Self-tuning Adaptive Algorithms in the Power Control of Wcdma Systems

Power control is an essential radio resource function in WCDMA systems. It is needed to compensate the nearfar effect, i.e., a strong signal overriding a weaker one at a receiver. In practical systems power control is handled so that a receiver measures the signal-to-interference ratio (SIR) and compares it to a target value. Based on this comparison, the receiver requests the transmitter to either decrease or increase its transmitter power by a fixed amount, typically 1 dB. A more sophisticated approach has been proposed in [0], where an adaptive self-tuning controller (STC) with generalized minimum variance (GMV) criterion was applied in the closed-loop power control. Simulations indicated that the proposed method outperformed the conventional bang-bang type power control algorithm proposed in [1]. However, it is not clear how to select the various polynomials included in the design of the GMV controller to maximize the controller performance. In this paper we use system identification methods for modeling the WCDMA closed-loop power control. The power control process is modeled using a convenient parameterized linear structure, which can be used to tune the GMV controller performance in the design phase. The model is identified using inputoutput data collected from a radio network simulator by opening the power control loop of a randomly selected user. The results give significant insight to the power control process and are useful in the design of adaptive power control algorithms.