5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

Autonomous dynamic spectrum management for coexistence of multiple cognitive tactical radio networks

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  • @INPROCEEDINGS{10.4108/ICST.CROWNCOM2010.9228,
        author={Vincent Le Nir and Bart Scheers},
        title={Autonomous dynamic spectrum management for coexistence of multiple cognitive tactical radio networks},
        proceedings={5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2010},
        month={9},
        keywords={Cognitive tactical radio networks dynamic spectrum management iterative water-filling},
        doi={10.4108/ICST.CROWNCOM2010.9228}
    }
    
  • Vincent Le Nir
    Bart Scheers
    Year: 2010
    Autonomous dynamic spectrum management for coexistence of multiple cognitive tactical radio networks
    CROWNCOM
    IEEE
    DOI: 10.4108/ICST.CROWNCOM2010.9228
Vincent Le Nir1,*, Bart Scheers1,*
  • 1: Royal Military Academy, Dept. Communication, Information Systems & Sensors (CISS), 30, Avenue de la Renaissance B-1000 Brussels BELGIUM.
*Contact email: vincent.lenir@rma.ac.be, bart.scheers@rma.ac.be

Abstract

In this paper, dynamic spectrum management is studied for multiple cognitive tactical radio networks coexisting in the same area. A tactical radio network is composed of a transmitter which broadcasts the same information to its multiple receivers. First, we consider the problem of power minimization subject to a minimum rate constraint and a spectral mask constraint for a single tactical radio network with multiple receivers over parallel channels (parallel multicast channels). Then, we extend the iterative waterfilling algorithm to multiple receivers for the coexistence of multiple cognitive tactical radio networks, meaning that there is no cooperation between the different networks. The power allocation is performed autonomously at the transmit side assuming knowledge of the noise variances and channel variations of the network. Simulation results show that the proposed algorithm is very robust in satisfying these constraints while minimizing the overall power in various scenarios.