Dr. Arman Farhang

More and more devices are connected wirelessly. This trend continues to rise at a higher pace with the emergence of new generation of applications and services in future wireless networks. Due to the seamless connectivity and high data rate requirements in a variety of services, very high frequencies are deployed for communication. However, there are lots of challenges when very high frequency bands, e.g., millimetre wave (mmWave) bands, are deployed for communication, such as severe signal blockage. This leads to unreliable communication. Therefore, this project explores an emerging communication paradigm where the propagation of the electromagnetic waves is manipulated in a controllable fashion. This is achieved by using Reconfigurable Intelligent Surfaces (RIS) to solve the signal blockage and hence, improve the overall user experience by improving the reliability of the wireless connections. This contributes towards increased connectivity and reliability of the mmWave wireless networks of the future. REFLECT-MMWAVE project brings together multidisciplinary experts from radio frequency and analogue circuits and antenna design, signal processing, machine learning and communication networks.

The emergence of a diverse set of services and applications in networks of the future set out many challenging requirements, including low latency and high reliability of the wireless links. These challenges are more pronounced in mission-critical applications such as autonomous vehicles that require safe and rapid reactions and cannot tolerate the wireless link becoming unreliable. This loss of reliability can be due to the fast variations of the wireless channel with time. To tackle such challenges, this project will develop flexible, efficient, and robust data transmission and detection techniques with reduced signaling overhead bolstered through utilization of advanced multiple antenna technologies. Dealing with time-varying channels has a long history; however, conventional solutions require fast tracking of such channels or large signaling overheads leading to huge latency issues. Hence, this project focuses on the design and development of a new generation of air interface technologies that simultaneously utilize physical resources in multiple dimensions such as time, frequency, and space with a disruptive approach to achieve the maximum diversity gains inherent to wireless channels. The research will thus enable mission-critical applications with high reliability and low latency requirements and enhance safety along with connectivity.

Network slicing is one of the overarching features towards 5G-and-beyond to achieve the true potential of the network resource utilization and efficiency. By establishing the framework of network slicing through air-interface heterogeneous signal orchestration and efficient resource allocation, the proposed work in this project underpins efficient end-to-end network slicing. We consider network slicing as a solution to design, customize, and optimize different subnetworks (or slices) on a common physical network infrastructure. This project develops a novel algorithmic framework leading to improved efficiency in terms of spectrum, cost, and complexity. This framework aims at supporting a complete end-to-end network slicing for the diverse ecosystems emerging in future networks. In particular, the approach is based on advanced configurable time-frequency grid design through adaptively changing the subcarrier-spacing/symbol-duration to accommodate a wide set of use-cases, i.e. those from delay-tolerant to latency-critical systems such as massive machine type communications (mMTC) and ultra-reliable low latency communications (URLLC) applications, respectively.

6G envisions unprecedented requirements for immersive, hyper-reliable, ubiquitous and low-latency connectivity together with dynamic sensing and AI-native capabilities across diverse and complex propagation environments. However, traditional waveforms and signal processing methods struggle to meet these requirements, especially under high mobility, interference, scalability and energy efficiency constraints. Furthermore, exploitation of MIMO (multiple input, multiple output) antenna technologies such as extremely large antenna arrays causes energy consumption bottlenecks as the number of RF chains scales-up. Hence, significant new innovations in signal and waveform design/processing, will be needed to meet the ambitious sustainability, performance, and standardization and backward compatibility goals of 6G. To address these challenges, a new pan-European consortium has been established to put forth this proposal, bringing together leading experts from a range of complementary disciplines, including RF and analogue circuit design, antenna systems, multidimensional signal processing, machine learning, and communication networks."" MULTIPLY-6G aims to develop advanced multidimensional waveform technologies, low-complexity extreme large arrays, and advanced spectrum sharing techniques, in an Open RAN (O-RAN) framework. This approach could unlock unprecedented levels of area spectral efficiency, energy efficiency and communication link reliability for wireless networks beyond 5G. It explores a revolutionary approach towards multi-dimensional waveform processing/design, by channel representation in delay, Doppler, and wavenumber domains, ensuring compatibility with standard wireless protocols.