Tutorial details
Electromagnetic signal and information theory: Beyond diagonal reconfigurable intelligent surfaces and holographic surfaces
Bruno Clerckx (Imperial College London, United Kingdom), Marco Di Renzo (L2S-CentraleSupelec, France), Hongyu Li (Imperial College London, United Kingdom), Matteo Nerini (Imperial College London, United Kingdom).
Electromagnetic signal and information theory (ESIT) is an emerging interdisciplinary discipline that is concerned with the mathematical treatment and information processing of electromagnetic fields governing the transmission and processing of messages through communication systems. In this tutorial we discuss two new areas in the broad field of ESIT, namely beyond diagonal reconfigurable intelligent surfaces (BD-RIS) and holographic surfaces. This first part of the tutorial introduces the audience to BD-RIS, viewed as the next generation of RIS characterized by scattering matrix not constrained to be diagonal, and shows the benefits of BD RIS over conventional diagonal RIS. The second part of the tutorial discusses holographic surface being an electrically large antenna that is made of a virtually infinite number of radiating elements coupled with electronic circuits and a limited number of radio frequency chains.
Large-scale distributed computing systems, such as MapReduce, Spark, or distributed deep networks, are critical for parallelizing the execution of computational tasks. Nevertheless, a struggle between computation and communication complexity lies at the heart of distributed computing. There has been recently a substantial effort to address this problem for a class of functions, such as distributed matrix multiplication, distributed gradient coding, linearly separable functions, and beyond. In this tutorial, we will discuss the key methods devised to understand the fundamental tradeoff between communication and computation complexities. In the first part of the tutorial, we will unveil information and graph-theoretic approaches to resolve some well-known distributed coding and communication problems, allowing for lowered communication complexity and even for a) correlated data, b) a broad class of functions, and c) well-known topologies. In the second part of the tutorial, we will detail coding theoretic techniques, allowing for the evaluation of the joint behavior of the communication and computation costs, storage, and recovery thresholds, motivated by the same challenge in the complexities.
THz wireless sensing and communication
Yasaman Ghasempour (Princeton University, USA), Vitaly Petrov (KTH Royal Institute of Technology, Sweden)
The use of frequencies above 100 GHz has recently garnered significant interest due to abundant bandwidth for Tb/sec communication and sub-mm wavelengths for super-resolution sensing and imaging. However, effective communication and sensing in this spectral range demand a fundamental rethinking of wireless network architecture, including innovative beamforming, near-field channel models, resource allocation, and more. This tutorial explores the distinct opportunities and challenges of communication and sensing above 100 GHz. It delves into emerging and scalable beamforming architectures to counteract the significantly higher propagation loss in this regime. Additionally, it provides an overview of recent near-field wavefronts (e.g., Bessel beams and Airy beams) with unique characteristics to alleviate link blockage, the longstanding challenge in mm-Wave and sub-THz regimes, while offering new avenues for enhanced sensing, interference mitigation, and security. The tutorial concludes by presenting the signal processing research challenges, open questions, and promising application domains for future THz systems.
An information-theoretic view of integrated sensing and communication (ISAC)
Michèle Wigger (Telecom Paris, France)
In a first part of this tutorial we provide an introduction to Shannon’s famous channel coding theorem, as well as to the theory of optimal sensing systems (detection errors, distortion, etc.). We then show modern applications of these results for integrated sensing and communication (ISAC) systems. ISAC systems are expected to be important building blocks of future 6G standards as they merge radar and communication into single systems with reduced hardware costs and bandwidth requirements. Specifically, we shall present the optimal capacity-distortion and capacity-detection error exponent tradeoffs for single-transmitter and single-receiver ISAC systems. The last part of the tutorial will then cover extensions to network scenarios with multiple transmitters or multiple receivers. Specifically, for multiple transmitters we will present information-theoretic coding schemes that integrate collaborative sensing and collaborative communication into a single code construction and we show that these constructions achieve improved performances.
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