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.