Power control for mobile DS/CDMA systems using a modified Elman neural network controller

Abstract

It is well recognized that power control is an important technique to combat the near-far effect and increase the maximum capacity in direct sequence code division multiple access (DS/CDMA) cellular systems. We propose a modified Elman (1990) neural network (MENN) based multiple-model power control scheme to keep the received power almost constant at the base station. Unlike the conventional "bang-bang" control and fuzzy control, the MENN can identify the inverse dynamical characteristics of the channel by adaptive on-line learning. The inverse channel model is then used for reverse link power control. Hence, large overshoot and long rise time can be effectively avoided. Simulations show that the fluctuation of controlled received power is satisfactory. The overshoot and channel tracking error are small.