Adaptive kernel methods for CDMA systems

This paper discusses a new adaptive learning approach for code division multiple access (CDMA) systems. The author extends the previous work of Gong et al. (1999) where they applied support vector machines (SVM) for CDMA signal recovery using a modified version of SVM based on a mean squared error criterion called least squares SVM. The least squares SVM solution is found by solving a set of linear equations. An advantage of this formulation is that the algorithm can be implemented adaptively online. The least squares SVM solutions are compared via simulations to other conventional CDMA receivers and found to have comparable performance to standard SVM solutions. The least squares SVM are promising as they offer simple methods of realizing nonlinear receivers, can be implemented adaptively, and can work in time-varying environments that are typical for wireless communications