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

Massive MIMO for Internet of Things (IoT) Connectivity

Massive MIMO is considered to be one of the key technologies in the emerging 5G systems, but also a concept applicable to other wireless systems. Exploiting the large number of degrees of freedom (DoFs) of massive MIMO essential for achieving high spectral efficiency, high data rates and extreme spatial multiplexing of densely distributed users. On the one hand, the benefits of applying massive MIMO for broadband communication are well known and there has been a large body of research on designing communication schemes to support high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT) is still a developing topic, as IoT connectivity has requirements and constraints that are significantly different from the broadband connections. In this paper we investigate the applicability of massive MIMO to IoT connectivity. Specifically, we treat the two generic types of IoT connections envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC). This paper fills this important gap by identifying the opportunities and challenges in exploiting massive MIMO for IoT connectivity. We provide insights into the trade-offs that emerge when massive MIMO is applied to mMTC or URLLC and present a number of suitable communication schemes. The discussion continues to the questions of network slicing of the wireless resources and the use of massive MIMO to simultaneously support IoT connections with very heterogeneous requirements. The main conclusion is that massive MIMO can bring benefits to the scenarios with IoT connectivity, but it requires tight integration of the physical-layer techniques with the protocol design.Comment: Submitted for publicatio

Goodbye, ALOHA!

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The vision of the Internet of Things (IoT) to interconnect and Internet-connect everyday people, objects, and machines poses new challenges in the design of wireless communication networks. The design of medium access control (MAC) protocols has been traditionally an intense area of research due to their high impact on the overall performance of wireless communications. The majority of research activities in this field deal with different variations of protocols somehow based on ALOHA, either with or without listen before talk, i.e., carrier sensing multiple access. These protocols operate well under low traffic loads and low number of simultaneous devices. However, they suffer from congestion as the traffic load and the number of devices increase. For this reason, unless revisited, the MAC layer can become a bottleneck for the success of the IoT. In this paper, we provide an overview of the existing MAC solutions for the IoT, describing current limitations and envisioned challenges for the near future. Motivated by those, we identify a family of simple algorithms based on distributed queueing (DQ), which can operate for an infinite number of devices generating any traffic load and pattern. A description of the DQ mechanism is provided and most relevant existing studies of DQ applied in different scenarios are described in this paper. In addition, we provide a novel performance evaluation of DQ when applied for the IoT. Finally, a description of the very first demo of DQ for its use in the IoT is also included in this paper.Peer ReviewedPostprint (author's final draft

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

A use case of low power wide area networks in future 5G healthcare applications

Abstract. The trend in all cellular evolution to the Long-Term Evolution (LTE) has always been to offer users continuously increasing data rates. However, the next leap forwards towards the 5th Generation Mobile Networks (5G) will be mainly addressing the needs of devices. Machines communicating with each other, sensors reporting to a server, or even machines communicating with humans, these are all different aspects of the same technology; the Internet of Things (IoT). The key differentiator between Machine-to-Machine (M2M) communications and IoT will be the added -feature of connecting devices and sensors not only to themselves, but also to the internet. The appropriate communications network is the key to allow this connectivity. Local Area Networks (LANs) and Wide Area Networks (WANs) have been thought of as enablers for IoT, but since they both suffered from limitations in IoT aspects, the need for a new enabling technology was evident. LPWANs are networks dedicated to catering for the needs of IoT such as providing low energy consumption for wireless devices. LPWANs can be categorized into proprietary LPWANs and cellular LPWANs. Proprietary LPWANs are created by an alliance of companies working together on creating a communications standard operating in unlicensed frequency bands. An example of proprietary LPWANs is LoRa. Whereas cellular LPWANs are standardized by the 3rd Partnership Project (3GPP) and they are basically versions of the LTE standard especially designed for machine communications. An example of cellular LPWANs is Narrowband IoT (NB IoT). This diploma thesis documents the usage of LoRa and NB IoT in a healthcare use case of IoT. It describes the steps and challenges of deploying an LTE network at a target site, which will be used by the LoRa and NB IoT sensors to transmit data through the 5G test network (5GTN) to a desired server location for storing and later analysis.Matalan tehonkulutuksen ja pitkänkantaman teknologian käyttötapaus tulevaisuuden 5G:tä hyödyntävissä terveydenhoidon sovelluksissa. Tiivistelmä. Pitemmän aikavälin tarkastelussa matkaviestintäteknologian kehittyminen nykyisin käytössä olevaan Long-Term Evolution (LTE) teknologiaan on tarkoittanut käyttäjille yhä suurempia datanopeuksia. Seuraavassa askeleessa kohti 5. sukupolven matkaviestintäverkkoja (5G) lähestytään kehitystä myös laitteiden tarpeiden lähtökohdista. Toistensa kanssa kommunikoivat koneet, palvelimille dataa lähettävät anturit tai jopa ihmisten kanssa kommunikoivat koneet ovat kaikki eri puolia samasta teknologisesta käsitteestä; esineiden internetistä (IoT). Oleellisin ero koneiden välisessä kommunikoinnissa (M2M) ja IoT:ssä on, että erinäiset laitteet tulevat olemaan yhdistettyinä paitsi toisiinsa myös internettiin. Tätä kytkentäisyyttä varten tarvitaan tarkoitukseen kehitetty matkaviestinverkko. Sekä lähiverkkoja (LAN) että suuralueverkkoja (WAN) on pidetty mahdollisina IoT mahdollistajina, mutta näiden molempien käsitteiden alle kuuluvissa teknologioissa on rajoitteita IoT:n vaatimusten lähtökohdista, joten uuden teknologian kehittäminen oli tarpeellista. Matalan tehonkulutuksen suuralueverkko (LP-WAN) on käsite, johon luokitellaan eri teknologioita, joita on kehitetty erityisesti IoT:n tarpeista lähtien. LP-WAN voidaan jaotella ainakin itse kehitettyihin ja matkaviestinverkkoihin perustuviin teknologisiin ratkaisuihin. Itse kehitetyt ratkaisut on luotu lukuisten yritysten yhteenliittymissä eli alliansseissa ja nämä ratkaisut keskittyvät lisensoimattomilla taajuuksilla toimiviin langattomiin ratkaisuihin, joista esimerkkinä laajasti käytössä oleva LoRa. Matkaviestinverkkoihin perustuvat lisensoiduilla taajuuksilla toimivat ratkaisut on puolestaan erikseen standardoitu 3GPP-nimisessä yhteenliittymässä, joka nykyisellään vastaa 2G, 3G ja LTE:n standardoiduista päätöksistä. Esimerkki 3GPP:n alaisesta LPWAN-luokkaan kuuluvasta teknologiasta on kapea kaistainen IoT-teknologia, NB-IoT. Tässä diplomityössä keskitytään terveydenhoidon käyttötapaukseen, missä antureiden mittaamaa tietoa siirretään langattomasti käyttäen sekä LoRa että NB-IoT teknologioita. Työssä kuvataan eri vaiheet ja haasteet, joita liittyi kun rakennetaan erikseen tiettyyn kohteeseen LTE-verkon radiopeitto, jotta LoRa:a ja NB-IoT:a käyttävät anturit saadaan välittämään mitattua dataa halutulle palvelimelle säilytykseen ja myöhempää analysointia varten. LTE-radiopeiton rakensi Oulun yliopiston omistama 5G testiverkko, jonka tarkoitus on tukea sekä tutkimusta että ympäröivää ekosysteemiä tulevaisuuden 5G:n kehityksessä

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, and support for a large number of low-power, lowcost devices. As 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. The cognitive radio concept has emerged to address spectrum under-utilization and scarcity. The heterogeneous network model is another alternative to relax the number of covered users. To this extent, we present a complete fundamental understanding and the engineering details of cognitive radios, the heterogeneous network model, and power and cost challenges in the context of future M2M cellular networks.pre-prin

A survey on 5G networks for the Internet of Things : communication technologies and challenges

The Internet of Things (IoT) is a promising technology which tends to revolutionize and connect the global world via heterogeneous smart devices through seamless connectivity. The current demand for machine-type communications (MTC) has resulted in a variety of communication technologies with diverse service requirements to achieve the modern IoT vision. More recent cellular standards like long-term evolution (LTE) have been introduced for mobile devices but are not well suited for low-power and low data rate devices such as the IoT devices. To address this, there is a number of emerging IoT standards. Fifth generation (5G) mobile network, in particular, aims to address the limitations of previous cellular standards and be a potential key enabler for future IoT. In this paper, the state-of-the-art of the IoT application requirements along with their associated communication technologies are surveyed. In addition, the third generation partnership project cellular-based low-power wide area solutions to support and enable the new service requirements for Massive to Critical IoT use cases are discussed in detail, including extended coverage global system for mobile communications for the Internet of Things, enhanced machine-type communications, and narrowband-Internet of Things. Furthermore, 5G new radio enhancements for new service requirements and enabling technologies for the IoT are introduced. This paper presents a comprehensive review related to emerging and enabling technologies with main focus on 5G mobile networks that is envisaged to support the exponential traf c growth for enabling the IoT. The challenges and open research directions pertinent to the deployment of massive to critical IoT applications are also presented in coming up with an ef cient context-aware congestion control mechanism.In part by the Department of Research and International Support, University of Pretoria, South Africa, and in part by the Meraka Institute, Council for Scientific and Industrial Research, South Africa.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639am2018Electrical, Electronic and Computer Engineerin

Radio resource allocation algorithms for multicast OFDM systems

Mención Internacional en el título de doctorVideo services have become highly demanded in mobile networks leading to an unprecedented traffic growth. It is expected that traffic from wireless and mobile devices will account for nearly 70 percent of total IP traffic by the year 2020, and the video services will account for nearly 75 percent of mobile data traffic by 2022. Multicast transmission is one of the key enablers towards a more spectral and energy efficient distribution of multimedia content in current and envisaged mobile networks. It is worth noting that multicast is a mechanism that efficiently delivers the same content to many users, not only focusing on video broadcasting, but also distributing many other media, such as software updates, weather forecast or breaking news. Although multicast services are available in Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, new improvements are needed in some areas to handle the demands expected in the near future. Resource allocation techniques for multicast services are one of the main challenging issues, since it is required the development of novel schemes to meet the demands of their evolution towards the next generation. Most multicast techniques adopt rather conservative strategies that select a very robust modulation and coding scheme (MCS), whose characteristics are determined by the propagation conditions experienced by the worst user in the group in order to ensure that all users in a multicast group are able to correctly decode the received data. Obviously, this robustness comes at the prize of a low spectral efficiency. This thesis presents an exhaustive study of broadcast/multicast technology for current mobile networks, especially focusing on the scheduling and resource allocation (SRA) strategies to maximize the potential benefits that multicast transmissions imply on the spectral efficiency. Based on that issue, some contributions have been made to the state of the art in the radio resource management (RRM) for current and beyond mobile multicast services. • In the frame of LTE/LTE-A, the evolved multimedia broadcast and multicast service (eMBMS) shares the physical layer resources with the unicast transmission mode (at least up to Release 12). Consequently, the time allocation to multicast transmission is limited to a maximum of a 60 percent, and the remaining subframes (at least 40 percent) are reserved for unicast transmissions. With the aim of achieving the maximum aggregated data rate (ADR) among the multicast users, we have implemented several innovative SRA schemes that combine the allocation of multicast and unicast resources in the LTE/LTE-A frame, guaranteeing the prescribed quality of service (QoS) requirements for every user. • In the specific context of wideband communication systems, the selection of the multicast MCS has often relied on the use of wideband channel quality indicators (CQIs), providing rather imprecise information regarding the potential capacity of the multicast channel. Only recently has the per-subband CQI been used to improve the spectral efficiency of the system without compromising the link robustness. We have proposed novel subband CQI-based multicast SRA strategies that, relying on the selection of more spectrally efficient transmission modes, lead to increased data rates while still being able to fulfill prescribed QoS metrics. • Mobile broadcast/multicast video services require effective and low complexity SRA strategies. We have proposed an SRA strategy based on multicast subgrouping and the scalable video coding (SVC) technique for multicast video delivery. This scheme focuses on reducing the search space of solutions and optimizes the ADR. The results in terms of ADR, spectral efficiency, and fairness among multicast users, along with the low complexity of the algorithm, show that this new scheme is adequate for real systems. These contributions are intended to serve as a reference that motivate ongoing and future investigation in the challenging field of RRM for broadcast/ multicast services in next generation mobile networks.La demanda de servicios de vídeo en las redes móviles ha sufrido un incremento exponencial en los últimos años, lo que a su vez ha desembocado en un aumento sin precedentes del tráfico de datos. Se espera que antes del año 2020, el trafico debido a dispositivos móviles alcance cerca del 70 por ciento del tráfico IP total, mientras que se prevé que los servicios de vídeo sean prácticamente el 75 por ciento del tráfico de datos en las redes móviles hacia el 2022. Las transmisiones multicast son una de las tecnologías clave para conseguir una distribución más eficiente, tanto espectral como energéticamente, del contenido multimedia en las redes móviles actuales y futuras. Merece la pena reseñar que el multicast es un mecanismo de entrega del mismo contenido a muchos usuarios, que no se enfoca exclusivamente en la distribución de vídeo, sino que también permite la distribución de otros muchos contenidos, como actualizaciones software, información meteorológica o noticias de última hora. A pesar de que los servicios multicast ya se encuentran disponibles en las redes Long Term Evolution (LTE) y LTE-Advanced (LTE-A), la mejora en algunos ámbitos resulta necesaria para manejar las demandas que se prevén a corto plazo. Las técnicas de asignación de recursos para los servicios multicast suponen uno de los mayores desafíos, ya que es necesario el desarrollo de nuevos esquemas que nos permitan acometer las exigencias que supone su evolución hacia la próxima generación. La mayor parte de las técnicas multicast adoptan estrategias conservadoras, seleccionando esquemas de modulación y codificación (MCS) impuestos por las condiciones de propagación que experimenta el usuario del grupo con peor canal, para así asegurar que todos los usuarios pertenecientes al grupo multicast sean capaces de decodificar correctamente los datos recibidos. Como resulta obvio, la utilización de esquemas tan robustos conlleva el precio de sufrir una baja eficiencia espectral. Esta tesis presenta un exhaustivo estudio de la tecnología broadcast/ multicast para las redes móviles actuales, que se centra especialmente en las estrategias de asignación de recursos (SRA), cuyo objetivo es maximizar los beneficios que la utilización de transmisiones multicast potencialmente implica en términos de eficiencia espectral. A partir de dicho estudio, hemos realizado varias contribuciones al estado del arte en el ámbito de la gestión de recursos radio (RRM) para los servicios multicast, aplicables en las redes móviles actuales y futuras. • En el marco de LTE/LTE-A, el eMBMS comparte los recursos de la capa física con las transmisiones unicast (al menos hasta la revisión 12). Por lo tanto, la disponibilidad temporal de las transmisiones multicast está limitada a un máximo del 60 por ciento, reservándose las subtramas restantes (al menos el 40 por ciento) para las transmisiones unicast. Con el objetivo de alcanzar la máxima tasa total de datos (ADR) entre los usuarios multicast, hemos implementado varios esquemas innovadores de SRA que combinan la asignación de los recursos multicast y unicast de la trama LTE/LTE-A, garantizando los requisitos de QoS a cada usuario. • En los sistemas de comunicaciones de banda ancha, la selección del MCS para transmisiones multicast se basa habitualmente en la utilización de CQIs de banda ancha, lo que proporciona información bastante imprecisa acerca de la capacidad potencial del canal multicast. Recientemente se ha empezado a utilizar el CQI por subbanda para mejorar la eficiencia espectral del sistema sin comprometer la robustez de los enlaces. Hemos propuesto nuevas estrategias para SRA multicast basadas en el CQI por subbanda que, basándose en la selección de los modos de transmisión con mayor eficiencia espectral, conducen a mejores tasas de datos, a la vez que permiten cumplir los requisitos de QoS. • Los servicios móviles de vídeo broadcast/multicast precisan estrategias eficientes de SRA con baja complejidad. Hemos propuesto una estrategia de SRA basada en subgrupos multicast y la técnica de codificación de vídeo escalable (SVC) para la difusión de vídeo multicast, la cual se centra en reducir el espacio de búsqueda de soluciones y optimizar el ADR. Los resultados obtenidos en términos de ADR, eficiencia espectral y equidad entre los usuarios multicast, junto con la baja complejidad del algoritmo, ponen de manifiesto que el esquema propuesto es adecuado para su implantación en sistemas reales. Estas contribuciones pretenden servir de referencia que motive la investigación actual y futura en el interesante ámbito de RRM para los servicios broadcast/multicast en las redes móviles de próxima generación.Programa Oficial de Doctorado en Multimedia y ComunicacionesPresidente: Atilio Manuel Da Silva Gameiro.- Secretario: Víctor Pedro Gil Jiménez.- Vocal: María de Diego Antó

PROCESS FOR BREAKING DOWN THE LTE SIGNAL TO EXTRACT KEY INFORMATION

The increasingly important role of Long Term Evolution (LTE) has increased security concerns among the service providers and end users and made security of the network even more indispensable. The main thrust of this thesis is to investigate if the LTE signal can be broken down in a methodical way to obtain information that would otherwise be private; e.g., the Global Positioning System (GPS) location of the user equipment/base station or identity (ID) of the user. The study made use of signal simulators and software to analyze the LTE signal to develop a method to remove noise, breakdown the LTE signal and extract desired information. From the simulation results, it was possible to extract key information in the downlink like the Downlink Control Information (DCI), Cell-Radio Network Temporary Identifier (C-RNTI) and physical Cell Identity (Cell-ID). This information can be modified to cause service disruptions in the network within a reasonable amount of time and with modest computing resources.Defence Science and Technology Agency, SingaporeApproved for public release; distribution is unlimited