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[ELEN] 2026-10-15 (15:00) : Seminar on Wireless Sensing and Communications
At Nyquist
Section 1:Optimal Sparse Array Design for Sensing and Communications (15:00)
Speaker :
Marius Pesavento (TU Darmstadt)
Abstract : Sparse linear arrays obtained by thinning large uniform linear arrays are widely used in wireless communications and radar sensing because they offer large effective apertures and high angular resolution with fewer sensors. However, thinning also introduces array ambiguities that can induce rank deficiencies in the associated channel or sensing matrix, thereby limiting spatial multiplexing gains and preventing unique multisource parameter estimation in certain scenarios. Conventional sparse-array designs for sensing are often based on local criteria, such as Fisher information matrix (FIM) analysis, which do not fully account for dependencies among sources. More fundamentally, the underlying problem is that of determining the spark of a generalized Vandermonde matrix – an important open question with connections to algebraic coding theory, polynomial approximation, and control theory. In this talk, we present a novel scalable framework for the design and analysis of sparse (thinned) uniform arrays. Specifically, we reformulate the problem as one of designing structured matrices of maximum rank, which in turn yields simple principles for constructing optimal sparse arrays. The resulting approach combines symbolic computation with structured rank optimization. It is simple, scalable, and well suited to the design of very large sparse arrays.
Section 2:Near-field Radio Localization and Mapping with Intelligent Surfaces (16:00)
Speaker :
Anna Guerra (Università di Bologna)
Abstract : The next generation of cellular networks promises to revolutionize wireless communication by creating smart radio environments (SREs) through the use of reconfigurable intelligent surfaces (RISs). These RISs offer significant benefits, including the ability to optimize the radio channel for specific applications, thereby enhancing overall system performance. For instance, RIS elements can be reconfigured to achieve precise localization and sensing, while simultaneously improving communications in cellular networks. Additionally, with the adoption of large aperture arrays and high frequencies, the traditional plane wave approximation, which is valid in the far field, becomes inadequate. In these scenarios, cellular users are likely to be positioned in the near field relative to base stations and RISs. The resulting wavefront curvature allows for the extraction of both distance and angle-of-arrival information, enabling more accurate source localization with fewer deployed devices (single-anchor localization). This webinar will present recent advancements in near-field localization and sensing for next-generation communication systems. It will begin by exploring the localization fundamental localization limits in RIS-aided systems, followed by a review of algorithms designed for imaging and tracking mobile users. The webinar will also show how optimizing the phase profile of RISs can significantly impact localization performance.
[INMA] 2026-10-13 (14:00) : Using randomness to reveal (part of) the mathematics of (deep) learning
At Euler building (room A.002)
Speaker :
Laurent Jacques (UCLouvain)
Abstract : In this talk, we will see how several phenomena in the study of machine and deep learning models, such as their ability to linearly separate two classes of samples or their stability with respect to input variations, can be partly explained by random, untrained parameters. We will draw connections with one-bit compressive sensing and the measure concentration phenomenon.
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