Overload-state downlink resource scheduling and its challenges towards 5G networks

The growing variety and consumption of the mobile services throughout the cellular networks lead to various challenging issues in radio resource scheduling. To have an apparent perspective over the resource scheduling in real implementation of the next generation cellular networks, it is essential to consider sequences of alternating overload and normal states of the traffic, occurring much in the system. In this paper, we do a performance study of three overload-state schedulers by implementing such a network environment and exploiting the advantages and drawbacks of the compared algorithms. This performance study through the simulation results reveals that the existing overload-state resource scheduling schemes do not satisfy the fifth generation (5G) mobile network's requirements to be more optimized in hard real time fashion. Then, open challenges and potential research directions for resource management in future 5G mobile networks are presented at the end

Overload-state downlink resource scheduling and its challenges towards 5G networks

The growing variety and consumption of the mobile services throughout the cellular networks lead to various challenging issues in radio resource scheduling. To have an apparent perspective over the resource scheduling in real implementation of the next generation cellular networks, it is essential to consider sequences of alternating overload and normal states of the traffic, occurring much in the system. In this paper, we do a performance study of three overload-state schedulers by implementing such a network environment and exploiting the advantages and drawbacks of the compared algorithms. This performance study through the simulation results reveals that the existing overload-state resource scheduling schemes do not satisfy the fifth generation (5G) mobile network's requirements to be more optimized in hard real time fashion. Then, open challenges and potential research directions for resource management in future 5G mobile networks are presented at the end

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

Massive Non-Orthogonal Multiple Access for Cellular IoT: Potentials and Limitations

The Internet of Things (IoT) promises ubiquitous connectivity of everything everywhere, which represents the biggest technology trend in the years to come. It is expected that by 2020 over 25 billion devices will be connected to cellular networks; far beyond the number of devices in current wireless networks. Machine-to-Machine (M2M) communications aims at providing the communication infrastructure for enabling IoT by facilitating the billions of multi-role devices to communicate with each other and with the underlying data transport infrastructure without, or with little, human intervention. Providing this infrastructure will require a dramatic shift from the current protocols mostly designed for human-to-human (H2H) applications. This article reviews recent 3GPP solutions for enabling massive cellular IoT and investigates the random access strategies for M2M communications, which shows that cellular networks must evolve to handle the new ways in which devices will connect and communicate with the system. A massive non-orthogonal multiple access (NOMA) technique is then presented as a promising solution to support a massive number of IoT devices in cellular networks, where we also identify its practical challenges and future research directions.Comment: To appear in IEEE Communications Magazin

Machine-type communications: current status and future perspectives toward 5G systems

Machine-type communications (MTC) enables a broad range of applications from mission- critical services to massive deployment of autonomous devices. To spread these applications widely, cellular systems are considered as a potential candidate to provide connectivity for MTC devices. The ubiquitous deployment of these systems reduces network installation cost and provides mobility support. However, based on the service functions, there are key challenges that currently hinder the broad use of cellular systems for MTC. This article provides a clear mapping between the main MTC service requirements and their associated challenges. The goal is to develop a comprehensive understanding of these challenges and the potential solutions. This study presents, in part, a roadmap from the current cellular technologies toward fully MTC-capable 5G mobile systems.Peer reviewe