Power prediction in mobile communication systems using an optimal neural-network structure
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
By increasing the request for mobile services, the CDMA cellular system has been used extensively. This is due to advantages of spread spectrum techniques used in CDMA systems, and their higher capacity in compare to the FDMA & the TDMA systems. Power control is a very important issue in the CDMA systems. Different types of power control are used in the CDMA. Closed loop power control which is used for solving the fast fading problem is one of these types. However, proper estimation of received signal to interference ratio (SIR), related to mobile power adjustment is essential. In this paper we will present a new and efficient method using Kalman filter for SIR estimation. This method is compared with other methods such as linear prediction and Grey prediction. Outage probability calculation for the above methods is performed. The results are presented and compared in different curves. Based on our simulation results, outage probability obtained with this new method is less than previously reported methods.