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.
Highlights
1 Introduction Inverse control has been used for several applications such as channel equalization [1, 2] automatic gain control (AGC) [3], noise and interference cancelation [4, 5], and transmission power control [6, 7] which is the topic of this paper
The least mean square (LMS) algorithm is not directly suitable for active control applications where the adaptive filter works as a controller for a time-variant system
The filteredx least mean square (FxLMS) algorithm is a good choice for that kind of applications [4]
Summary
Inverse control has been used for several applications such as channel equalization [1, 2] automatic gain control (AGC) [3], noise and interference cancelation [4, 5], and transmission power control [6, 7] which is the topic of this paper. The proposed algorithm provides a fast adapting inverse power control solution that does not overshoot the power level as much after a fade as the conventional solution in [14]. Several simulation studies are performed with the practical power control algorithms both in additive white Gaussian noise (AWGN) and fading channels. There is no loss in performance in dividing the total transmitted signal energy differently among the L channels, and the model does not change the comparison between the selected power control algorithms. The fading of the adjacent subcarriers is not uncorrelated, but this is typical in all OFDM systems, and it is in practice handled with frequency domain interleaving With these assumptions, our system model represents a MIMOOFDM system. MSE is compared to signal power, in this case transmission power
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