Reliable and Low-Latency Fronthaul for Tactile Internet Applications

With the emergence of Cloud-RAN as one of the dominant architectural solutions for next-generation mobile networks, the reliability and latency on the fronthaul (FH) segment become critical performance metrics for applications such as the Tactile Internet. Ensuring FH performance is further complicated by the switch from point-to-point dedicated FH links to packet-based multi-hop FH networks. This change is largely justified by the fact that packet-based fronthauling allows the deployment of FH networks on the existing Ethernet infrastructure. This paper proposes to improve reliability and latency of packet-based fronthauling by means of multi-path diversity and erasure coding of the MAC frames transported by the FH network. Under a probabilistic model that assumes a single service, the average latency required to obtain reliable FH transport and the reliability-latency trade-off are first investigated. The analytical results are then validated and complemented by a numerical study that accounts for the coexistence of enhanced Mobile BroadBand (eMBB) and Ultra-Reliable Low-Latency (URLLC) services in 5G networks by comparing orthogonal and non-orthogonal sharing of FH resources.Comment: 11pages, 13 figures, 3 bio photo

Analysis of Bandwidth and Latency Constraints on a Packetized Cloud Radio Access Network Fronthaul

Cloud radio access network (C-RAN) is a promising architecture for the next-generation RAN to meet the diverse and stringent requirements envisioned by fifth generation mobile communication systems (5G) and future generation mobile networks. C-RAN offers several advantages, such as reduced capital expenditure (CAPEX) and operational expenditure (OPEX), increased spectral efficiency (SE), higher capacity and improved cell-edge performance, and efficient hardware utilization through resource sharing and network function virtualization (NFV). However, these centralization gains come with the need for a fronthaul, which is the transport link connecting remote radio units (RRUs) to the base band unit (BBU) pool. In conventional C-RAN, legacy common public radio interface (CPRI) protocol is used on the fronthaul network to transport the raw, unprocessed baseband in-phase/quadrature-phase (I/Q) samples between the BBU and the RRUs, and it demands a huge fronthaul bandwidth, a strict low-latency, in the order of a few hundred microseconds, and a very high reliability. Hence, in order to relax the excessive fronthaul bandwidth and stringent low-latency requirements, as well as to enhance the flexibility of the fronthaul, it is utmost important to redesign the fronthaul, while still profiting from the acclaimed centralization benefits. Therefore, a flexibly centralized C-RAN with different functional splits has been introduced. In addition, 5G mobile fronthaul (often also termed as an evolved fronthaul ) is envisioned to be packet-based, utilizing the Ethernet as a transport technology. In this thesis, to circumvent the fronthaul bandwidth constraint, a packetized fronthaul considering an appropriate functional split such that the fronthaul data rate is coupled with actual user data rate, unlike the classical C-RAN where fronthaul data rate is always static and independent of the traffic load, is justifiably chosen. We adapt queuing and spatial traffic models to derive the mathematical expressions for statistical multiplexing gains that can be obtained from the randomness in the user traffic. Through this, we show that the required fronthaul bandwidth can be reduced significantly, depending on the overall traffic demand, correlation distance and outage probability. Furthermore, an iterative optimization algorithm is developed, showing the impacts of number of pilots on a bandwidth-constrained fronthaul. This algorithm achieves additional reduction in the required fronthaul bandwidth. Next, knowing the multiplexing gains and possible fronthaul bandwidth reduction, it is beneficial for the mobile network operators (MNOs) to deploy the optical transceiver (TRX) modules in C-RAN cost efficiently. For this, using the same framework, a cost model for fronthaul TRX cost optimization is presented. This is essential in C-RAN, because in a wavelength division multiplexing-passive optical network (WDM-PON) system, TRXs are generally deployed to serve at a peak load. But, because of variations in the traffic demands, owing to tidal effect, the fronthaul can be dimensioned requiring a lower capacity allowing a reasonable outage, thus giving rise to cost saving by deploying fewer TRXs, and energy saving by putting the unused TRXs in sleep mode. The second focus of the thesis is the fronthaul latency analysis, which is a critical performance metric, especially for ultra-reliable and low latency communication (URLLC). An analytical framework to calculate the latency in the uplink (UL) of C-RAN massive multiple-input multiple-output (MIMO) system is presented. For this, a continuous-time queuing model for the Ethernet switch in the fronthaul network, which aggregates the UL traffic from several massive MIMO-aided RRUs, is considered. The closed-form solutions for the moment generating function (MGF) of sojourn time, waiting time and queue length distributions are derived using Pollaczek–Khinchine formula for our M/HE/1 queuing model, and evaluated via numerical solutions. In addition, the packet loss rate – due to the inability of the packets to reach the destination in a certain time – is derived. Due to the slotted nature of the UL transmissions, the model is extended to a discrete-time queuing model. The impact of the packet arrival rate, average packet size, SE of users, and fronthaul capacity on the sojourn time, waiting time and queue length distributions are analyzed. While offloading more signal processing functionalities to the RRU reduces the required fronthaul bandwidth considerably, this increases the complexity at the RRU. Hence, considering the 5G New Radio (NR) flexible numerology and XRAN functional split with a detailed radio frequency (RF) chain at the RRU, the total RRU complexity is computed first, and later, a tradeoff between the required fronthaul bandwidth and RRU complexity is analyzed. We conclude that despite the numerous C-RAN benefits, the stringent fronthaul bandwidth and latency constraints must be carefully evaluated, and an optimal functional split is essential to meet diverse set of requirements imposed by new radio access technologies (RATs).Ein cloud-basiertes Mobilfunkzugangsnetz (cloud radio access network, C-RAN) stellt eine vielversprechende Architektur für das RAN der nächsten Generation dar, um die vielfältigen und strengen Anforderungen der fünften (5G) und zukünftigen Generationen von Mobilfunknetzen zu erfüllen. C-RAN bietet mehrere Vorteile, wie z.B. reduzierte Investitions- (CAPEX) und Betriebskosten (OPEX), erhöhte spektrale Effizienz (SE), höhere Kapazität und verbesserte Leistung am Zellrand sowie effiziente Hardwareauslastung durch Ressourcenteilung und Virtualisierung von Netzwerkfunktionen (network function virtualization, NFV). Diese Zentralisierungsvorteile erfordern jedoch eine Transportverbindung (Fronthaul), die die Antenneneinheiten (remote radio units, RRUs) mit dem Pool an Basisbandeinheiten (basisband unit, BBU) verbindet. Im konventionellen C-RAN wird das bestehende CPRI-Protokoll (common public radio interface) für das Fronthaul-Netzwerk verwendet, um die rohen, unverarbeitet n Abtastwerte der In-Phaseund Quadraturkomponente (I/Q) des Basisbands zwischen der BBU und den RRUs zu transportieren. Dies erfordert eine enorme Fronthaul-Bandbreite, eine strenge niedrige Latenz in der Größenordnung von einigen hundert Mikrosekunden und eine sehr hohe Zuverlässigkeit. Um die extrem große Fronthaul-Bandbreite und die strengen Anforderungen an die geringe Latenz zu lockern und die Flexibilität des Fronthauls zu erhöhen, ist es daher äußerst wichtig, das Fronthaul neu zu gestalten und dabei trotzdem von den erwarteten Vorteilen der Zentralisierung zu profitieren. Daher wurde ein flexibel zentralisiertes CRAN mit unterschiedlichen Funktionsaufteilungen eingeführt. Außerdem ist das mobile 5G-Fronthaul (oft auch als evolved Fronthaul bezeichnet) als paketbasiert konzipiert und nutzt Ethernet als Transporttechnologie. Um die Bandbreitenbeschränkung zu erfüllen, wird in dieser Arbeit ein paketbasiertes Fronthaul unter Berücksichtigung einer geeigneten funktionalen Aufteilung so gewählt, dass die Fronthaul-Datenrate mit der tatsächlichen Nutzdatenrate gekoppelt wird, im Gegensatz zum klassischen C-RAN, bei dem die Fronthaul-Datenrate immer statisch und unabhängig von der Verkehrsbelastung ist. Wir passen Warteschlangen- und räumliche Verkehrsmodelle an, um mathematische Ausdrücke für statistische Multiplexing- Gewinne herzuleiten, die aus der Zufälligkeit im Benutzerverkehr gewonnen werden können. Hierdurch zeigen wir, dass die erforderliche Fronthaul-Bandbreite abhängig von der Gesamtverkehrsnachfrage, der Korrelationsdistanz und der Ausfallwahrscheinlichkeit deutlich reduziert werden kann. Darüber hinaus wird ein iterativer Optimierungsalgorithmus entwickelt, der die Auswirkungen der Anzahl der Piloten auf das bandbreitenbeschränkte Fronthaul zeigt. Dieser Algorithmus erreicht eine zusätzliche Reduktion der benötigte Fronthaul-Bandbreite. Mit dem Wissen über die Multiplexing-Gewinne und die mögliche Reduktion der Fronthaul-Bandbreite ist es für die Mobilfunkbetreiber (mobile network operators, MNOs) von Vorteil, die Module des optischen Sendeempfängers (transceiver, TRX) kostengünstig im C-RAN einzusetzen. Dazu wird unter Verwendung des gleichen Rahmenwerks ein Kostenmodell zur Fronthaul-TRX-Kostenoptimierung vorgestellt. Dies ist im C-RAN unerlässlich, da in einem WDM-PON-System (wavelength division multiplexing-passive optical network) die TRX im Allgemeinen bei Spitzenlast eingesetzt werden. Aufgrund der Schwankungen in den Verkehrsanforderungen (Gezeiteneffekt) kann das Fronthaul jedoch mit einer geringeren Kapazität dimensioniert werden, die einen vertretbaren Ausfall in Kauf nimmt, was zu Kosteneinsparungen durch den Einsatz von weniger TRXn und Energieeinsparungen durch den Einsatz der ungenutzten TRX im Schlafmodus führt. Der zweite Schwerpunkt der Arbeit ist die Fronthaul-Latenzanalyse, die eine kritische Leistungskennzahl liefert, insbesondere für die hochzuverlässige und niedriglatente Kommunikation (ultra-reliable low latency communications, URLLC). Ein analytisches Modell zur Berechnung der Latenz im Uplink (UL) des C-RAN mit massivem MIMO (multiple input multiple output) wird vorgestellt. Dazu wird ein Warteschlangen-Modell mit kontinuierlicher Zeit für den Ethernet-Switch im Fronthaul-Netzwerk betrachtet, das den UL-Verkehr von mehreren RRUs mit massivem MIMO aggregiert. Die geschlossenen Lösungen für die momenterzeugende Funktion (moment generating function, MGF) von Verweildauer-, Wartezeit- und Warteschlangenlängenverteilungen werden mit Hilfe der Pollaczek-Khinchin-Formel für unser M/HE/1-Warteschlangenmodell hergeleitet und mittels numerischer Verfahren ausgewertet. Darüber hinaus wird die Paketverlustrate derjenigen Pakete, die das Ziel nicht in einer bestimmten Zeit erreichen, hergeleitet. Aufgrund der Organisation der UL-Übertragungen in Zeitschlitzen wird das Modell zu einem Warteschlangenmodell mit diskreter Zeit erweitert. Der Einfluss der Paketankunftsrate, der durchschnittlichen Paketgröße, der SE der Benutzer und der Fronthaul-Kapazität auf die Verweildauer-, dieWartezeit- und dieWarteschlangenlängenverteilung wird analysiert. Während das Verlagern weiterer Signalverarbeitungsfunktionalitäten an die RRU die erforderliche Fronthaul-Bandbreite erheblich reduziert, erhöht sich dadurch im Gegenzug die Komplexität der RRU. Daher wird unter Berücksichtigung der flexiblen Numerologie von 5G New Radio (NR) und der XRAN-Funktionenaufteilung mit einer detaillierten RF-Kette (radio frequency) am RRU zunächst die gesamte RRU-Komplexität berechnet und später ein Kompromiss zwischen der erforderlichen Fronthaul-Bandbreite und der RRU-Komplexität untersucht. Wir kommen zu dem Schluss, dass trotz der zahlreichen Vorteile von C-RAN die strengen Bandbreiten- und Latenzbedingungen an das Fronthaul sorgfältig geprüft werden müssen und eine optimale funktionale Aufteilung unerlässlich ist, um die vielfältigen Anforderungen der neuen Funkzugangstechnologien (radio access technologies, RATs) zu erfüllen

Performance Improvement of Time-Sensitive Fronthaul Networks in 5G Cloud-RANs Using Reinforcement Learning-Based Scheduling Scheme

The rapid surge in internet-driven smart devices and bandwidth-hungry multimedia applications demands high-capacity internet services and low latencies during connectivity. Cloud radio access networks (C-RANs) are considered the prominent solution to meet the stringent requirements of fifth-generation (5G) and beyond networks by deploying the fronthaul transport links between baseband units (BBUs) and remote radio heads (RRHs). High-capacity optical links could be conventional mainstream technology for deploying the fronthaul in C-RANs. But densification of optical links significantly increases the cost and imposes several design challenges on fronthaul architecture which makes them impractical. Contrary, Ethernet-based fronthaul links can be lucrative solutions for connecting the BBUs and RRHs but are inadequate to meet the rigorous end-to-end delays, jitter, and bandwidth requirements of fronthaul networks. This is because of the inefficient resource allocation and congestion control schemes for the capacity constraint Ethernet-based fronthaul links. In this research, a novel reinforcement learning-based optimal resource allocation scheme has been proposed which eradicates the congestion and improves the latencies to make the capacity-constraints low-cost Ethernet a suitable solution for the fronthaul networks. The experiment results verified a notable 50% improvement in reducing delay and jitter as compared to the existing schemes. Furthermore, the proposed scheme demonstrated an enhancement of up to 70% in addressing conflicting time slots and minimizing packet loss ratios. Hence, the proposed scheme outperforms the existing state-of-the-art resource allocation techniques to satisfy the stringent performance demands of fronthaul networks.</p

Survey on 5G Second Phase RAN Architectures and Functional Splits

The Radio Access Network (RAN) architecture evolves with different generations of mobile communication technologies and forms an indispensable component of the mobile network architecture. The main component of the RAN infrastructure is the base station, which includes a Radio Frequency unit and a baseband unit. The RAN is a collection of base stations connected to the core network to provide coverage through one or more radio access technologies. The advancement towards cloud native networks has led to centralizing the baseband processing of radio signals. There is a trade-off between the advantages of RAN centralization (energy efficiency, power cost reduction, and the cost of the fronthaul) and the complexity of carrying traffic between the data processing unit and distributed antennas. 5G networks hold high potential for adopting the centralized architecture to reduce maintenance costs while reducing deployment costs and improving resilience, reliability, and coordination. Incorporating the concept of virtualization and centralized RAN architecture enables to meet the overall requirements for both the customer and Mobile Network Operator. Functional splitting is one of the key enablers for 5G networks. It supports Centralized RAN, virtualized Radio Access Network, and the recent Open Radio Access Networks. This survey provides a comprehensive tutorial on the paradigms of the RAN architecture evolution, its key features, and implementation challenges. It provides a thorough review of the 3rd Generation Partnership Project functional splitting complemented by associated challenges and potential solutions. The survey also presents an overview of the fronthaul and its requirements and possible solutions for implementation, algorithms, and required tools whilst providing a vision of the evaluation beyond 5G second phase.info:eu-repo/semantics/submittedVersio

Statistical distribution of packet inter-arrival rates in an Ethernet fronthaul

This paper investigates the effects of background traffic streams in the packet inter-arrival rates of an LTE traffic stream, when these streams are transported over the same Ethernet fronthaul network. Contention of background traffic with LTE traffic can occur in a Cloud-RAN that is transporting traffic streams originating from Constant Bit-Rate (CBR) sources such as the Common Public Radio Interface (CPRI) and from other non-CBR sources originating from different LTE physical layer functional subdivisions. Packet inter-arrival statistics are important in such a network, as they can be used to estimate and/or predict buffer sizes in receiving network nodes. Buffer management will also be important for traffic streams originating from functional splits (such as direct LTE MAC transport block transportation) where user plane data and control primitives have to be time aligned at the receiving node

Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.Peer ReviewedPostprint (author's final draft

Software defined wireless network (sdwn) for industrial environment: case of underground mine

Avec le développement continu des industries minières canadiennes, l’établissement des réseaux de communications souterrains avancés et sans fil est devenu un élément essentiel du processus industriel minier et ceci pour améliorer la productivité et assurer la communication entre les mineurs. Cette étude vise à proposer un système de communication minier en procurant une architecture SDWN (Software Defined Wireless Network) basée sur la technologie de communication LTE. Dans cette étude, les plateformes les plus importantes de réseau mobile 4G ont été étudiées, configurées et testées dans deux zones différentes : un tunnel de mine souterrain et un couloir intérieur étroit. Également, une architecture mobile combinant SDWN et NFV (Network Functions Virtualization) a été réalisée