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Blind equalization based on compensation fuzzy neural network has proposed. It using compensation neurons to get tradeoff between negative and active operation, thus the network can be training using fuzzy rule of initial right or wrong setting, and fault tolerance and stability are improved. Simulations results show that this algorithm has faster convergence speed and less residual error compared...
Three applications in wireless networks where model-free stochastic learning is applicable, are discussed. The learning based optimization problems are formulated and simulation results are presented. Some open issues are also discussed.
In this paper the performance of the ESPAR (electronically steerable passive array radiator) antenna in suppressing both the co-channel and inter-symbol interferences is compared with the conventional circular and linear arrays. For this purpose, the STAP (space-time adaptive processing) is implemented in both arrays with equal elements. Simulation results show that when the pattern of the ESPAR antenna...
This paper addresses adaptive channel estimation for time-varying mobile wireless channels with nonstationary statistics. We presents a reduced complexity adaptive channel estimator based on a set membership filtering approach known as the Optimal Bounding Ellipsoid (OBE) algorithm. To exploit time and frequency domain correlation properties of the channel in an efficient low-complexity way, we allow...
This paper studies efficient complex valued matrix manipulations for multi-user STBC-MIMO decoding. A novel method called Alamouti blockwise analytical matrix inversion (ABAMI) is proposed for the inversion of large complex matrices that are based on Alamouti sub-blocks. Another method using a variant of Givens rotation is proposed for fast QR decomposition of this kind of matrices. Our solutions...
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