Efficient Resource Allocation in Software Defined Wireless Networks

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Future generations of cellular networks will change significantly in order to cope with the increasing number of network users as well as their request for high data rate services with high quality of service including low delay requirements. Additionally, the energy consumptions of cellular networks is about 0.5% of the total energy consumption world wide. Environment and economics require to increase the energy efficiency and keep or lower the level of energy consumption while increase the data rate by a factor of at least 1000. In the project, we develop a new radio access network architecture which is flexible and traffic and density aware. The architecture reflects well the recent developments in terms of massive MIMO base stations, non-orthogonal multiple access (NOMA) and exploits the features of software defined radio and networking. Methodologically, the project formulates the corresponding radio resource management tasks as solid programming problems and solves them either centralized or in a distributed implementation. Coexistence of several network technologies as mmWave, WiFi and cellular allows to supply users with multiple seamless connectivity if the corresponding resource allocation supports it. The project also considers robust resource allocation for imperfect channel and traffic state information. The multi-objective programming problems are solved by using the latest optimization tools including fractional programming, convex sequential approximation, semidefinite relaxation. All solutions are analyzed in terms of performance, complexity and convergence. The developed algorithms will build a basis for software implementation in 5G and beyond networks.