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中文摘要：
为了解决认知无线电网络中次用户对主用户进行定位的问题，提出了一种加权最小二乘的迭代定位算法．采用两状态马尔可夫模型作为主用户通信模型，能量检测作为次用户的感知模型．该算法可以在不干扰主用户正常工作的情况下，利用次用户之间的合作感知结果进行定位，并估计出主用户的三维地理位置信息．提出了一种可以降低定位算法复杂度的简化算法．通过对定位问题的理论分析，求出了均方误差的Cramer-Rao理论下界．仿真结果表明，算法的均方误差非常接近Cramer-Rao理论下界，能有效地估计主用户的三维位置信息。提高定位精度．
英文摘要：
A detection probability based iterative localization algorithm using weighted least squares method is proposed to solve the secondary users＇ problem of locating the primary users in cognitive radio networks. The primary users＇ transmission model is described as a 2-state Markov model and energy detection is used by secondary users for sensing. The proposed algorithm leverages the cooperative spectrum sensing to locate the primary users and is working transparently to the primary system. Furthermore, the proposed localization algorithm is able to acquire the three-dimensional position information of the primary user. Next, a simplified version of the algorithm is introduced to reduce the complexity. We have also conducted an evaluation and obtained the Cramer-Rao lower bound （CRLB） in terms of the mean square error of the algorithm. Simulation shows that the performance of the improved algorithm approaches the CRLB and is able to estimate the three-dimensional positions of the primary users effectively and promote the localization precision.
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