Integration of Carrier Aggregation and Dual Connectivity for the ns-3 mmWave Module

Thanks to the wide availability of bandwidth, the millimeter wave (mmWave) frequencies will provide very high data rates to mobile users in next generation 5G cellular networks. However, mmWave links suffer from high isotropic pathloss and blockage from common materials, and are subject to an intermittent channel quality. Therefore, protocols and solutions at different layers in the cellular network and the TCP/IP protocol stack have been proposed and studied. A valuable tool for the end-to-end performance analysis of mmWave cellular networks is the ns-3 mmWave module, which already models in detail the channel, Physical (PHY) and Medium Access Control (MAC) layers, and extends the Long Term Evolution (LTE) stack for the higher layers. In this paper we present an implementation for the ns-3 mmWave module of multi connectivity techniques for 3GPP New Radio (NR) at mmWave frequencies, namely Carrier Aggregation (CA) and Dual Connectivity (DC), and discuss how they can be integrated to increase the functionalities offered by the ns-3 mmWave module.Comment: 9 pages, 7 figures, submitted to the Workshop on ns-3 (WNS3) 201

Enabling RAN Slicing Through Carrier Aggregation in mmWave Cellular Networks

The ever increasing number of connected devices and of new and heterogeneous mobile use cases implies that 5G cellular systems will face demanding technical challenges. For example, Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) scenarios present orthogonal Quality of Service (QoS) requirements that 5G aims to satisfy with a unified Radio Access Network (RAN) design. Network slicing and mmWave communications have been identified as possible enablers for 5G. They provide, respectively, the necessary scalability and flexibility to adapt the network to each specific use case environment, and low latency and multi-gigabit-per-second wireless links, which tap into a vast, currently unused portion of the spectrum. The optimization and integration of these technologies is still an open research challenge, which requires innovations at different layers of the protocol stack. This paper proposes to combine them in a RAN slicing framework for mmWaves, based on carrier aggregation. Notably, we introduce MilliSlice, a cross-carrier scheduling policy that exploits the diversity of the carriers and maximizes their utilization, thus simultaneously guaranteeing high throughput for the eMBB slices and low latency and high reliability for the URLLC flows.Comment: 8 pages, 8 figures. Proc. of the 18th Mediterranean Communication and Computer Networking Conference (MedComNet 2020), Arona, Italy, 202

Implementation of Reference Public Safety Scenarios in ns-3

During incidents and disasters it is fundamental to provide to first responders high performance and reliable communications, in order to improve their coordination capabilities and their awareness of the surrounding environment, and to allow them to promptly transmit and receive alerts on possible dangerous situations or emergencies. The accurate evaluation of the performance of different Public Safety Communication (PSC) networking and communications technologies is therefore of paramount importance, and the characterization of the scenario in which these technologies need to operate is fundamental to obtain meaningful results. In this paper, we present the implementation of three reference PSC scenarios, which are open source and made publicly available to the research community, describing the incidents, the mobility and applications of first responders, and providing examples on how a mmWave-based Radio Access Network (RAN) can support high-traffic use cases. Moreover, we present the implementation of two novel mobility models for ns-3, which can be used to enable the simulation of realistic PSC scenarios in ns-3.Comment: 8 pages, 9 figures, submitted to WNS3 201

NR V2X Communications at Millimeter Waves: An End-to-End Performance Evaluation

3GPP NR V2X represents the new 3GPP standard for next-generation vehicular systems which, among other innovations, supports vehicle-to-vehicle (V2V) operations in the millimeter wave (mmWave) spectrum to address the communication requirements of future intelligent automotive networks. While mmWaves will enable massive data rates and low latency, the propagation characteristics at very high frequencies become very challenging, thereby calling for accurate performance evaluations as a means to properly assess the performance of such systems. Along these lines, in this paper MilliCar, the new ns-3 module based on the latest NR V2X specifications, is used to provide an end-to-end performance evaluation of mmWave V2V networks. We investigate the impact of different propagation scenarios and system parameters, including the inter-vehicle distance, the adopted frame numerology, and the modulation and coding scheme, and provide guidelines towards the most promising V2V deployment configurations.Comment: 6 pages, 7 figures. Submitted to IEEE Globecom 202

Programmable and customized intelligence for traffic steering in 5G networks using open RAN architectures

5G and beyond mobile networks will support heterogeneous use cases at an unprecedented scale, thus demanding automated control and optimization of network functionalities customized to the needs of individual users. Such fine-grained control of the Radio Access Network (RAN) is not possible with the current cellular architecture. To fill this gap, the Open RAN paradigm and its specification introduce an “open” architecture with abstractions that enable closed-loop control and provide data-driven, and intelligent optimization of the RAN at the userlevel. This is obtained through custom RAN control applications (i.e., xApps) deployed on near-real-time RAN Intelligent Controller (near-RT RIC) at the edge of the network. Despite these premises, as of today the research community lacks a sandbox to build data-driven xApps, and create large-scale datasets for effective Artificial Intelligence (AI) training. In this paper, we address this by introducing ns-O-RAN , a software framework that integrates a real-world, production-grade near- RT RIC with a 3GPP-based simulated environment on ns-3, enabling at the same time the development of xApps and automated large-scale data collection and testing of Deep Reinforcement Learning (DRL)- driven control policies for the optimization at the user-level. In addition, we propose the first user-specific O-RAN Traffic Steering (TS) intelligent handover framework. It uses Random Ensemble Mixture (REM), a Conservative Q-learning (CQL) algorithm, combined with a state-of-the-art Convolutional Neural Network (CNN) architecture, to optimally assign a serving base station to each user in the network. Our TS xApp, trained with more than 40 million data points collected by ns-O-RAN, runs on the near-RT RIC and controls the ns-O-RAN base stations. We evaluate the performance on a large-scale deployment with up to 126 users with 8 base stations, showing that the xApp-based handover improves throughput and spectral efficiency by an average of 50% over traditional handover heuristics, with less mobility overhead

Analisi e progettazione di modelli, algoritmi e architetture per reti cellulari di prossima generazione

A causa del sempre maggior numero di utenti, della crescente domanda di dati mobili e della nascita di nuove applicazioni, le reti cellulari necessitano di costante aggiornamento. L’ultima generazione di reti mobili, le reti 5G, è caratterizzata da elevate prestazioni ed estrema flessibilità, grazie alle quali è possibile supportare vari casi d’uso con diversi requisiti di servizio. Le comunicazioni a frequenze millimetriche rappresentano una delle principali novità dello standard 5G, perché consentono l’utilizzo di una vasta porzione di risorse radio ed il raggiungimento di elevate velocità di trasmissione. Tuttavia, la realizzazione di sistemi cellulari operanti a tali frequenze è soggetta a numerose problematiche che derivano dalle severe condizioni di propagazione dei segnali radio. Questa tesi si pone l’obiettivo di fornire soluzioni innovative per risolvere le problematiche realizzative e sfruttare appieno i benefici di questa tecnologia. Nello specifico, (i) vengono presentati nuovi strumenti per la simulazione delle reti di prossima generazione, tra cui un modello di canale e modelli per la caratterizzazione delle antenne e delle operazioni di beamforming; (ii) vengono identificati i benefici e le problematiche relative alla realizzazione di reti millimetriche con backhaul senza fili e viene presentato un efficiente meccanismo di ripartizione delle risorse; (iii) viene analizzata l’interazione cross-layer che deriva dall’utilizzo congiunto di soluzioni HBF e MU-MIMO; (iv) viene introdotto un sistema innovativo per l’implementazione del paradigma di network slicing all’interno di una rete di accesso a frequenze millimetriche e, infine, (v) viene valutata la possibilità di supportare servizi di comunicazioni veicolare attraverso comunicazioni a frequenze millimetriche. L’approccio di tipo “system-level” utilizzato in questa tesi permette di caratterizzare il comportamento della rete in modo adeguato, prendendo in considerazione l’intero stack protocollare e tutti gli elementi che influenzano le prestazioni degli utenti finali. I risultati ottenuti dimostrano l’efficacia delle soluzioni proposte, aprendo nuove strade per la realizzazione di reti cellulari più efficienti e performanti.The always-increasing number of mobile subscribers, the growing demand for mobile data, and the emergence of new applications require cellular systems to be constantly improved. The last generation of cellular networks, i.e., 5G, stands out for its high performance and extreme flexibility, making it possible to support multiple use cases with diverse and stringent service requirements. One of the main novelties is represented by the possibility to communicate at millimeter wave (mmWave) frequencies, providing access to an unprecedented amount of radio resources which can theoretically enable extremely high data rates. However, signals propagating at these frequencies experience harsh conditions, posing several challenges for the realization of efficient mmWave cellular systems. The grand objective of this thesis is to provide innovative solutions to overcome the limitations of mmWave communications and exploit the potential of this technology in the context of 5G and beyond cellular networks. In particular, we (i) present novel simulation tools, including channel, antenna, and beamforming models for the accurate characterization of next-generation cellular systems; (ii) identify the potential and challenges for the realization of wireless-backhauled mmWave deployments, and present a semi-centralized resource partitioning scheme for this type of networks; (iii) analyze the cross-layer challenges arising from the integration of Hybrid Beamforming (HBF) and Multi User MIMO (MU-MIMO) in mmWave cellular systems; (iv) introduce a novel framework to enable network slicing in mmWave Radio Access Networks (RANs); and (v) evaluate the feasibility of providing vehicular communication services by means of mmWave communications. We adopt a system-level approach that allow us to properly characterize the network behavior, considering the full protocol stack and all the elements that have an impact on the performance of the end-users. Our results demonstrate the effectiveness of the proposed solutions, breaking new ground towards more efficient and high-performance mmWave cellular systems