A Direction Of Arrival(DOA) estimator based on the signal separation principle is introduced, and one of representative multidimensional estimators is established by introducing Matrix Operator projection signal steer...A Direction Of Arrival(DOA) estimator based on the signal separation principle is introduced, and one of representative multidimensional estimators is established by introducing Matrix Operator projection signal steering Vector Excision(MOVE) operation. Thanks to Alternating Separation (AS) technique, the multidimensional problem is transformed into a series of one-dimensional optimal ones. Furthermore, an equivalent simplified implementation of the AS is obtained. Finally the definiteness and uniqueness of the estimator are analyzed.展开更多
The paper investigates the problem of the design of an optimal Orthogonal Fre- quency Division Multiplexing (OFDM) receiver against unknown frequency selective fading. A fast convergent Monte Carlo receiver is propose...The paper investigates the problem of the design of an optimal Orthogonal Fre- quency Division Multiplexing (OFDM) receiver against unknown frequency selective fading. A fast convergent Monte Carlo receiver is proposed. In the proposed method, the Markov Chain Monte Carlo (MCMC) methods are employed for the blind Bayesian detection without channel es- timation. Meanwhile, with the exploitation of the characteristics of OFDM systems, two methods are employed to improve the convergence rate and enhance the efficiency of MCMC algorithms. One is the integration of the posterior distribution function with respect to the associated channel parameters, which is involved in the derivation of the objective distribution function; the other is the intra-symbol differential coding for the elimination of the bimodality problem resulting from the presence of unknown fading channels. Moreover, no matrix inversion is needed with the use of the orthogonality property of OFDM modulation and hence the computational load is significantly reduced. Computer simulation results show the effectiveness of the fast convergent Monte Carlo receiver.展开更多
基金Partially supported by the National Natural Science Foundation of China(No.60372036), Natural Science Foundation of Shaanxi Province (2002F24) and Funds from the Information Industry Ministry of China (2002XK610039)
文摘A Direction Of Arrival(DOA) estimator based on the signal separation principle is introduced, and one of representative multidimensional estimators is established by introducing Matrix Operator projection signal steering Vector Excision(MOVE) operation. Thanks to Alternating Separation (AS) technique, the multidimensional problem is transformed into a series of one-dimensional optimal ones. Furthermore, an equivalent simplified implementation of the AS is obtained. Finally the definiteness and uniqueness of the estimator are analyzed.
基金Partially supported by the National Natural Science Foundation of China (No.60172028).
文摘The paper investigates the problem of the design of an optimal Orthogonal Fre- quency Division Multiplexing (OFDM) receiver against unknown frequency selective fading. A fast convergent Monte Carlo receiver is proposed. In the proposed method, the Markov Chain Monte Carlo (MCMC) methods are employed for the blind Bayesian detection without channel es- timation. Meanwhile, with the exploitation of the characteristics of OFDM systems, two methods are employed to improve the convergence rate and enhance the efficiency of MCMC algorithms. One is the integration of the posterior distribution function with respect to the associated channel parameters, which is involved in the derivation of the objective distribution function; the other is the intra-symbol differential coding for the elimination of the bimodality problem resulting from the presence of unknown fading channels. Moreover, no matrix inversion is needed with the use of the orthogonality property of OFDM modulation and hence the computational load is significantly reduced. Computer simulation results show the effectiveness of the fast convergent Monte Carlo receiver.
