8th International Conference on Cognitive Radio Oriented Wireless Networks

Research Article

Primary User DoA and RSS Estimation in Cognitive Radio Networks Using Sectorized Antennas

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  • @INPROCEEDINGS{10.4108/icst.crowncom.2013.252049,
        author={Janis Werner and Jun Wang and Aki Hakkarainen and Mikko Valkama and Danijela Cabric},
        title={Primary User DoA and RSS Estimation in Cognitive Radio Networks Using Sectorized Antennas},
        proceedings={8th International Conference on Cognitive Radio Oriented Wireless Networks},
        publisher={ICST},
        proceedings_a={CROWNCOM},
        year={2013},
        month={11},
        keywords={doa and rss estimation sectorized antennas},
        doi={10.4108/icst.crowncom.2013.252049}
    }
    
  • Janis Werner
    Jun Wang
    Aki Hakkarainen
    Mikko Valkama
    Danijela Cabric
    Year: 2013
    Primary User DoA and RSS Estimation in Cognitive Radio Networks Using Sectorized Antennas
    CROWNCOM
    IEEE
    DOI: 10.4108/icst.crowncom.2013.252049
Janis Werner1,*, Jun Wang2, Aki Hakkarainen1, Mikko Valkama1, Danijela Cabric2
  • 1: Tampere University of Technology
  • 2: University of California Los Angeles
*Contact email: janis.werner@tut.fi

Abstract

Received-signal-strength (RSS) and direction-of-arrival (DoA) are the sufficient measurements to solve the primary user localization problem in cognitive radio networks. In this paper we consider using energy measurements from sectorized antenna to estimate RSS and DoA of a primary user. Abstracting from practical antenna types, we define a sectorized antenna as an antenna that can be set to different operating modes, each of which resulting in a selectivity of those signals that arrive from within a certain, continuous range of angles, i.e.\ a sector. We first characterize the achievable performance of RSS and DoA estimations using energy measurements from sectorized antennas by means of the Cramer-Rao Bound (CRB), which provides a lower bound on the estimation accuracy of any unbiased estimator. We then propose a practical RSS and DoA estimator, namely the simplified least squares (SLS) algorithm. The SLS algorithm minimizes a cost function obtained from two largest energy measurements among all sectors, and its accuracy closely approaches the CRB. Simulation results studying the impact of important system parameters, such as SNR, number of sectors and number of samples, on the achievable accuracy specified by the CRB and the SLS algorithm are presented.