Analysis of MAC-level throughput in LTE systems with link rate adaptation and HARQ protocols

LTE is rapidly gaining momentum for building future 4G cellular systems, and real operational networks are under deployment worldwide. To achieve high throughput performance, in addition to an advanced physical layer design LTE exploits a combination of sophisticated mechanisms at the radio resource management layer. Clearly, this makes difficult to develop analytical tools to accurately assess and optimise the user perceived throughput under realistic channel assumptions. Thus, most existing studies focus only on link-layer throughput or consider individual mechanisms in isolation. The main contribution of this paper is a unified modelling framework of the MAC-level downlink throughput of a sigle LTE cell, which caters for wideband CQI feedback schemes, AMC and HARQ protocols as defined in the LTE standard. We have validated the accuracy of the proposed model through detailed LTE simulations carried out with the ns-3 simulator extended with the LENA module for LTE

On the optimal user grouping in NOMA system technology

This paper provides a state-of-art analysis of the most relevant studies on optimal user-aggregation strategies for non-orthogonal multiple access (NOMA) technology. The main ideas behind are i) to highlight how, in addition to the adoption of an optimal power allocation scheme, an optimal user-aggregation strategy represents an important key factor for improving NOMA system performance, and ii) to provide an exhaustive survey of the most relevant studies which can serve as useful starting point for the definition of new channel state-aware user-aggregation strategies for NOMA systems which, at the time of writing, represents a research field that still remains to be investigated more in depth. A detailed and complete analysis, which permits to point out the need to guarantee a certain relationship between users’ channel gain, is provided for each cited work

Opportunistic traffic Offloadings Mechanisms for Mobile/4G Networks

In the last few years, it has been observed a drastic surge of data traffic demand from mobile personal devices (smartphones and tablets) over cellular networks [1]. Even though a significant improvement in cellular bandwidth provisioning is expected with LTE-Advanced systems, the overall situation is not expected to change significantly. In fact, the diffusion of M2M and IoT devices is expected to increase at an exponential pace (the share of M2M devices is predicted to increase 5x by 2018 [1]) while the capacity of the cellular network is expected to increase linearly [1]. In order to meet such a high demand and to increase the capacity of the channel, multiple offloading techniques are currently under investigation, from modifications inside the cellular network architecture, to integration of multiple wireless broadband infrastructures, to exploiting direct communications between mobile devices. All these approaches can be diveded in two main classes: - To develop more sophisticated physical layer technologies (e.g. massive MIMO, higher-order modulation schemes, cooperative multi-period transmission/reception) - To offload part of the traffic from the cellular to another complementary network. From this perspective the thesis contributes on both areas. On the one hand we discuss our investigations about the performance of the LTE channel capacity through the development of a unified modelling framework of the MAC-level downlink throughput of a sigle LTE cell, which caters for wideband CQI feedback schemes, AMC and HARQ protocols as defined in the LTE standard. Furthemore we also propose a solution, based on reinforcement learning, to improve the LTE Adaptive Modulation and coding Scheme (MCS). On the other hand we have proposed and validated offloading mechanisms which are minimally invasive for users' mobile devices, as they use only minimally their resources. Furthemore, as opposed to most of the literature, we consider the case where requests for content are non-synchronised, i.e. users request content at random points in time

Promoting STEM via UMI: an Ecological Framing of CoPs in Networking and Networked Robotics

Ubiquitous Computing, Mobile Computing and Internet of Things (UMI) technologies, are widely diffused in the everyday life. In addition to their primary usage (e.g., supporting the implementation of the future 5G network),these technologies can be used in the context of Science Education.According to this perspective, the innovative psycho-pedagogical approach here presented has been ad-hoc developed for the Horizon 2020 Project “Exploiting Ubiquitous Computing, Mobile Computing and the Internet of Things to promote Science Education” (Umi-Sci-Ed). The aim of the project is to enhance knowledge and skills of Science, Technology, Engineering and Mathematics (STEM) and to promote positive attitudes towards these disciplines. In order to reach this goal, the UMI technologies, framed in the Community of Practices (CoPs) paradigm, will be introduced in the learning process of secondary schools’ students (i.e., 9thand 10thgrade). Specifically, the students will attend to innovative learning activities, such as hands-on activities, concerning with Networking and networked Robotics. In the present contribution, the theoretical framework that constitutes the rationale for the Umi-Sci-Ed projectwill be described. In particular, the “bottom-up” socio-constructionist perspective will be presented, aswell as the main technological tools (e.g., UDOO) that would be used to implement an integrated STEM learning environment. The expected results of the project will be discussed

Hybrid 6-DoFs magnetic localization for robotic capsule endoscopes compatible with high-grade magnetic field navigation

This paper proposes a hybrid 6-DoFs localization system for endoscopic magnetic capsules, compatible with external high-grade permanent magnetic locomotion. The proposed localization system, which is able to provide an accurate estimation of the endoscopic capsule pose, finds application in the robotic endoscopy field to provide efficient closed-loop navigation of a magnetically-driven tethered capsule. It takes advantage of two optimization steps based on a triangulation approach, i.e. (1) mathematical approximations of the magnetic field, and (2) minimization of the magnetic field mean square deviation. The proposed localization system was tested in two different in-vitro scenarios for mimicking the clinical cases that a magnetic capsule would encounter during tele-operated magnetic navigation. The development phase was preceded by an in-depth work-space analysis to lay the groundwork for the localization design and implementation. Results of the hybrid 6-DoFs localization system show a significant accuracy in accordance with the state-of-the-art, i.e. < 5 mm and < 5° in position and orientation, but introducing benefits in expanding the work-space by increasing the number of electromagnets on the operating table as an independent solution with respect to the external magnetic locomotion source

Digital Twin for 6G: Taxonomy, Research Challenges, and the Road Ahead

The concept of digital twin (DT) is constantly revealing as a key enabling technology for the deployment of mobile communication services envisaged for the sixth-generation (6G) Internet-of-Things (IoT). This paper aims at providing a comprehensive review of the current state-of-the-art DT-enabled 6G oriented network services. The main characteristics of this new key enabling technology and its critical aspects are highlighted. An overview of the 6G network requirements for the deployment of its innovative envisioned services is firstly provided, emphasizing how the DT concept represents a complementary key enabling technology for them. This is followed by a brief introduction of the DT technology. Subsequently, a comprehensive classification and analysis of the research advancements on DT-enabled 6G services currently available in literature is provided. This paper is concluded by highlighting the most representative challenges and future directions necessary for the deployment of this promising and innovative technology

Jointly power allocation and phase shift optimization for RIS empowered downlink cellular networks

Reconfigurable Intelligent Surfaces (RIS) have been highlighted by the research community as a key enabling technology for the enhancement of next-generation wireless network performance, including energy efficiency, spectral efficiency, and network throughput. This paper investigates how RIS-assisted communication can effectively maximize the downlink throughput of a cellular network. Specifically, the paper considers a communication scenario where a single base station serves multiple ground users with the aid of an RIS placed on a building facade. For such a communication scenario, we considered an optimization problem aimed at maximizing the overall downlink throughput by jointly optimizing power allocation at the base station and phase shift of RIS reflecting elements, subject to power consumption and quality-of-service constraints. To address its non-convex nature, the original optimization problem has been divided into two subproblems. The first one, for power control with fixed phase shift values, is a convex problem that can be easily solved. Subsequently, a phase shift searching procedure to solve the non-convex problem of RIS phase shift optimization has been adopted. The results from numerical simulations show that the proposed method outperforms other conventional methods proposed in the literature. In addition, computational complexity analysis has been conducted to prove the low complexity of the proposed method

Molecular characterization of an aggregation-prone variant of alpha-synuclein used to model synucleinopathies

The misfolding and aggregation of alpha-synuclein (aSyn) are thought to be central events in synucleinopathies. The physiological function of aSyn has been related to vesicle binding and trafficking, but the precise molecular mechanisms leading to aSyn pathogenicity are still obscure. In cell models, aSyn does not readily aggregate, even upon overexpression. Therefore, cellular models that enable the study of aSyn aggregation are essential tools for our understanding of the molecular mechanisms that govern such processes. Here, we investigated the structural features of SynT, an artificial variant of aSyn that has been widely used as a model of aggregation in mammalian cell systems, since it is more prone to aggregation than aSyn. Using Nuclear Magnetic Resonance (NMR) spectroscopy we performed a detailed structural characterization of SynT through a systematic comparison with normal, unmodified aSyn. Interestingly, we found that the conformations adopted by SynT resemble those described for the unmodified protein, demonstrating the usefulness of SynT as a model for aSyn aggregation. However, subtle differences were observed at the N-terminal region involving transient intra and/or intermolecular interactions that are known to regulate aSyn aggregation. Importantly, our results indicate that disturbances in the N-terminal region of SynT, and the consequent decrease in membrane binding of the modified protein, might contribute to the observed aggregation behavior of aSyn, and validate the use of SynT, one of the few models of aSyn aggregation in cultured cells

Automatic annotation of experimentally derived, evolutionarily conserved post-translational modifications onto multiple genomes

New generation sequencing technologies have resulted in significant increases in the number of complete genomes. Functional characterization of these genomes, such as by high-throughput proteomics, is an important but challenging task due to the difficulty of scaling up existing experimental techniques. By use of comparative genomics techniques, experimental results can be transferred from one genome to another, while at the same time minimizing errors by requiring discovery in multiple genomes. In this study, protein phosphorylation, an essential component of many cellular processes, is studied using data from large-scale proteomics analyses of the phosphoproteome. Phosphorylation sites from Homo sapiens, Mus musculus and Drosophila melanogaster phosphopeptide data sets were mapped onto conserved domains in NCBI’s manually curated portion of Conserved Domain Database (CDD). In this subset, 25 phosphorylation sites are found to be evolutionarily conserved between the three species studied. Transfer of phosphorylation annotation of these conserved sites onto sequences sharing the same conserved domains yield 3253 phosphosite annotations for proteins from coelomata, the taxonomic division that spans H. sapiens, M. musculus and D. melanogaster. The method scales automatically, so as the amount of experimental phosphoproteomics data increases, more conserved phosphorylation sites may be revealed