Vertical Handover (VHO). The VHO is a vital process taken place by Mobile Users (MUs) in order to satisfy their preferences of security and cost, in addition to the rest of parameters of network and terminal such as latency and velocity, respectively. However, a proactive security for upcoming sensitive connection and performing VHO between heterogeneous mobile networks have not been considered. This paper therefore comes up with a new secure algorithm to address this issue: Proactive Security for Upcoming Sensitive Connection (PSUSC). Analysis of the PSUSC algorithm proves reducing potential attacks extremely compared with previous works which rely on using less secure RAT.

Mobility prediction assisted call admission control model for mobile heterogeneous cellular network

Mobility prediction assisted call admission control model for mobile heterogeneous cellular network

Technical-Economic Analysis of Photovoltaic Systems Applied to Heterogeneous Mobile Networks in Rural Areas

The use of renewable sources as an energy matrix has become crucial for the development of rural mobile networks both to meet increasing energy consumption in mobile network segments and to improve the efficiency of the grid. Thus, this work aims to analyze the economic viability of the photovoltaic system as an energy source for 5G mobile networks in rural environments by means of energy consumption models for mobile networks and cost for installation and operation of photovoltaic systems. Results indicate that although the analysis is characterized for a rural scenario with low population density, where economic viability is low due to geographic location and access difficulties, the photovoltaic system has great feasibility of implantation and operation. Thus, according to the results, the implementation of this renewable energy source is financially favorable in locations with a higher insolation rate above 4.0 kWh/m2.day. In addition, the reduction in the emission of CO2 in the atmosphere from the use of the photovoltaic system demonstrated the environmental importance of this energy source.

Personal Picocell Scheme Using Adaptive Control CRE in Heterogeneous Mobile Networks

Heterogeneous networks (HetNets), which are combined with a macrocell and picocell in the same coverage, are expected to further increase the system capacity in fifth-generation mobile systems and beyond. In HetNets, the cell range expansion (CRE) technique plays an important role and can allow more user equipment (UE) to access the picocell, i.e., virtually expand the picocell coverage. However, conventional CRE techniques that provide a fixed cell selection offset (CSO) for all UE may worsen user throughput if UE is forced to connect to the picocell because the received signal-to-interference plus noise ratio of the UE becomes lower. Therefore, we propose a personal picocell scheme using an adaptive control CRE technique to improve user throughput in which different CSOs are assigned to UE to form each optimal picocell for each UE. In this paper, we first describe the aspects and algorithm of the proposed scheme. Then, we show the user throughput for adaptive control CRE in comparison with conventional CRE by using system-level computer simulations for the two types of HetNets, i.e., single-band and multi-band HetNets. In the simulations, we first clarify the optimal parameters of the adaptive control CRE. We then show the average and 5-percentile user throughput of the optimized adaptive control CRE in comparison with that of conventional CRE. From these results, we confirmed that the personal picocell scheme using the adaptive control CRE can improve the 5-percentile user throughput while maintaining the average user throughput compared with that of conventional CRE.