Adaptive Fuzzy Logic Based AP Selection for Scalable User-Centric Cell-Free Massive MIMO

We propose an adaptive fuzzy logic (FL) based access point (AP) selection scheme, considering multiple criteria for each user equipment (UE) to select a more reasonable AP cluster in user-centric cell-free (CF) massive multiple-input multiple-output (MIMO) systems. Except for the large-scale fading, the small-scale fading, allocated power from APs and inter-user interference are considered as important criteria for AP selection in this paper. Rather than the conventional FL method with predetermined fuzzy membership function, in the proposed adaptive FL scheme, the thresholds are adjusted adaptively according to the change of criteria's numerical ranges, which is more robust to the changing network environment. The proposed method considers the time-variation of the channel in each coherence block and remains system scalability in signal processing for data transmission and power control. This method also focuses on the AP clusters association by choosing the power and inter-user interference as criteria in FL, to avoid redundant connection and reduce interference between UEs. To achieve scalability in channel estimation, an initial association algorithm with switching scheme is proposed, making an attractive balance between UE fairness and limited AP processing capabilities. Simulation verifies that the adaptive FL based AP selection scheme outperforms other existing algorithms in terms of UE fairness, spectral efficiency and energy efficiency.