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

Mobile Wireless Sensor Networks: An Overview

Mobile wireless sensor networks (MWSNs) have emerged and shifted the focus from the typical static wireless sensor networks to networks with mobile sensor nodes that are capable to sense the various types of events. Also, they can change their position frequently in a specific sensing area. The applications of the MWSNs can be widely divided into time-driven, event-driven, on-demand and tracking based applications. Mobile sensor node architecture, residual energy utilization, mobility, topology, scalability, localization, data collection routing, Quality of Service (QoS), etc., are the key factors to design an energy efficient MWSNs for some specific purpose. This chapter deals with an overview of the MWSNs and a few significant phenomena to design an energy efficient MWSNs to the large-scale environment

Airborne Directional Networking: Topology Control Protocol Design

This research identifies and evaluates the impact of several architectural design choices in relation to airborne networking in contested environments related to autonomous topology control. Using simulation, we evaluate topology reconfiguration effectiveness using classical performance metrics for different point-to-point communication architectures. Our attention is focused on the design choices which have the greatest impact on reliability, scalability, and performance. In this work, we discuss the impact of several practical considerations of airborne networking in contested environments related to autonomous topology control modeling. Using simulation, we derive multiple classical performance metrics to evaluate topology reconfiguration effectiveness for different point-to-point communication architecture attributes for the purpose of qualifying protocol design elements

Towards Transportation Digital Twin Systems for Traffic Safety and Mobility Applications: A Review

Digital twin (DT) systems aim to create virtual replicas of physical objects that are updated in real time with their physical counterparts and evolve alongside the physical assets throughout its lifecycle. Transportation systems are poised to significantly benefit from this new paradigm. In particular, DT technology can augment the capabilities of intelligent transportation systems. However, the development and deployment of networkwide transportation DT systems need to take into consideration the scale and dynamic nature of future connected and automated transportation systems. Motivated by the need of understanding the requirements and challenges involved in developing and implementing such systems, this paper proposes a hierarchical concept for a Transportation DT (TDT) system starting from individual transportation assets and building up to the entire networkwide TDT. A reference architecture is proposed for TDT systems that could be used as a guide in developing TDT systems at any scale within the presented hierarchical concept. In addition, several use cases are presented based upon the reference architecture which illustrate the utility of a TDT system from transportation safety, mobility and environmental applications perspective. This is followed by a review of current studies in the domain of TDT systems. Finally, the critical challenges and promising future research directions in TDT are discussed to overcome existing barriers to realize a safe and operationally efficient connected and automated transportation systems.Comment: 15 pages, 2 figures; corrected issue in author(s) fiel