Low density spreading multiple access

The need for ubiquitous coverage and the increasing demand for high data rate services, keeps constant pressure on the cellular network infrastructure. There has been intense research to improve the system spectral efficiency and coverage, and a significant part of this effort focused on developing and optimizing the multiple access techniques. One such technique that has been recently proposed is the low density spreading (LDS), which manages the multiple access interference to offer efficient and low complexity multiuser detection. The LDS technique has shown a promising performance as a multiple access technique for cellular systems. This chapter will give an overview on the LDS multiple access technique. The motivations for the LDS design will be highlighted by comparing it to conventional spreading techniques, including brief history of the early work on LDS. Furthermore, a background on the design of LDS in multicarrier communications, such as signatures design, a belief propagation multiuser detection, etc., will be presented along with the challenges and opportunities associated with the multicarrier LDS multiple access

Random Codes and Graphs for Secure Communication

This dissertation considers two groups of problems related to secure communication. The first line of research is devoted to theoretical problems of copyright protection of digital content. Embedding identification data in the content is a well-developed technique of content protection known under the name of fingerprinting. Schemes that provide such protection are known as fingerprinting codes in the literature. We study limits of the number of users of a fingerprinting system as well as constructions of low-complexity fingerprinting codes that support a large number of users. The second problem that is addressed in the dissertation relates to connectivity analysis of ad hoc wireless networks. One of the basic requirements in such environments is to ensure that none of the nodes are completely isolated from the network. We address the problem of characterizing threshold parameters for node isolation that enable the system designer to choose the power needed for network operation based on the outage probability of links in the network. The methods of this research draw from coding theory, information theory and random graphs. An idea that permeates most results in this dissertation is the application of randomization both in the analysis of fingerprinting and node isolation. The main contributions of this dissertation belong in the area of fingerprinting and are described as follows. We derive new lower and upper bounds on the optimal trade-off between the number of users and the length of the fingerprints required to ensure reliability of the system, which we call fingerprinting capacity. Information-theoretic techniques employed in our proofs of bounds on capacity originate in coding theorems for channels with multiple inputs. Constructions of fingerprinting codes draw on methods of coding theory related to list decoding and code concatenation. We also analyze random graph models for ad hoc networks with link failures and secure sensor networks that employ randomized key distribution. We establish a precise zero-one law for node isolation in the model with link failures for nodes placed on the circle. We further generalize this result to obtain a one-law for secure sensor networks on some surfaces

Deep Learning, Shallow Dips: Transit light curves have never been so trendy

At the crossroad between photometry and time-domain astronomy, light curves are invaluable data objects to study distant events and sources of light even when they can not be spatially resolved. In particular, the field of exoplanet sciences has tremendously benefited from acquired stellar light curves to detect and characterise a majority of the outer worlds that we know today. Yet, their analysis is challenged by the astrophysical and instrumental noise often diluting the signals of interest. For instance, the detection of shallow dips caused by transiting exoplanets in stellar light curves typically require a precision of the order of 1 ppm to 100 ppm in units of stellar flux, and their very study directly depends upon our capacity to correct for instrumental and stellar trends. The increasing number of light curves acquired from space and ground-based telescopes—of the order of billions—opens up the possibility for global, efficient, automated processing algorithms to replace individual, parametric and hard-coded ones. Luckily, the field of deep learning is also progressing fast, revolutionising time series problems and applications. This reinforces the incentive to develop data-driven approaches hand-in-hand with existing scientific models and expertise. With the study of exoplanetary transits in focus, I developed automated approaches to learn and correct for the time-correlated noise in and across light curves. In particular, I present (i) a deep recurrent model trained via a forecasting objective to detrend individual transit light curves (e.g. from the Spitzer space telescope); (ii) the power of a Transformer-based model leveraging whole datasets of light curves (e.g. from large transit surveys) to learn the trend via a masked objective; (iii) a hybrid and flexible framework to combine neural networks with transit physics

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin