Optimization of Blind Spoofing Using Discrete Model

In order to improve the optimizing efficiency, one dimensional blind-walking optimization method is proposed, which can be realized by halving step or doubling step for the applicability test condition of the sensing point. The optimum point, then, can be reached at high rate by doubling step and converged by halving step. Current point should be updated in whole design space. The flow chart of this algorithm with operating process is put forward. And then, two optimization problems with uni-modal and multimodal objective functions are solved respectively. The simulation results show that the proposed method is better than the ordinary method, which has the advantages of fast convergence speed, less calculating amounts, and wide application scope, etc. Taking the method as innovative kernel, random research method, feasible direction method and other complex methods are improved. Its characteristics are suitable for vivid teaching like interpreting. The linear subspace-based blind and group-blind multiuser detectors recently developed represent a robust and efficient adaptive multiuser detection technique for code-division multiple-access (CDMA) systems. In this paper, we consider adaptive transmitter optimization strategies for CDMA systems operating in fading multipath environments in which these detectors are employed. We make use of more recent results on the analytical performance of these blind and group-blind receivers in the design and analysis of the transmitter optimization techniques. In particular, we develop a maximum-eigenvector-based method of optimizing spreading codes for given channel conditions and a utility-based power control algorithm for CDMA systems with blind or group-blind multiuser detection.