On Channel Gain Estimation And Robust Energy Detection

With the growth of mobile communication,the problems of spectrum resources shortage and spectrum underutilization are increasingly prominent.Spectrum sharing is considered as one of the candidate technologies to alleviate these problems.In order to realize spectrum sharing between primary users and cognitive users,cognitive radio system needs to carry out channel gain estimation and robust spectrum sensing.Therefore,channel gain estimation and robust spectrum sensing are important technologies to realize spectrum sharing.This thesis investigates the methods about channel gains estimation and spectrum sensing.The main contributions are summarized as follows:1.The thesis proposes a channel gains estimation method to estimate primary-channel gain and cross-channel gain simultaneously.Firstly,a two-hop relay system model of primary users is established,where a cognitive user acts as a relay node Then,we analyze the relationship between the transmit power of a primary receiver and the transmit power of a cognitive transmitter and obtain the analytic expression.Finally,by employing the relationship,an estimation method is developed,which enables the SU-Tx to acquire the primary-channel and cross-channel gains simultaneously.The performance of the proposed estimator is analyzed.2.The thesis proposes the robust energy detection against noise uncertainty.Due to the sparsity of the covariance matrix of OFDM signals,we reveal that the likelihood ratio test approximates to energy detection(ED)at low signal to noise ratio.However,the noise power uncertainty can degrade the performance of ED severely.To tackle this issue,we derive the relationship among noise power,total power and autocorrelation coefficient of received signals,and propose an unbiased estimator of noise power.Finally,a robust energy detection against noise uncertainty is proposed,and the analytical expression of theoretical performance is derived.3.An OFDM experimental system based on GNU Radio and USRP(Universal Software Radio Peripheral)is established.A robust spectrum sensing method is verified by using experimental data generated by the system.Finally,numerical results demonstrate that the method works well under noise uncertainty.