In this paper, based on the phase-position perturbation method, an innovative optimal adaptive antenna technique is proposed, where the deduced radiation pattern formulas available for searching optimal solutions are ...
详细信息
In this paper, based on the phase-position perturbation method, an innovative optimal adaptive antenna technique is proposed, where the deduced radiation pattern formulas available for searching optimal solutions are used to search the optimal weighting vector. The optimal radiation pattern designs of adaptive antenna are studied by the phase-position perturbation method. Memetic algorithms are used to search the optimal weighting vector of the phase-position perturbations for the array factor. The design for an optimal radiation pattern of an adaptive antenna can not only adjustably suppress the interferers by placing nulls at the directions of the interfering sources, but at the same time provide a maximum main lobe in the direction of the desired signal, i.e., to maximize the signal-to-interference ratio. To achieve this goal, a new convergent method, referred to as the two-way convergent method for memetic algorithms, is proposed. The memetic algorithm combines a genetic algorithm and local search heuristics to solve combinatorial optimization problems. The memetic algorithm is a kind of improved type of the traditional genetic algorithm. By using a local search procedure, it can avoid the shortcomings of the traditional genetic algorithm, whose termination criteria are set up by using the trial and error method. This proposed method is also able to solve the multipath problem, which exists at the same time in this communication system. The optimal radiation pattern concept can be implemented in practical wireless communication systems. Simulation results are also given in this paper.
This paper proposes a new application based on fuzzy logic to search the optimal Step Size of the Normalized Least Mean Square (NLMS) algorithm for beamforming systems. The searching of the step size depends on the fu...
详细信息
ISBN:
(纸本)9781479984985
This paper proposes a new application based on fuzzy logic to search the optimal Step Size of the Normalized Least Mean Square (NLMS) algorithm for beamforming systems. The searching of the step size depends on the fuzzy inference results of an estimation of the final value of the cost function (J(E)) instead of using its instantaneous value. The update of the step-size is performed outside of the adaptive algorithm and given it feedback by the fuzzy inference system;therefore the step-size is still fixed for the NLMS algorithm but variable for the complete searching scheme. Simulation experimental results show that a useful approximation of the optimal step-size can he obtained far different conditions of signal-to-noise plus interference ratios (SINR) and the minimization of the mean square error for the adaptive beamforming algorithm is also achieved.
This paper proposes a new approach based on information classification algorithms, fuzzy logic and neural networks for generating the membership functions to be used for searching the optimal step size of the normaliz...
详细信息
ISBN:
(纸本)9781479975846
This paper proposes a new approach based on information classification algorithms, fuzzy logic and neural networks for generating the membership functions to be used for searching the optimal step size of the normalized least mean square adaptive algorithm, when it is applied in adaptivelinear antenna arrays. To this end a multilayer perceptron neural network, which is trained using the back propagation algorithm and the information obtained from several values estimated from the cost function of NLMS algorithm as well as the signal to interference noise ratio, generates the membership functions. Experimental results obtained by computer simulation show that the proposed approach provides fairly good estimation of the membership functions of the fuzzy logic stage used to obtain a near optimal step size. Evaluation results also show the desirable convergence properties of proposed approach when used to optimize adaptive antenna arrays.
This paper proposes a new application based on fuzzy logic to search the optimal Step Size of the Normalized Least Mean Square (NLMS) algorithm for beamforming systems. The searching of the step size depends on the fu...
详细信息
ISBN:
(纸本)9781479984992
This paper proposes a new application based on fuzzy logic to search the optimal Step Size of the Normalized Least Mean Square (NLMS) algorithm for beamforming systems. The searching of the step size depends on the fuzzy inference results of an estimation of the final value of the cost function (J_E) instead of using its instantaneous value. The update of the step-size is performed outside of the adaptive algorithm and given it feedback by the fuzzy inference system;therefore the step-size is still fixed for the NLMS algorithm but variable for the complete searching scheme. Simulation experimental results show that a useful approximation of the optimal step-size can be obtained for different conditions of signal-to-noise plus interference ratios (SINR) and the minimization of the mean square error for the adaptive beamforming algorithm is also achieved.
暂无评论