Application of Complex Systems Science to Wireless Systems
Dr Harun Siljak leads the project COCODIMM, which aims at observing Distributed Massive MIMO as a complex system with rich spatio-temporal dynamics. Complex systems science, control and nonlinear dynamics meet reversible computation and hardware design in the process of understanding the physics and the engineering of massive MIMO.
Dr Alessandro Chiumento works at the interface between traditional wireless communication, complex Systems and machine learning. The main objectives of his project – IoCT – are to determine scalable, hierarchical multi agent solutions which include emergent properties of wireless networks in the feedback loop between a highly abstracted centralised monitor and local but data intensive controllers.
A number of trends in 5G and IoT systems – denser networks, multi-ownership, resource sharing, NFV, SDN, to name just a few – are changing the organizational structure of telecom network from a rigid and static to a dynamic system. Merim Dzaferagic‘s PhD work relies on Information and Complexity Theory, Network Science and Agent-Based Modelling, to better understand how distributed intelligence emerges and affects the network operation.
See also the TRICKLE team website.
Future Wireless Systems
Recently machine-to-machine communications has emerged as an enabling technology for the practical realization of Internet-of-Things (IoT). Such networks face several challenges like connectivity among large number of machines with diverse functionalities, wide coverage area, resource and QoS constraints. Dr Indrakshi Dey leads the project FD-M2Mcomm, a cross-layer full-duplex design will be proposed to address the above-mentioned challenges of machine-to-machine communication systems.
5G is expected to cater to numerous different vertical industries and use-cases which present a diverse range of requirements to the network. This necessitates a flexible network that is characterised by its versatility and ability to adapt to different services. As part of his PhD, Conor Sexton focuses on ways to introduce this flexibility into future networks, chiefly by using the concept of resource slicing.
The architecture of device caching exploits the large storage available in modern smartphones to cache multimedia files that might be highly demanded by the devices. The scope of Ramy Amer‘s PhD work is to investigate and maximize the cache offloading gain via coordinated multi-point (CoMP) transmission for a clustered Device-to-Device (D2D) caching network.
The wide spectrum available in millimetre-wave (mmWave) frequencies is the key to enhance the wireless communication data rates for 5G mobile networks. In his PhD, Fadhil Firyaguna is studying the characterization of optimal network deployments of mmWave networks considering the human body blockage effects on such networks.
Massive MIMO systems heavily suffer from synchronization errors, such as carrier frequency offset (CFO). Due to the large number of base station antennas, frequency synchronization can impose an enormous amount of computational complexity to the system. To deal with this issue, in her PhD Parna Sabeti has proposed novel low-complexity CFO estimation and compensation techniques for massive MIMO systems.
Next generation wireless communication systems are expected to support a 1000x increase in capacity, and meeting this will require network densification using small cells base stations. The cost-effective availability for backhaul is currently the main limitation holding back dense network deployments, particularly for mmWave coverage. In his PhD project, Andrea Bonfante studies the flexible and cost-efficient solution is represented by self-backhauling, defined as the capability for a BS to enable in the same spectrum resources both the access and the backhaul transmissions.