With the emergence of the fifth generation(5G)cognitive radio(CR)networks,inter-ference-tolerant CR network research is gaining interest.An interference-tolerant CR network is made up of a mixture of licensed primary users(PUs)and unlicensed secondary users(SUs).The CRs share the spectrum resource by meeting two basic requirements:low energy consumption and low radio pollution to each other.Previous studies on interference-tolerant CR networks have tended to focus on static CRU to static primary network(sPN)(sCRU-sPN)interference and static CRU to static CRU(sCRU-sCRU)interference.In contrast to these two types of interference,in this thesis,we consider another type of interference which can be found in practical CR networks.This is mobile CRU to sPN(mCRU-sPN)interference.If the sPN contains some passive PU receivers,then the introduction of mCRU,makes in-terference mitigation in mCRU-sPN networks even more challenging.This thesis empowers the sPN base station with an interference management scheme which utilizes time-reversal communication in order to provide spatial focusing at an intended SU receiver.Thus,spatial focusing reduces interference to the passive PU receivers in the network.Moreover,time-reversal communication enables us to circumnavigate the difficult problem of determining the location of passive PU receivers.However,time-reversal communication is dependent on robust channel estimation.Under time-varying channel conditions or imperfect channel estimation,the performance of time-reversal communication deteriorates immensely.The deterioration is due to the nature of time-reversal communication heavily relying on channel reciprocity and channel stationarity to function properly.Hence,the implementation of time-reversal communication under rapidly time-varying channel conditions is a challenging open problem.To ameliorate this deterioration,we propose to design a nonstationary time-varying non-causal Wiener filter in order to solve the channel estimation problem.The proposed Wiener filter is based on the time-varying power spectrum.The time-varying power spectrum is obtained by modelling the rapidly time-varying channel as a locally stationary process.This means that over small intervals,the channel can be viewed as approximately stationary and correlated inside these stationary intervals.Consequently,the time-varying spectrum can be easily calculated by estimating the covariance of the Wigner-Ville distribution of each locally stationary interval.Subsequently,after obtaining the proposed Wiener filter solution,the sPN base station utilizes the Wiener filter to eliminate the symbol-timing synchronization error from the round-trip time-of-flight measurements of its pulse-shaped orthogonal frequency division multiplex-ing(PS-OFDM)transmission.The base station is then able to accurately determine the distance between itself and the mCRU by measuring the round-trip time-of-flight of the PS-OFDM signal.The base station also employs minimum-variance distortionless response(MVDR)beam-forming in order to estimate the direction-of-arrival(DOA)of the returning PS-OFDM uplink signals from the mCRU transmitter.However,under time-varying channel propagation con-ditions induced by the mCRU mobility.The MVDR beamforming performance becomes suboptimal due to the nonstationary nature of the impinging mCRU waveforms onto the fixed base station antenna array.We propose to use time-frequency Wigner-Ville distribution in the design of a robust nonstationary MVDR beamformer instead of the traditional signal covariance matrix.Time-frequency distributions are more appropriate in handling nonstationary impinging signals than the traditional signal covariance matrix,because of their ability to localize the non-stationary signal power in the time-frequency domain.Hence,enhancing the signal-to-noise ratio(SNR),leading to improved DOA estimates.Finally,as a result of the distance and DOA measurements,the sPN base station is able to localize the position of the peripatetic mCRU in relation to its area of coverage.Consequently,if the mCRU wonders into the sPN protection range,the base station can employ a quality of service(QoS)constrained power minimization algorithm in order to boost the QoS by minimizing the mCRU power transmission.This leads to the maximization of signal-to-interference noise ratio(SINR)of the sPN,thus creating an interference-tolerant CR network.