Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&

Korkean luotettavuuden verkkohallinteiset laitteiden väliset yhteydet

Fifth generation cellular networks aim to provide new types of services. Prominent amongst these are industrial automation and vehicle-to-vehicle communications. Such new use cases demand lower latencies and higher reliability along with greater flexibility than current and past generations of cellular technologies allow. Enabling these new service types requires the introduction of device-to-device communications (D2D). This work investigated network-controlled D2D schemes wherein cellular base stations retain control over spectrum usage. D2D nodes assemble into clusters. Each D2D cluster then organises itself as it sees fit within the constraints imposed by the cellular network. A review of proposed D2D control schemes was conducted to identify pertinent interference issues. Measurements were then devised to empirically collect quantitative data on the impact of this interference. Measurements were conducted using a software-defined radio (SDR) platform. An SDR based system was selected to enable a low cost and highly flexible iterative approach to development while still providing the accuracy of real-world measurement. D2D functionality was added to the chosen SDR system with the essential parts of Long Term Evolution Release 8 implemented. Two series of measurements were performed. The first aimed to determine the adjacent channel interference impact of a cellular user being located near a D2D receiver. The second measurement series collected data on the co-channel interference of spectrum re-use between a D2D link and a moving cellular transmitter. Based on these measurements it was determined that D2D communications within a cellular system is feasible. Furthermore, the required frequency of channel state information reporting as a function of node velocity was determined.Viidennen sukupolven solukkoverkoilla pyritään mahdollistamaan uudentyyppisiä palveluja kuten teollisuusautomatiikkaa ja ajoneuvojen välistä viestintää. Tämänkaltaiset uudet käyttötarkoitukset vaativat lyhyempien viiveiden ja korkeammat luotettavuuden ohella myös suurempaa joustavuutta kuin minkä nykyisen sukupolven matkapuhelinverkkoteknologiat sallivat. Edellä mainittujen uusien palvelujen toteuttaminen vaatii suoria laitteiden välisiä yhteyksiä (engl. D2D). Tässä diplomityössä keskityttiin tutkimaan verkkohallinteisia D2D-rakenteita, joissa solukkoverkko hallinnoi spektrin käyttöä. D2D-päätteet liittyvät yhteen muodostaakseen klustereita, jotka hallinnoivat sisäistä tietoliikennettään parhaaksi katsomallaan tavalla solukkoverkon asettamien rajoitusten puitteissa. Kirjallisuuskatsauksen avulla selvitettiin aiemmissa tutkimuksissa esitetyille D2D-ratkaisuille yhteiset interferenssiongelmat. Näiden vaikutusta ja suuruutta tutkittiin mittausten avulla. Mittaukset toteutettiin ohjelmistoradioalustan (engl. SDR) avulla. SDR-pohjaisen järjestelmän käyttö mahdollisti edullisen ja joustavan tavan kerätä empiirisiä mittaustuloksia. D2D-toiminnallisuus lisättiin Long Term Evolution Release 8:n olennaiset ominaisuudet omaavaan alustaan. Tällä alustalla toteutettiin kaksi mittaussarjaa. Ensimmäisellä kerättiin tuloksia viereisellä kanavalla toimivan matkapuhelimen D2D-vastaanottimelle aiheuttamasta interferenssistä näiden ollessa toistensa läheisyydessä. Toisella mittaussarjalla selvitettiin samalla kanavalla toimivan D2D-yhteyden ja liikkuvan matkapuhelimen välistä interferenssiä. Mittausten perusteella todettiin D2D-toiminnallisuuden lisäämisen solukkoverkkoon olevan mahdollista. Lisäksi laskettiin vaadittava kanavalaadun päivitystiheys päätteiden nopeuden funktiona

Recent Advances in Cellular D2D Communications

Device-to-device (D2D) communications have attracted a great deal of attention from researchers in recent years. It is a promising technique for offloading local traffic from cellular base stations by allowing local devices, in physical proximity, to communicate directly with each other. Furthermore, through relaying, D2D is also a promising approach to enhancing service coverage at cell edges or in black spots. However, there are many challenges to realizing the full benefits of D2D. For one, minimizing the interference between legacy cellular and D2D users operating in underlay mode is still an active research issue. With the 5th generation (5G) communication systems expected to be the main data carrier for the Internet-of-Things (IoT) paradigm, the potential role of D2D and its scalability to support massive IoT devices and their machine-centric (as opposed to human-centric) communications need to be investigated. New challenges have also arisen from new enabling technologies for D2D communications, such as non-orthogonal multiple access (NOMA) and blockchain technologies, which call for new solutions to be proposed. This edited book presents a collection of ten chapters, including one review and nine original research works on addressing many of the aforementioned challenges and beyond

FiFo: Fishbone Forwarding in Massive IoT Networks

Massive Internet of Things (IoT) networks have a wide range of applications, including but not limited to the rapid delivery of emergency and disaster messages. Although various benchmark algorithms have been developed to date for message delivery in such applications, they pose several practical challenges such as insufficient network coverage and/or highly redundant transmissions to expand the coverage area, resulting in considerable energy consumption for each IoT device. To overcome this problem, we first characterize a new performance metric, forwarding efficiency, which is defined as the ratio of the coverage probability to the average number of transmissions per device, to evaluate the data dissemination performance more appropriately. Then, we propose a novel and effective forwarding method, fishbone forwarding (FiFo), which aims to improve the forwarding efficiency with acceptable computational complexity. Our FiFo method completes two tasks: 1) it clusters devices based on the unweighted pair group method with the arithmetic average; and 2) it creates the main axis and sub axes of each cluster using both the expectation-maximization algorithm for the Gaussian mixture model and principal component analysis. We demonstrate the superiority of FiFo by using a real-world dataset. Through intensive and comprehensive simulations, we show that the proposed FiFo method outperforms benchmark algorithms in terms of the forwarding efficiency.Comment: 13 pages, 16 figures, 5 tables; to appear in the IEEE Internet of Things Journal (Please cite our journal version that will appear in an upcoming issue.