Title :
Performance Analysis of Primary User RSS/DoA Estimation and Localization in Cognitive Radio Networks Using Sectorized Antennas
Author :
Jun Wang ; Werner, J. ; Valkama, Mikko ; Cabric, Danijela
Author_Institution :
Dept. of Electr. Eng., Univ. of California Los Angeles, Los Angeles, MD, USA
Abstract :
In this letter we present analytical performance evaluation of primary user (PU) RSS/DoA estimation and localization through cooperating cognitive radios (CRs). We assume that the CRs are equipped with sectorized antennas, an antenna model we use to describe different types of directional antennas with a low hardware overhead (e.g. only a single RF front-end). We first derive the bias and mean square error (MSE) of RSS and DoA estimates based on the simplified least square (SLS) algorithm. We then proceed to derive the theoretical MSE of PU localization using the Stansfield algorithm that fuses SLS estimates from multiple nodes. Simulation results studying the impact of various system parameters on the RSS/DoA estimation and localization accuracy are presented to verify theoretical derivations, as well as provide design guidelines for localization systems based on sectorized antennas.
Keywords :
cognitive radio; cooperative communication; direction-of-arrival estimation; directive antennas; least mean squares methods; radio networks; CR; MSE; PU localization; SLS algorithm; Stansfield algorithm; cognitive radio networks; directional antennas; mean square error; multiple nodes; primary user RSS-DoA estimation; sectorized antennas; simplified least square algorithm; Algorithm design and analysis; Antenna arrays; Direction-of-arrival estimation; Estimation; Shadow mapping; Signal to noise ratio; RSS/DoA estimation; Sectorized antennas; Stansfield algorithm; passive localization; performance analysis;
Journal_Title :
Wireless Communications Letters, IEEE
DOI :
10.1109/WCL.2014.021314.140007
