Simple Statistical Analysis of the Impact of Some Nonidealities in Downstream VDSL with Linear Precoding

Abstract This paper considers a VDSL downstream system where crosstalk is compensated by linear precoding. Starting from a recently introduced mathematical model for FEXT channels, simple analytical methods are derived for evaluating the average bit rates achievable, taking into account three of the most important nonidealities. First, absolute and relative estimation errors in the crosstalk coefficients are discussed, and explicit formulas are obtained to express their impact. A simple approach is presented for computing the maximum line length where linear precoding overcomes the noncoordinate system. Then, the effect of out-of-domain crosstalk is analyzed. Finally, quantization errors in precoding coefficients are considered. We show that by the assumption of a midtread quantization law with different thresholds, a relatively small number of quantization bits is sufficient, thus reducing the implementation complexity. The presented formulas allow to quantify the impact of practical impairments and give a useful tool to design engineers and service providers to have a first estimation of the performance achievable in a specified scenario

Consciousness, cognition, and the hierarchy of context: extending the global neuronal workspace model

We adapt an information theory analysis of interacting cognitive biological and social modules to the problem of the global neuronal workspace, the new standard neuroscience paradigm for consciousness. Tunable punctuation emerges in a natural way, suggesting the possibility of fitting appropriate phase transition power law, and away from transition, generalized Onsager relation expressions, to observational data on conscious reaction. The development can be extended in a straightforward manner to include psychosocial stress, culture, or other cognitive modules which constitute a structured, embedding hierarchy of contextual constraints acting at a slower rate than neuronal function itself. This produces a 'biopsychosociocultural' model of individual consciousness that, while otherwise quite close to the standard treatment, meets compelling philosophical and other objections to brain-only descriptions

Physical Layer Techniques for High Frequency Wireline Broadband Systems

This thesis collects contributions to wireline and wireless communication systems with an emphasis on multiuser and multicarrier physical layer technology. To deliver increased capacity, modern wireline access systems such as G.fast extend the signal bandwidth up from tens to hundreds of MHz. This ambitious development revealed a number of unforeseen hurdles such as the impact of impedance changes in various forms. Impedance changes have a strong effect on the performance of multi-user crosstalk mitigation techniques such as vectoring. The first part of the thesis presents papers covering the identification of one of these problems, a model describing why it occurs and a method to mitigate its effects, improving line stability for G.fast systems.A second part of the thesis deals with the effects of temperature changes on wireline channels. When a vectored (MIMO) wireline system is initialized, channel estimates need to be obtained. This thesis presents contributions on the feasibility of re-using channel coefficients to speed up the vectoring startup procedures, even after the correct coefficients have changed, e.g., due to temperature changes. We also present extensive measurement results showing the effects of temperature changes on copper channels using a temperature chamber and British cables. The last part of the thesis presents three papers on the convergence of physical layer technologies, more specifically the deployment of OFDM-based radio systems using twisted pairs in different ways. In one proposed scenario, the idea of using the access copper lines to deploy small cells inside users' homes is explored. The feasibility of the concept, the design of radio-heads and a practical scheme for crosstalk mitigation are presented in three contributions

A Data Compression Strategy for the Efficient Uncertainty Quantification of Time-Domain Circuit Responses

This paper presents an innovative modeling strategy for the construction of efficient and compact surrogate models for the uncertainty quantification of time-domain responses of digital links. The proposed approach relies on a two-step methodology. First, the initial dataset of available training responses is compressed via principal component analysis (PCA). Then, the compressed dataset is used to train compact surrogate models for the reduced PCA variables using advanced techniques for uncertainty quantification and parametric macromodeling. Specifically, in this work sparse polynomial chaos expansion and least-square support-vector machine regression are used, although the proposed methodology is general and applicable to any surrogate modeling strategy. The preliminary compression allows limiting the number and complexity of the surrogate models, thus leading to a substantial improvement in the efficiency. The feasibility and performance of the proposed approach are investigated by means of two digital link designs with 54 and 115 uncertain parameters, respectively

Synesthesia: Detecting Screen Content via Remote Acoustic Side Channels

We show that subtle acoustic noises emanating from within computer screens can be used to detect the content displayed on the screens. This sound can be picked up by ordinary microphones built into webcams or screens, and is inadvertently transmitted to other parties, e.g., during a videoconference call or archived recordings. It can also be recorded by a smartphone or "smart speaker" placed on a desk next to the screen, or from as far as 10 meters away using a parabolic microphone. Empirically demonstrating various attack scenarios, we show how this channel can be used for real-time detection of on-screen text, or users' input into on-screen virtual keyboards. We also demonstrate how an attacker can analyze the audio received during video call (e.g., on Google Hangout) to infer whether the other side is browsing the web in lieu of watching the video call, and which web site is displayed on their screen

Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

The applications of satellites to communications, navigation and surveillance for aircraft operating over the contiguous United States. Volume 1 - Technical report

Satellite applications to aircraft communications, navigation, and surveillance over US including synthesized satellite network and aircraft equipment for air traffic contro