H2020Индивидуална стипендия2021–2024

MASCOT · An Information-Theoretic Perspective on Massive Asynchronous Connectivity

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2021-10-01 → 2024-09-30
Финансиране от ЕС: 263 732 €
Участници: 2
Схема: MSCA-IF

Линиите свързват координатора с партньорите.

Накратко на български

Безжичната комуникация между множество устройства, като сензорите в Интернет на вещите, се анализира от гледна точка на теорията на информацията. Това помага за създаването на по-надеждни и енергоефективни протоколи за предаване на данни при голям брой свързани устройства.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

An Information-Theoretic Perspective on Massive Asynchronous Connectivity

MSCOT addresses the challenges posed by massive connectivity in asynchronous communications from an information theory perspective. The primary objective is to develop efficient communication methods for scenarios where numerous devices need to communicate asynchronously over a shared medium, maintaining energy efficiency and low computational complexity. The significance of this research extends to various real-world applications. In a society increasingly reliant on interconnected devices and communication technologies, solving the massive connectivity problem is critical. From the Internet of Things (IoT) to 5G networks and beyond, MASCOT aims to design protocols specifically for these services and applications, enabling a revolution in wireless communication systems by making them more reliable, energy-efficient, and capable of meeting the diverse needs of our modern, interconnected world. This knowledge serves as a foundation for researchers and developers, driving the creation of communication schemes tailored to this emerging field. As MASCOT concludes, it has demonstrated theoretically that handling device collisions is essential to meet reliability and energy-efficiency constraints in IoT-like and machine-type communications. Using information-theoretic tools, MASCOT provides finite-blocklength theoretical bounds and approximations, as well as initial deep-learning-based algorithms focused on interference rejection among devices causing unintentional interference. MASCOT paved the way for fundamentally supported operations for services and applications involving battery-limited devices transmitting short packets sporadically through theoretical research and practical algorithms based on the latest deep learning architectures tailored to this problem.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

It is expected that in the coming decades the population living in urban areas will increase dramatically. Therefore, the sustainability of our planet depends critically on a smart and energy-efficient operation of cities. Wireless communication technologies arise as one of the main enablers to reach this goal. For example, services and applications such as intelligent transportation, industry automation, and mobile healthcare will require to accommodate a vast number of heterogeneous and battery-limited wireless devices connecting asynchronously and sporadically to the network. This is commonly known as the massive connectivity problem. Since traditional wireless communication technologies were not designed to support this kind of services and applications, there is a need for a profound theoretical study of this problem.The main objective of MASCOT is to characterize, from an information-theoretic perspective, the fundamental limits and tradeoffs of the asynchronous massive connectivity problem. To this end, I will derive in the outgoing phase at MIT nonasymptotic bounds and asymptotic expansions characterizing these limits. In the return phase at Universidad Carlos III de Madrid, I will then explore different strategies to efficiently and accurately compute the nonasymptotic bounds derived at MIT. During the course of the project, I will elaborate guidelines about how future wireless communication schemes must be designed, and I will adapt existing schemes according to these guidelines. The proposed training activities during the fellowship are fundamental for the correct achievements of MASCOT as well as to secure my future career goals. MASCOT guarantees a two-way transfer of knowledge since it combines my past expertise on elaborating and efficiently evaluating fundamental limits of low-latency wireless communications with the supervisors’ expertise on information theory applied to the massive connectivity problem and asynchronous communications.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSIDAD CARLOS III DE MADRID · Getafe (Madrid)КоординаторИспания
MASSACHUSETTS INSTITUTE OF TECHNOLOGY · CambridgeСъединени щати