This paper proposes a two-layer joint radio resource management (JRRM) framework to improve the efficiency in multi-radio and multi-operator cellular scenarios. On the one hand, the intra-operator JRRM relies on fuzzy-neural mechanisms with economic-driven reinforcement learning techniques to exploit radio resources within a single operator domain. On the other hand, inter-operator JRRM allows subscribers to get service through other operators in case the home operator network is blocked. Simulation results in a number of different scenarios show that inter-operator agreements established in a cooperative scenario bring benefits to both operators and users, enabling an efficient load management and increasing the operators' revenue.
['Lorenza Giupponi', 'Ramón Agustí', 'Jordi Pérez-Romero', 'O. Salient']
Improved Revenue and Radio Resource Usage through Inter-Operator Joint Radio Resource Management