A unified framework for adaptive inverse power control

Abstract

In this paper, a unified framework for adaptive inverse power control is developed. It is based on a modified filtered-x least mean square (MFxLMS) algorithm that is proposed and analyzed. A practical version of the algorithm for closed loop power control is also developed. The filtered-x least mean square (FxLMS) algorithm is widely used for inverse control such as noise cancelation. This is the first paper to apply the algorithm for power control. We have modified the conventional FxLMS algorithm by adding absolute value blocks since power control does not need phase information. The modification makes the algorithm more robust and requires fewer bits to be transmitted in the feedback link. The main contribution of the paper is that the proposed algorithm can be seen as generalized inverse control to be used in power control research. It gives a unified framework for several existing algorithms, linking them to the least mean square (LMS) literature. Numerical results are provided, comparing the performance of the proposed algorithm to existing practical algorithms used, e.g., in Third Generation Partnership Project (3GPP) long-term evolution (LTE) systems.