Connectivity

As modern society becomes increasingly reliant on seamless, high-capacity, and low-latency communications, it is essential to develop systems that can handle the diverse demands of various applications—from streaming media to supporting critical infrastructure like healthcare and transportation. The Connectivity challenge addresses this by exploring how advanced techniques can jointly enhance the performance of wired and wireless networks, using them as complementary resources rather than separate, siloed technologies.

Connectivity has traditionally been designed with a focus on either wired systems, such as fibre optics, or wireless technologies, including radio frequency (RF) and emerging terahertz (THz) communications. However, the rapid expansion of mobile networks, Internet of Things (IoT) devices, and the increasing demand for data-intensive applications necessitate a more integrated approach. The goal of the C1 challenge is to demonstrate how these two domains can be seamlessly combined to create more efficient and adaptive networks that dynamically adjust based on user needs and environmental conditions. UCL is tasked with developing and demonstrating techniques that enable communication systems to transition between wired and wireless modes, selecting the optimal channel based on factors like bandwidth requirements, distance, and interference.

One key aspect of this challenge is to experiment with multi-band communication, where different portions of the spectrum (such as THz, RF, and optical) are used simultaneously to enhance data throughput and reliability. For instance, in urban environments, high-frequency wireless spectrum could be used for short-range, high-speed data transfers, while wired systems like fibre optics handle long-distance or high-bandwidth connections. In more remote or rural areas, where wired infrastructure is limited, wireless communication could dominate, with techniques developed to ensure reliable coverage and capacity.

Moreover, the Connectivity challenge will also focus on optimizing network efficiency in real-time. UCL researchers will explore how advanced algorithms, including machine learning, can be employed to predict and manage network traffic, ensuring that data flows smoothly even in congested areas or during peak usage times. The ability to dynamically allocate resources between wired and wireless channels will not only improve user experiences but also increase network resilience.

Through demonstrations of these advanced connectivity techniques, this challenge aims to provide a blueprint for future communication networks that can flexibly adapt to different environments and user requirements, ensuring optimal performance and paving the way for next-generation all-spectrum connectivity.