摘要
To improve the computational speed, the ROLS-AWS algorithm was employed in the RBF based MUD receiver. The radial basis function was introduced into the multi-user detection （MUD） firstly. Then a three-layer neural network demodulation spread-spectrum signal model in the synchronous Gauss channel was given and the multi-user detection receiver was analyzed intensively. Simulations by computer illustrate that the proposed RBF based MUD receiver employing the ROKS-AWS algorithm is better than conventional detectors and common BP neural network based MUD receivers on suppressing multiple access interference and near-far resistance.
To improve the computational speed,the ROLS-AWS algorithm was employed in the RBF based MUD receiver.The radial basis function was introduced into the multi-user detection(MUD)firstly.Then a three-layer neural network demodulation spread-spectrum signal model in the synchronous Gauss channel was given and the multi-user detection receiver was analyzed intensively.Simulations by computer illustrate that the proposed RBF based MUD receiver employing the ROLS-AWS algorithm is better than conventional detectors and common BP neural network based MUD receivers on suppressing multiple access interference and near-far resistance.
