Improved Revenue and Radio Resource Usage through Inter-Operator Joint Radio Resource Management

— 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. Keywords-Heterogeneous wireless networks; fuzzy neural; B3G systems; multi-operator; reinforcement learning.

• Type: Conference
• Year: 2007
• Where: ICC
• Authors: Lorenza Giupponi, Ramón Agustí, Jordi Pérez-Romero, Oriol Sallent
• Keywords: Communications, ICC 2007, Multi-operator Cellular Scenarios, Radio Resources, Reinforcement Learning