4th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

Aggregated interference control for cognitive radio networks based on multi-agent learning

  • @INPROCEEDINGS{10.1109/CROWNCOM.2009.5188951,
        author={Ana  Galindo-Serrano and Lorenza Giupponi},
        title={Aggregated interference control for cognitive radio networks based on multi-agent learning},
        proceedings={4th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2009},
        month={8},
        keywords={Cognitive radio aggregated interference multiagent system decentralized Q-learning.},
        doi={10.1109/CROWNCOM.2009.5188951}
    }
    
  • Ana Galindo-Serrano
    Lorenza Giupponi
    Year: 2009
    Aggregated interference control for cognitive radio networks based on multi-agent learning
    CROWNCOM
    IEEE
    DOI: 10.1109/CROWNCOM.2009.5188951
Ana Galindo-Serrano1,*, Lorenza Giupponi1,*
  • 1: Centre Tecnol. de Telecomunicacions de Catalunya (CTTC), Parc Mediterrani de la Tecnol., Barcelona, Spain
*Contact email: ana.maria.galindo@cttc.es, lorenza.giupponi@cttc.es

Abstract

This paper deals with the problem of aggregated interference generated by multiple cognitive radios (CR) at the receivers of primary (licensed) users. In particular, we consider a secondary CR system based on the IEEE 802.22 standard for wireless regional area networks (WRAN), and we model it as a multi-agent system where the multiple agents are the different secondary base stations in charge of controlling the different secondary cells. We propose a solution for the aggregated interference problem based on a form of real-time multi-agent reinforcement learning known as decentralized Q-learning, so that the multi-agent system is designed to learn an optimal policy by directly interacting with the surrounding environment in a distributed fashion. Simulation results reveal that the proposed approach is able to fulfil the primary users interference constraints, without introducing signalling overhead in the system.