As a key technique in CDMA communication system, the multiuser detection can jointly detect the signals transmitted by all the users, thereby alleviate the “near-far” effect, cancel the MAI and the increase the system capacity. In this paper by applying neural network algorithms to multiuser detection, we have gained some significative results.The main works of this paper can be summarized as follows:1. Analyzed and researched the probability and the theory of using neural network in CDMA communication systems.2. Proposed a Lagrange neural network blind multiuser detector in the synchronous CDMA system through white Gauss channel, derived its dynamic equations, proved its stability and convergence simply, gave the circuit implement of the neural network. The simulation results showed the proposed algorithm has the fast convergence speed, and be suit to the time-varying environment. 3. In multipath channel, adopted a new cost function, converted the complex-valued optimization problem to real-valued optimization problem, solved the problem using Lagrange neural network efficiently. The simulation results show the proposed algorithm improved the calculation complexity and the convergence performance.

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