On the Fundamental Limits of Random Non-orthogonal Multiple Access in Cellular Massive IoT

Machine-to-machine (M2M) constitutes the communication paradigm at the basis of Internet of Things (IoT) vision. M2M solutions allow billions of multi-role devices to communicate with each other or with the underlying data transport infrastructure without, or with minimal, human intervention. Current solutions for wireless transmissions originally designed for human-based applications thus require a substantial shift to cope with the capacity issues in managing a huge amount of M2M devices. In this paper, we consider the multiple access techniques as promising solutions to support a large number of devices in cellular systems with limited radio resources. We focus on non-orthogonal multiple access (NOMA) where, with the aim to increase the channel efficiency, the devices share the same radio resources for their data transmission. This has been shown to provide optimal throughput from an information theoretic point of view.We consider a realistic system model and characterise the system performance in terms of throughput and energy efficiency in a NOMA scenario with a random packet arrival model, where we also derive the stability condition for the system to guarantee the performance.Comment: To appear in IEEE JSAC Special Issue on Non-Orthogonal Multiple Access for 5G System

Next Generation M2M Cellular Networks: Challenges and Practical Considerations

In this article, we present the major challenges of future machine-to-machine (M2M) cellular networks such as spectrum scarcity problem, support for low-power, low-cost, and numerous number of devices. As being an integral part of the future Internet-of-Things (IoT), the true vision of M2M communications cannot be reached with conventional solutions that are typically cost inefficient. Cognitive radio concept has emerged to significantly tackle the spectrum under-utilization or scarcity problem. Heterogeneous network model is another alternative to relax the number of covered users. To this extent, we present a complete fundamental understanding and engineering knowledge of cognitive radios, heterogeneous network model, and power and cost challenges in the context of future M2M cellular networks

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

Kapeankaistan LTE koneiden välisessä satelliittitietoliikenteessä

Recent trends to wireless Machine-to-Machine (M2M) communication and Internet of Things (IoT) has created a new demand for more efficient low-throughput wireless data connections. Beside the traditional wireless standards, focused on high bandwidth data transfer, has emerged a new generation of Low Power Wide Area Networks (LPWAN) which targets for less power demanding low-throughput devices requiring inexpensive data connections. Recently released NB-IoT (Narrowband IoT) specification extends the existing 4G/LTE standard allowing more easily accessible LPWAN cellular connectivity for IoT devices. Narrower bandwidth and lower data rates combined to a simplified air interface make it less resource demanding still benefiting from the widely spread LTE technologies and infrastructure. %% Applications & Why space Applications, such as wide scale sensor or asset tracking networks, can benefit from a global scale network coverage and easily available low-cost user equipment which could be made possible by new narrowband IoT satellite networks. In this thesis, the NB-IoT specification and its applicability for satellite communication is discussed. Primarily, LTE and NB-IoT standards are designed only for terrestrial and their utilization in Earth-to-space communication raises new challenges, such as timing and frequency synchronization requirements when utilizing Orthogonal Frequency Signal Multiplexing (OFDM) techniques. Many of these challenges can be overcome by specification adaptations and other existing techniques making minimal changes to the standard and allowing extension of the terrestrial cellular networks to global satellite access.Viimeaikaiset kehitystrendit koneiden välisessä kommunikaatiossa (Machine to Machine Communication, M2M) ja esineiden Internet (Internet of Things, IoT) -sovelluksissa ovat luoneet perinteisteisten nopean tiedonsiirron langattomien standardien ohelle uuden sukupolven LPWAN (Low Power Wide Area Networks) -tekniikoita, jotka ovat tarkoitettu pienitehoisille tiedonsiirtoa tarvitseville sovelluksille. Viimeaikoina yleistynyt NB-IoT standardi laajentaa 4G/LTE standardia mahdollistaen entistä matalamman virrankulutuksen matkapuhelinyhteydet IoT laitteissa. Kapeampi lähetyskaista ja hitaampi tiedonsiirtonopeus yhdistettynä yksinkertaisempaan ilmarajapintaan mahdollistaa pienemmän resurssivaatimukset saman aikaan hyötyen laajalti levinneistä LTE teknologioista ja olemassa olevasta infrastruktuurista. Useissa sovelluskohteissa, kuten suurissa sensoriverkoissa, voitaisiin hyötyä merkittävästi globaalista kattavuudesta yhdistettynä edullisiin helposti saataviin päätelaitteisiin. Tässä työssä käsitellään NB-IoT standardia ja sen soveltuvuutta satellittitietoliikenteeseen. LTE ja NB-IoT ovat kehitty maanpääliseen tietoliikenteeseen ja niiden hyödyntäminen avaruuden ja maan välisessä kommunikaatiossa aiheuttaa uusia haasteita esimerkiksi aika- ja taajuussynkronisaatiossa ja OFDM (Orthogonal Frequency Signal Multiplexing) -tekniikan hyödyntämisessä. Nämä haasteet voidaan ratkaista soveltamalla spesifikaatiota sekä muilla jo olemassa olevilla tekniikoilla tehden mahdollisimman vähän muutoksia alkuperäiseen standardiin, ja täten sallien maanpäälisten IoT verkkojen laajenemisen avaruuteen

Platforms and Protocols for the Internet of Things

Building a general architecture for the Internet of Things (IoT) is a very complex task, exacerbated by the extremely large variety of devices, link layer technologies, and services that may be involved in such a system. In this paper, we identify the main blocks of a generic IoT architecture, describing their features and requirements, and analyze the most common approaches proposed in the literature for each block. In particular, we compare three of the most important communication technologies for IoT purposes, i.e., REST, MQTT, and AMQP, and we also analyze three IoT platforms: openHAB, Sentilo, and Parse. The analysis will prove the importance of adopting an integrated approach that jointly addresses several issues and is able to flexibly accommodate the requirements of the various elements of the system. We also discuss a use case which illustrates the design challenges and the choices to make when selecting which protocols and technologies to use