Future wireless communication networks are expected to address unprecedented challenges to cope with a high degree of heterogeneity in terms of devices, deployment types, environments, carrier frequency, etc. Moreover, they are expected to provide orders of magnitude improvement to such heterogeneous networks in key technical requirements including throughput, number of connected devices, latency and reliability. With such diverse services and diverging requirements, it is cumbersome to design a unified all-in-one radio system to meet the technical needs for all types of services. In addition, designing separate systems that run on separate infrastructures make the operation and management of the system highly complex, expensive and spirally inefficient. The scope of the project is to establish a radio ecosystem on a common infrastructure that efficiently accommodates communication services for all vertical sections from manufacturing, entertainment, public safety, public transport, healthcare, financial services, automotive and energy utilities. This can be enabled by an algorithmic framework orchestrating all radio slices that are individually customised and optimally designed.
Network slicing is an overarching feature towards 5G-and-beyond to support all scenarios efficiently. Core network slicing has attracted much attention through network functions virtualisation. However, from the radio level, an algorithmic framework for spectrum- and cost-efficient air-interface to achieve the true potential of end-to-end network slicing for the future diverse radio systems is still an open problem yet to be solved.
To guarantee the required performance for each individual user case efficiently, the physical layer (PHY) configurations should be delicately optimised and medium access control layer (MAC) radio resource should be allocated on-demand. For instance, subcarrier spacing is one of the paramount importance parameters for modern multicarrier communication systems (e.g., LTE, WiFi, etc.), the service for future massive machine type communications (mMTC) might require smaller subcarrier spacing (thus larger symbol duration) to support massive delay-tolerant devices. While vehicle to vehicle (V2V) communications, on the other hand, have more stringent latency requirements, thus, symbol duration should be significantly reduced compared to mMTC. However, cohabitation of the individually optimised services in one system may bring several technical challenges from both PHY and MAC. It will destroy the system orthogonality and PHY algorithm framework that the state-of-the-art telecommunication systems built on. From the resource allocation perspective, one of the challenges is that not only the multi-slice system forests a complex multiple layers resource structure, but also technical requirement of each slice can be significantly different. Thus, a cross-layer and cross-slice optimisation is envisioned to maximise the overall air-inference performance.
The aim of REORDER is to address the abovementioned challenges, by establishing the framework of air-interface heterogeneous signal orchestration and efficient resource allocation. The proposed work fills in the last piece of the puzzle for realistic and efficient end-to-end network slicing. From this sense, REORDER will "reorder" the radio resource allocation caused by slice configuration disorders.
The project will be undertaken in the Communication, Sensing and Imaging research group (CSI) in the University of Glasgow, by the PI, a PDRA and a PhD student based at the University of Glasgow. Our industrial partners include NEC Telecom MODUS (UK), Mathworks Research Centre Glasgow, and VIAVI Solutions (UK). The radical approaches proposed in this project will be verified though both state-of-the-art standard compatible system-level simulation and software defined radio (SDR) based over-the-air experimentations.
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