Mobility management in 5G heterogeneous networks

In recent years, mobile data traffic has increased exponentially as a result of widespread popularity and uptake of portable devices, such as smartphones, tablets and laptops. This growth has placed enormous stress on network service providers who are committed to offering the best quality of service to consumer groups. Consequently, telecommunication engineers are investigating innovative solutions to accommodate the additional load offered by growing numbers of mobile users. The fifth generation (5G) of wireless communication standard is expected to provide numerous innovative solutions to meet the growing demand of consumer groups. Accordingly the ultimate goal is to achieve several key technological milestones including up to 1000 times higher wireless area capacity and a significant cut in power consumption. Massive deployment of small cells is likely to be a key innovation in 5G, which enables frequent frequency reuse and higher data rates. Small cells, however, present a major challenge for nodes moving at vehicular speeds. This is because the smaller coverage areas of small cells result in frequent handover, which leads to lower throughput and longer delay. In this thesis, a new mobility management technique is introduced that reduces the number of handovers in a 5G heterogeneous network. This research also investigates techniques to accommodate low latency applications in nodes moving at vehicular speeds

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

DR9.3 Final report of the JRRM and ASM activities

Deliverable del projecte europeu NEWCOM++This deliverable provides the final report with the summary of the activities carried out in NEWCOM++ WPR9, with a particular focus on those obtained during the last year. They address on the one hand RRM and JRRM strategies in heterogeneous scenarios and, on the other hand, spectrum management and opportunistic spectrum access to achieve an efficient spectrum usage. Main outcomes of the workpackage as well as integration indicators are also summarised.Postprint (published version

Efficient radio resource management in next generation wireless networks

The current decade has witnessed a phenomenal growth in mobile wireless communication networks and subscribers. In 2015, mobile wireless devices and connections were reported to have grown to about 7.9 billion, exceeding human population. The explosive growth in mobile wireless communication network subscribers has created a huge demand for wireless network capacity, ubiquitous wireless network coverage, and enhanced Quality of Service (QoS). These demands have led to several challenging problems for wireless communication networks operators and designers. The Next Generation Wireless Networks (NGWNs) will support high mobility communications, such as communication in high-speed rails. Mobile users in such high mobility environment demand reliable QoS, however, such users are plagued with a poor signal-tonoise ratio, due to the high vehicular penetration loss, increased transmission outage and handover information overhead, leading to poor QoS provisioning for the networks' mobile users. Providing a reliable QoS for high mobility users remains one of the unique challenges for NGWNs. The increased wireless network capacity and coverage of NGWNs means that mobile communication users at the cell-edge should have enhanced network performance. However, due to path loss (path attenuation), interference, and radio background noise, mobile communication users at the cell-edge can experience relatively poor transmission channel qualities and subsequently forced to transmit at a low bit transmission rate, even when the wireless communication networks can support high bit transmission rate. Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed. The performance of proposed ATMA CAC scheme is investigated and compare it with the traditional CAC scheme. The ATMA scheme exploits the mobility events in the highspeed mobility communication environment and the calls (new and handoff calls) generation pattern to enhance the QoS (new call blocking and handoff call dropping probabilities) of the mobile users. The numbers of new and handoff calls in wireless communication networks are dynamic random processes that can be effectively modeled by the Continuous Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed

D4.3 Final Report on Network-Level Solutions

Research activities in METIS reported in this document focus on proposing solutions to the network-level challenges of future wireless communication networks. Thereby, a large variety of scenarios is considered and a set of technical concepts is proposed to serve the needs envisioned for the 2020 and beyond. This document provides the final findings on several network-level aspects and groups of solutions that are considered essential for designing future 5G solutions. Specifically, it elaborates on: -Interference management and resource allocation schemes -Mobility management and robustness enhancements -Context aware approaches -D2D and V2X mechanisms -Technology components focused on clustering -Dynamic reconfiguration enablers These novel network-level technology concepts are evaluated against requirements defined by METIS for future 5G systems. Moreover, functional enablers which can support the solutions mentioned aboveare proposed. We find that the network level solutions and technology components developed during the course of METIS complement the lower layer technology components and thereby effectively contribute to meeting 5G requirements and targets.Aydin, O.; Valentin, S.; Ren, Z.; Botsov, M.; Lakshmana, TR.; Sui, Y.; Sun, W.... (2015). D4.3 Final Report on Network-Level Solutions. http://hdl.handle.net/10251/7675

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

Cross-layer design and optimization of medium access control protocols for wlans

This thesis provides a contribution to the field of Medium Access Control (MAC) layer protocol design for wireless networks by proposing and evaluating mechanisms that enhance different aspects of the network performance. These enhancements are achieved through the exchange of information between different layers of the traditional protocol stack, a concept known as Cross-Layer (CL) design. The main thesis contributions are divided into two parts. The first part of the thesis introduces a novel MAC layer protocol named Distributed Queuing Collision Avoidance (DQCA). DQCA behaves as a reservation scheme that ensures collision-free data transmissions at the majority of the time and switches automatically to an Aloha-like random access mechanism when the traffic load is low. DQCA can be enriched by more advanced scheduling algorithms based on a CL dialogue between the MAC and other protocol layers, to provide higher throughput and Quality of Service (QoS) guarantees. The second part of the thesis explores a different challenge in MAC layer design, related to the ability of multiple antenna systems to offer point-to-multipoint communications. Some modifications to the recently approved IEEE 802.11n standard are proposed in order to handle simultaneous multiuser downlink transmissions. A number of multiuser MAC schemes that handle channel access and scheduling issues and provide mechanisms for feedback acquisition have been presented and evaluated. The obtained performance enhancements have been demonstrated with the help of both theoretical analysis and simulation obtained results

A Distributed SON-Based User-Centric Backhaul Provisioning Scheme

5G definition and standardization projects are well underway, and governing characteristics and major challenges have been identified. A critical network element impacting the potential performance of 5G networks is the backhaul, which is expected to expand in length and breadth to cater to the exponential growth of small cells while offering high throughput in the order of gigabit per second and less than 1 ms latency with high resilience and energy efficiency. Such performance may only be possible with direct optical fiber connections that are often not available country-wide and are cumbersome and expensive to deploy. On the other hand, a prime 5G characteristic is diversity, which describes the radio access network, the backhaul, and also the types of user applications and devices. Thus, we propose a novel, distributed, self-optimized, end-to-end user-cell-backhaul association scheme that intelligently associates users with candidate cells based on corresponding dynamic radio and backhaul conditions while abiding by users' requirements. Radio cells broadcast multiple bias factors, each reflecting a dynamic performance indicator (DPI) of the end-to-end network performance such as capacity, latency, resilience, energy consumption, and so on. A given user would employ these factors to derive a user-centric cell ranking that motivates it to select the cell with radio and backhaul performance that conforms to the user requirements. Reinforcement learning is used at the radio cells to optimise the bias factors for each DPI in a way that maximise the system throughput while minimising the gap between the users' achievable and required end-to-end quality of experience (QoE). Preliminary results show considerable improvement in users' QoE and cumulative system throughput when compared with the state-of-the-art user-cell association schemes

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms

Comparison of vertical handover decision-based techniques in heterogeneous networks

Industry leaders are currently setting out standards for 5G Networks projected for 2020 or even sooner. Future generation networks will be heterogeneous in nature because no single network type is capable of optimally meeting all the rapid changes in customer demands. Heterogeneous networks are typically characterized by some network architecture, base stations of varying transmission power, transmission solutions and the deployment of a mix of technologies (multiple radio access technologies). In heterogeneous networks, the processes involved when a mobile node successfully switches from one radio access technology to the other for the purpose of quality of service continuity is termed vertical handover or vertical handoff. Active calls that get dropped, or cases where there is discontinuity of service experienced by mobile users can be attributed to the phenomenon of delayed handover or an outright case of an unsuccessful handover procedure. This dissertation analyses the performance of a fuzzy-based VHO algorithm scheme in a Wi-Fi, WiMAX, UMTS and LTE integrated network using the OMNeT++ discrete event simulator. The loose coupling type network architecture is adopted and results of the simulation are analysed and compared for the two major categories of handover basis; multiple and single criteria based handover methods. The key performance indices from the simulations showed better overall throughput, better call dropped rate and shorter handover time duration for the multiple criteria based decision method compared to the single criteria based technique. This work also touches on current trends, challenges in area of seamless handover and initiatives for future Networks (Next Generation Heterogeneous Networks)