Fast advance in the design of 5G cellular networks has motivated a lot of research that addresses challenges given by the explosive growth of traffic burden, the rise of energy consumption constraints, the unprecedentedly high demand for broadband mobile connectivity and guaranteed quality-of-service for end-users. Therefore the appearance of new technologies, system designs and fast network solutions becomes vital to bear such high demand in network infrastructures.
In this context, the wireless relay scenario has emerged as a key enabler to deal with such challenges. Having clever and efficient schemes that allow traffic to follow alternative relayed paths rather than direct delivery from producer to consumer stands as a crucial need to be properly integrated on the 5G and beyond networks. Depending on the kind of relay, we envision different relay paradigms: users aiming to relief the traffic burden enable device-to-device relay systems; flexible relaying for dense wireless backhaul systems powered by directional transmissions needs smart relay to boost spatial reuse that minimizes the amount of time needed for traffic readiness; and the possibility of mounting relays on extremely-mobile devices such as drones turns the air space into an unexplored vast amount of possibilities to properly position aerial relays.
In this thesis, we present practical optimization tools that leverage the mentioned wireless relay paradigms. We derive optimization frameworks that boost important network metrics such as fair traffic delivery, backhaul traffic readiness or network coverage in current cellular networks. We carefully model network features such as traffic paths, consumed energy, user throughput, transmission directionality or link activation cost, among others. Hence, we approach realistic network infrastructures restricted by technical, physical, flow, or fairness constraints. As unavoidable complex mathematical constraints arise that often turn into an NP-Complete problem, we propose lightweight schemes that work in low-degree polynomial time that are able to provide efficient close-to-optimal solutions, as required in current networks operating at tiny time-scales.
The results reported in this thesis show that designing optimization tools that properly identify key opportunities for efficient relay such as best split traffic paths, best directional transmission scheduling or best aerial relay positioning provides very high gains in terms of throughput experience, fast readiness of traffic at the edge nodes or users coverage. Hence, solutions proposed in this thesis comply with implementation requirements as well as guaranteed performance service for desirable integration on current cellular networks.
About Edgar Arribas
Edgar obtained his BSc in Mathematics from the University of Valencia, in Burjassot, Spain. While studying his BSc, Edgar worked as a Research Collaborator in the Department of Applied Mathematics, working primarily with Multiscale Decomposition Methods and Linear and Non-linear methods for curve re-constructions. Additionally, he received a collaborator’s grant from the Ministry of Education which allowed him to work as Assistant Professor in the same department.
The thesis defense will be conducted in English. Given the coronavirus crisis, the thesis defense will be online
PhD Thesis Advisor: Dr. Vincenzo Mancuso, IMDEA Networks Institute, Madrid, Spain
University: University Carlos III of Madrid, Spain
Doctoral Program: Telematics Engineering
PhD Committee members: